1) The document introduces modeling and simulation through an introductory lecture. It discusses the goals of modeling, simulation, and the course.
2) It describes what models and simulations are, and provides examples of different types of models and applications of simulation.
3) The key steps in building a simulation model are outlined, including defining the goal, collecting input data, verifying and validating the model, and analyzing output.
This document provides information on using simulation software Stella to teach concepts related to oscillation and the pendulum. It outlines the steps to effectively integrate simulation into the classroom, including: preparation, briefing students, demonstrating the simulation model, guided practice with students, checking for understanding, independent student practice, and closing the lesson. Specific examples are given for using the Pendulum Story simulation model to investigate relationships between variables like mass, displacement, and period of a pendulum. The document also discusses how simulations can motivate students to learn through intrinsic factors like curiosity and exploration of situations not possible in real life.
Simulation is used when it is difficult to construct an analytical model to solve a problem. It allows experimenting with changes to variables and parameters to understand how a real system performs without implementing changes in the real system. Some applications of simulation include aircraft design, pilot training, production planning, and modeling queuing systems. Simulation involves building a computer model of a system and running experiments to answer "what if" questions about how changes affect outcomes. It is useful for complex problems that cannot be solved analytically and allows low-cost experimentation with models of real systems.
The information in this slide is very useful for me to do the assignment regarding the simulation in which we have to report together with the presentation...
This document discusses simulation modeling and its applications. It begins with definitions of simulation as operating a model of a system over time to study its behavior. Simulation is used to evaluate system performance under different configurations before implementation. The key advantages are exploring "what if" scenarios without disrupting real systems and testing new designs. Common applications include manufacturing, construction, military, logistics and transportation. The document outlines the steps in a simulation study and discusses when simulation is appropriate versus not. It concludes with references on modeling and simulation.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
This document discusses systems analysis and simulation. It defines a system as a collection of elements that work together to achieve a goal. There are two main types of systems: discrete systems where state variables change at separate points in time, and continuous systems where state variables change continuously over time. A model represents a system in order to study it, as experimenting directly with the real system may not be possible or wise. Simulation models can be static or dynamic, deterministic or stochastic, discrete or continuous. Discrete-event simulation specifically models systems as they progress through time as a series of instantaneous events.
Simulation is a technique used to model complex systems and estimate statistical measures by representing the system and modeling individual elements' behavior randomly over time. Systems can be discrete, changing at separate points, or continuous, changing continuously. Simulation involves defining the problem, conceptually modeling the system, collecting data, coding the model, validating it, experimenting and analyzing results. It allows studying systems that would be impossible, too expensive, or impractical to study directly.
Operations research originated during World War II when scientists applied scientific methods to military operations. It has since been applied to many domains including business, transportation, and public health. Some key OR techniques include linear programming, transportation models, assignment problems, queuing theory, simulation, and inventory control models. The OR process involves formulating the problem, developing a mathematical model, selecting data inputs, solving the model, validating the model, and implementing the solution. Models can be classified as deterministic or stochastic, descriptive, predictive, or prescriptive, static or dynamic, and analytical or simulation-based. OR aims to help management make better decisions through quantitative analysis and optimization of systems and processes.
This document provides information on using simulation software Stella to teach concepts related to oscillation and the pendulum. It outlines the steps to effectively integrate simulation into the classroom, including: preparation, briefing students, demonstrating the simulation model, guided practice with students, checking for understanding, independent student practice, and closing the lesson. Specific examples are given for using the Pendulum Story simulation model to investigate relationships between variables like mass, displacement, and period of a pendulum. The document also discusses how simulations can motivate students to learn through intrinsic factors like curiosity and exploration of situations not possible in real life.
Simulation is used when it is difficult to construct an analytical model to solve a problem. It allows experimenting with changes to variables and parameters to understand how a real system performs without implementing changes in the real system. Some applications of simulation include aircraft design, pilot training, production planning, and modeling queuing systems. Simulation involves building a computer model of a system and running experiments to answer "what if" questions about how changes affect outcomes. It is useful for complex problems that cannot be solved analytically and allows low-cost experimentation with models of real systems.
The information in this slide is very useful for me to do the assignment regarding the simulation in which we have to report together with the presentation...
This document discusses simulation modeling and its applications. It begins with definitions of simulation as operating a model of a system over time to study its behavior. Simulation is used to evaluate system performance under different configurations before implementation. The key advantages are exploring "what if" scenarios without disrupting real systems and testing new designs. Common applications include manufacturing, construction, military, logistics and transportation. The document outlines the steps in a simulation study and discusses when simulation is appropriate versus not. It concludes with references on modeling and simulation.
FellowBuddy.com is an innovative platform that brings students together to share notes, exam papers, study guides, project reports and presentation for upcoming exams.
We connect Students who have an understanding of course material with Students who need help.
Benefits:-
# Students can catch up on notes they missed because of an absence.
# Underachievers can find peer developed notes that break down lecture and study material in a way that they can understand
# Students can earn better grades, save time and study effectively
Our Vision & Mission – Simplifying Students Life
Our Belief – “The great breakthrough in your life comes when you realize it, that you can learn anything you need to learn; to accomplish any goal that you have set for yourself. This means there are no limits on what you can be, have or do.”
Like Us - https://www.facebook.com/FellowBuddycom
This document discusses systems analysis and simulation. It defines a system as a collection of elements that work together to achieve a goal. There are two main types of systems: discrete systems where state variables change at separate points in time, and continuous systems where state variables change continuously over time. A model represents a system in order to study it, as experimenting directly with the real system may not be possible or wise. Simulation models can be static or dynamic, deterministic or stochastic, discrete or continuous. Discrete-event simulation specifically models systems as they progress through time as a series of instantaneous events.
Simulation is a technique used to model complex systems and estimate statistical measures by representing the system and modeling individual elements' behavior randomly over time. Systems can be discrete, changing at separate points, or continuous, changing continuously. Simulation involves defining the problem, conceptually modeling the system, collecting data, coding the model, validating it, experimenting and analyzing results. It allows studying systems that would be impossible, too expensive, or impractical to study directly.
Operations research originated during World War II when scientists applied scientific methods to military operations. It has since been applied to many domains including business, transportation, and public health. Some key OR techniques include linear programming, transportation models, assignment problems, queuing theory, simulation, and inventory control models. The OR process involves formulating the problem, developing a mathematical model, selecting data inputs, solving the model, validating the model, and implementing the solution. Models can be classified as deterministic or stochastic, descriptive, predictive, or prescriptive, static or dynamic, and analytical or simulation-based. OR aims to help management make better decisions through quantitative analysis and optimization of systems and processes.
This document provides an overview and study guide for an engineering programming course using C++. It includes information on prerequisites, prescribed materials, course objectives, structure, administration, and evaluation. The course aims to teach object-oriented programming skills and problem solving using C++. It is divided into five units covering C++ coding elements, object-oriented design methodology, C++ classes and objects, graphical user interfaces, and interface programming. Students will complete lectures, tutorials, practical sessions, and self-study to learn programming concepts and skills to solve basic engineering problems. Evaluation will include module tests, practical assignments, and a final examination.
Simulation models allow students to participate in and observe simplified representations of real-world systems and processes over time. The document discusses key advantages and disadvantages of using simulations in education, including that simulations allow experimentation without building physical systems, help uncover unexpected behaviors, and can motivate students. Simulations are as effective as conventional teaching methods for conveying subject matter knowledge and more effective for knowledge retention. The conclusion emphasizes that simulations are a powerful educational tool that give students freedom to explore models and observe results in an interesting and fun way.
This document discusses advanced knowledge modeling techniques. It covers topics such as:
- Using viewpoints to introduce multiple hierarchies and specialization of concepts.
- Representing mathematical expressions and logical formulae using an imported language.
- Specifying rules and constraints and using variables to eliminate ambiguities.
- The importance of knowledge sharing and reuse through ontologies and domain standards.
- Different types of ontologies and languages for ontology specification.
- Maintaining a catalog of inference types as building blocks for knowledge models.
- Dealing with dynamic method selection by introducing a method selection task.
- Modeling strategic knowledge about combining tasks as a separate reasoning process.
This document discusses object-oriented analysis and design (OOAD) and the unified process. It introduces OOAD and the unified process framework, which includes inception, elaboration, construction, and transition phases. It also covers the unified modeling language (UML), including use case diagrams, class diagrams, and other diagram types. Specific topics covered include identifying actors and use cases, drawing associations and relationships between actors and use cases, class notation, and an example use case diagram for an alarm clock system.
Machine learning is a subfield of computer science that allows computers to learn without being explicitly programmed. It builds models from sample data to make data-driven predictions or decisions. Machine learning is used for tasks like spam filtering, intrusion detection, optical character recognition, and computer vision. It involves supervised learning from labeled examples, unsupervised learning to find patterns in unlabeled data, and reinforcement learning where a system interacts with an environment and receives rewards or punishments. The goal is for the learning system to generalize from its training data to perform accurately on new examples.
This document provides an overview of modeling and simulation. It defines modeling as representing a system to enable predicting the effects of changes. Simulation involves running experiments on a model. The key steps in modeling and simulation projects are: 1) identifying the problem, 2) formulating and developing the model, 3) validating the model, 4) designing simulation experiments, 5) performing simulations, and 6) analyzing and presenting results. Modeling and simulation can be used for a variety of purposes including education, design evaluation, forecasting, and risk assessment.
Research Questions for Validation and Verification in the Context of Model-Ba...Michalis Famelis
This document summarizes the key discussion points and research questions identified by a working group on model-based engineering and verification and validation. The group identified 8 thematic categories for focusing research: 1) bridging the gap between models and formal verification techniques, 2) refining existing V&V methodologies for model-based development, 3) relating design-time models to runtime behavior, 4) determining appropriate properties to verify, 5) verifying model transformations, 6) handling informal, formal and incomplete modeling, 7) benchmarking and comparing V&V tools, and 8) leveraging domain-specific languages. For each category, the document outlines the current status and poses open research questions to guide future work at the intersection of
This document discusses knowledge model templates for reusing elements when creating new knowledge models. It presents different types of tasks like classification, assessment, diagnosis, and monitoring that knowledge models can perform. For each task, it provides the typical inference structure, control structure, and domain schema that can be reused from templates. It also discusses how task templates can be customized for different variations and domains.
The document provides information on installing HandiSwage cable railing systems. It describes HandiSwage as the lowest cost cable railing that is easy to use with a swage tool. Key steps for installation include drilling post holes spaced 3 inches apart, measuring and cutting cable runs, swaging one end of the cable, installing fittings and tensioning cables starting from the middle. Cable sleeves and double posts can be used on corners and stairs to eliminate hardware.
70% of all SAP on Linux customers rely on SUSE Linux
Reduce your SAP infrastructure TCO by up to 80%
Intel's Enterprise Computing Platform is pulling ahead of UNIX
How to get your SAP landscapes to SUSE Linux on Intel: SAP Consulting by Texperts
This document contains an evaluation of a language teacher's certification dossier. It evaluates the teacher's ability to plan and evaluate lessons according to a curriculum, understand the institutional context, and prepare students for language examinations. The evaluation marks that the teacher provided evidence of stating objectives, defining lesson aims, and selecting appropriate activities. In remarks, the evaluator praises the teacher for using real situations to put lessons into practice. The original evaluation also positively assessed a series of integrated lessons on planning a meal that incorporated vocabulary from previous lessons and culminated in the students and teacher sharing a meal together.
The document discusses various considerations for planning and structuring a training course, including determining objectives, number of participants, venue requirements, and seating arrangements. It provides recommendations for each, describing advantages and disadvantages of different options. For example, it suggests limiting participants to 20 and assessing distractions at the venue. For seating, it analyzes formats like rows of chairs, a U-shape, banquet style, conference tables, and circles of chairs. The goal is to choose arrangements conducive to participation and that facilitate discussions, group work, and trainer movement in the room.
Skype marinair2011 Blog www.LRLiderTime.blogspot.ru
Приглашаем к сотрудничеству!
Крупная Немецкая компания прямых продаж LR HEALTH&BEAUTY SYSTEMS проводит набор менеджеров для рекламы компании и ее продукции для красоты и здоровья в России, Украине и Казахстане. Обучение проводится для менеджеров компании бесплатно. Критерии отбора: обучаемость, коммуникабельность, порядочность, активная жизненная позиция. Начинать работать у нас возможно от 18 лет, образование значения не имеет, пол тоже. Приветствуется опыт работы в компаниях прямых продаж, страховых компаниях, в сетевых компаниях, в торговле, бухгалтерии, административной должности. Сотрудники компании имеют возможность получить весь ассортимент товаров по закупочной цене. При выполнении условий компании по продажам продукции дальнейшее обучение в г.Москва, а также обучение за границей. Возможно сотрудничество с ИП и юридич.лицами. Телефон для связи 89136910033
Hackathon - Mapping da National Core a INSPIRE (Hydrography)smespire
webinar smeSpire "Hackathon Online - “Trasformazione di dataset spaziali open conformemente a INSPIRE” (2014-02-25).
Presentation about possible mapping between Italian topographic database specifications and INSPIRE (Hydrography).
Presented by Giuliana Ucelli (Informatica Trentina) with Daniela Ferrari (Provincia Autonoma Trento), Jody Marca and Piergiorgio Cipriano (Sinergis)
This paper discusses innovative tourism practices in India, including opportunities and challenges. It outlines several types of innovative tourism that have grown in India, such as medical tourism, spiritual tourism, and cultural tourism. Medical tourism involves traveling to India for affordable private medical care and treatments. Spiritual tourism is a major sector in India, with many traveling for religious purposes. Cultural tourism allows foreigners to experience India's diverse cultural and religious traditions through tours of festivals and rural/agricultural areas. However, the paper notes there is still room for improvement in innovative tourism in India.
Miracle Workers How Utilities Can Generate More Goodwill
Z-Pack Pfizer Can’t Assume that Science Will Trump a Scare Story
Livestrong Life After Lance is Possible—Telling the Small Stories Will Yield Big Results
The NYC Soda Ban Another Solution in Search of a Problem
LEVICK In the News
Blogs Worth Following
SIGN UP for LEVICK Insights
Este manual tiene como objetivo guiar la elaboración de estudios de prefactibilidad y factibilidad para proyectos de carreteras. Explica el ciclo de proyectos, la identificación del problema y las alternativas, la formulación del proyecto, el análisis beneficio-costo y criterios de rentabilidad, y la evaluación económica y financiera del proyecto. El manual fue desarrollado por un equipo de expertos nicaragüenses con el apoyo del gobierno de Dinamarca para normalizar los procesos de revisión de estud
Embracing INSPIRE in a legacy veterinary data management systemsmespire
The document discusses embracing INSPIRE standards in IZSVe's legacy veterinary data management system. IZSVe and 3DGIS are working together on the project. They are designing a new data model aligned with INSPIRE that can migrate IZSVe's legacy spatial data and support webGIS applications. This will improve data sharing and analysis within the veterinary community while making the data INSPIRE compliant. The new model structures the data better and allows different levels of detail.
Tugas ini membahas peranti keluaran (output device) yang meliputi monitor, printer, plotter, microfilm, dan audio. Beberapa poin penting yang dijelaskan adalah jenis-jenis monitor seperti CRT, LCD, resolusi dan ukuran monitor. Jenis-jenis printer seperti impact, thermal, inkjet, dan laser beserta prinsip kerjanya. Plotter digunakan untuk menghasilkan gambar berkualitas tinggi. Microfilm menyimpan banyak halaman dalam setiap lembarnya. Audio d
This document provides tips for scientists on how to spread their discoveries to the general public through journalists and media outlets. It advises focusing on practical consequences and everyday life impacts to attract journalists' interest. It also suggests using catchy opening lines and focusing on the intended audience when reaching out to general news publications versus scientific magazines. The document emphasizes making the message social through groups like "Dibattito scienza" on Facebook and considering both the effectiveness and ethics of experiments involving animals.
This document provides an overview and study guide for an engineering programming course using C++. It includes information on prerequisites, prescribed materials, course objectives, structure, administration, and evaluation. The course aims to teach object-oriented programming skills and problem solving using C++. It is divided into five units covering C++ coding elements, object-oriented design methodology, C++ classes and objects, graphical user interfaces, and interface programming. Students will complete lectures, tutorials, practical sessions, and self-study to learn programming concepts and skills to solve basic engineering problems. Evaluation will include module tests, practical assignments, and a final examination.
Simulation models allow students to participate in and observe simplified representations of real-world systems and processes over time. The document discusses key advantages and disadvantages of using simulations in education, including that simulations allow experimentation without building physical systems, help uncover unexpected behaviors, and can motivate students. Simulations are as effective as conventional teaching methods for conveying subject matter knowledge and more effective for knowledge retention. The conclusion emphasizes that simulations are a powerful educational tool that give students freedom to explore models and observe results in an interesting and fun way.
This document discusses advanced knowledge modeling techniques. It covers topics such as:
- Using viewpoints to introduce multiple hierarchies and specialization of concepts.
- Representing mathematical expressions and logical formulae using an imported language.
- Specifying rules and constraints and using variables to eliminate ambiguities.
- The importance of knowledge sharing and reuse through ontologies and domain standards.
- Different types of ontologies and languages for ontology specification.
- Maintaining a catalog of inference types as building blocks for knowledge models.
- Dealing with dynamic method selection by introducing a method selection task.
- Modeling strategic knowledge about combining tasks as a separate reasoning process.
This document discusses object-oriented analysis and design (OOAD) and the unified process. It introduces OOAD and the unified process framework, which includes inception, elaboration, construction, and transition phases. It also covers the unified modeling language (UML), including use case diagrams, class diagrams, and other diagram types. Specific topics covered include identifying actors and use cases, drawing associations and relationships between actors and use cases, class notation, and an example use case diagram for an alarm clock system.
Machine learning is a subfield of computer science that allows computers to learn without being explicitly programmed. It builds models from sample data to make data-driven predictions or decisions. Machine learning is used for tasks like spam filtering, intrusion detection, optical character recognition, and computer vision. It involves supervised learning from labeled examples, unsupervised learning to find patterns in unlabeled data, and reinforcement learning where a system interacts with an environment and receives rewards or punishments. The goal is for the learning system to generalize from its training data to perform accurately on new examples.
This document provides an overview of modeling and simulation. It defines modeling as representing a system to enable predicting the effects of changes. Simulation involves running experiments on a model. The key steps in modeling and simulation projects are: 1) identifying the problem, 2) formulating and developing the model, 3) validating the model, 4) designing simulation experiments, 5) performing simulations, and 6) analyzing and presenting results. Modeling and simulation can be used for a variety of purposes including education, design evaluation, forecasting, and risk assessment.
Research Questions for Validation and Verification in the Context of Model-Ba...Michalis Famelis
This document summarizes the key discussion points and research questions identified by a working group on model-based engineering and verification and validation. The group identified 8 thematic categories for focusing research: 1) bridging the gap between models and formal verification techniques, 2) refining existing V&V methodologies for model-based development, 3) relating design-time models to runtime behavior, 4) determining appropriate properties to verify, 5) verifying model transformations, 6) handling informal, formal and incomplete modeling, 7) benchmarking and comparing V&V tools, and 8) leveraging domain-specific languages. For each category, the document outlines the current status and poses open research questions to guide future work at the intersection of
This document discusses knowledge model templates for reusing elements when creating new knowledge models. It presents different types of tasks like classification, assessment, diagnosis, and monitoring that knowledge models can perform. For each task, it provides the typical inference structure, control structure, and domain schema that can be reused from templates. It also discusses how task templates can be customized for different variations and domains.
The document provides information on installing HandiSwage cable railing systems. It describes HandiSwage as the lowest cost cable railing that is easy to use with a swage tool. Key steps for installation include drilling post holes spaced 3 inches apart, measuring and cutting cable runs, swaging one end of the cable, installing fittings and tensioning cables starting from the middle. Cable sleeves and double posts can be used on corners and stairs to eliminate hardware.
70% of all SAP on Linux customers rely on SUSE Linux
Reduce your SAP infrastructure TCO by up to 80%
Intel's Enterprise Computing Platform is pulling ahead of UNIX
How to get your SAP landscapes to SUSE Linux on Intel: SAP Consulting by Texperts
This document contains an evaluation of a language teacher's certification dossier. It evaluates the teacher's ability to plan and evaluate lessons according to a curriculum, understand the institutional context, and prepare students for language examinations. The evaluation marks that the teacher provided evidence of stating objectives, defining lesson aims, and selecting appropriate activities. In remarks, the evaluator praises the teacher for using real situations to put lessons into practice. The original evaluation also positively assessed a series of integrated lessons on planning a meal that incorporated vocabulary from previous lessons and culminated in the students and teacher sharing a meal together.
The document discusses various considerations for planning and structuring a training course, including determining objectives, number of participants, venue requirements, and seating arrangements. It provides recommendations for each, describing advantages and disadvantages of different options. For example, it suggests limiting participants to 20 and assessing distractions at the venue. For seating, it analyzes formats like rows of chairs, a U-shape, banquet style, conference tables, and circles of chairs. The goal is to choose arrangements conducive to participation and that facilitate discussions, group work, and trainer movement in the room.
Skype marinair2011 Blog www.LRLiderTime.blogspot.ru
Приглашаем к сотрудничеству!
Крупная Немецкая компания прямых продаж LR HEALTH&BEAUTY SYSTEMS проводит набор менеджеров для рекламы компании и ее продукции для красоты и здоровья в России, Украине и Казахстане. Обучение проводится для менеджеров компании бесплатно. Критерии отбора: обучаемость, коммуникабельность, порядочность, активная жизненная позиция. Начинать работать у нас возможно от 18 лет, образование значения не имеет, пол тоже. Приветствуется опыт работы в компаниях прямых продаж, страховых компаниях, в сетевых компаниях, в торговле, бухгалтерии, административной должности. Сотрудники компании имеют возможность получить весь ассортимент товаров по закупочной цене. При выполнении условий компании по продажам продукции дальнейшее обучение в г.Москва, а также обучение за границей. Возможно сотрудничество с ИП и юридич.лицами. Телефон для связи 89136910033
Hackathon - Mapping da National Core a INSPIRE (Hydrography)smespire
webinar smeSpire "Hackathon Online - “Trasformazione di dataset spaziali open conformemente a INSPIRE” (2014-02-25).
Presentation about possible mapping between Italian topographic database specifications and INSPIRE (Hydrography).
Presented by Giuliana Ucelli (Informatica Trentina) with Daniela Ferrari (Provincia Autonoma Trento), Jody Marca and Piergiorgio Cipriano (Sinergis)
This paper discusses innovative tourism practices in India, including opportunities and challenges. It outlines several types of innovative tourism that have grown in India, such as medical tourism, spiritual tourism, and cultural tourism. Medical tourism involves traveling to India for affordable private medical care and treatments. Spiritual tourism is a major sector in India, with many traveling for religious purposes. Cultural tourism allows foreigners to experience India's diverse cultural and religious traditions through tours of festivals and rural/agricultural areas. However, the paper notes there is still room for improvement in innovative tourism in India.
Miracle Workers How Utilities Can Generate More Goodwill
Z-Pack Pfizer Can’t Assume that Science Will Trump a Scare Story
Livestrong Life After Lance is Possible—Telling the Small Stories Will Yield Big Results
The NYC Soda Ban Another Solution in Search of a Problem
LEVICK In the News
Blogs Worth Following
SIGN UP for LEVICK Insights
Este manual tiene como objetivo guiar la elaboración de estudios de prefactibilidad y factibilidad para proyectos de carreteras. Explica el ciclo de proyectos, la identificación del problema y las alternativas, la formulación del proyecto, el análisis beneficio-costo y criterios de rentabilidad, y la evaluación económica y financiera del proyecto. El manual fue desarrollado por un equipo de expertos nicaragüenses con el apoyo del gobierno de Dinamarca para normalizar los procesos de revisión de estud
Embracing INSPIRE in a legacy veterinary data management systemsmespire
The document discusses embracing INSPIRE standards in IZSVe's legacy veterinary data management system. IZSVe and 3DGIS are working together on the project. They are designing a new data model aligned with INSPIRE that can migrate IZSVe's legacy spatial data and support webGIS applications. This will improve data sharing and analysis within the veterinary community while making the data INSPIRE compliant. The new model structures the data better and allows different levels of detail.
Tugas ini membahas peranti keluaran (output device) yang meliputi monitor, printer, plotter, microfilm, dan audio. Beberapa poin penting yang dijelaskan adalah jenis-jenis monitor seperti CRT, LCD, resolusi dan ukuran monitor. Jenis-jenis printer seperti impact, thermal, inkjet, dan laser beserta prinsip kerjanya. Plotter digunakan untuk menghasilkan gambar berkualitas tinggi. Microfilm menyimpan banyak halaman dalam setiap lembarnya. Audio d
This document provides tips for scientists on how to spread their discoveries to the general public through journalists and media outlets. It advises focusing on practical consequences and everyday life impacts to attract journalists' interest. It also suggests using catchy opening lines and focusing on the intended audience when reaching out to general news publications versus scientific magazines. The document emphasizes making the message social through groups like "Dibattito scienza" on Facebook and considering both the effectiveness and ethics of experiments involving animals.
This document provides two ways to change the default program that opens a specific file type on Windows 7. The easiest way is to right click a file, select "Open with", and then choose the preferred program from the menu and select the option to always use that program. Alternatively, one can open the Default Programs menu from the Start button, select "Associate a file type or protocol with a program", choose the file type and preferred opening program, and click OK to configure the change.
This document discusses the food groups and items that a student from Ukraine eats on a daily, weekly, or monthly basis. It outlines fruits, grains, vegetables, meat/fish, dairy, and liquids that provide nutrients and are consumed daily or weekly. It also lists examples of junk food like fast food, soda, fried potatoes, alcohol, candies, and white bread that the student tries to avoid or limits to weekly consumption to maintain a healthy diet.
7 summer solstice2012-a cognitive heuristic model of epidemicsAle Cignetti
The document proposes a cognitive heuristic model for modeling epidemics that accounts for psychological and cognitive effects. It discusses limitations of traditional models and the need to consider adaptive cognitive strategies of agents. A tri-partite cognitive agent model is introduced containing modules for unconscious processes, reasoning, and learning. Finally, a recipe is outlined for an epidemics model incorporating a weighted network environment, viral features, economic factors, bounded agent cognition, and multiple timescales.
The document provides an overview of course requirements for a Business Strategy course. It includes details on assignments, exams, projects, and reading requirements. The key topics to be covered in the course include defining strategy, the components of strategic management, business-level strategy such as cost leadership and differentiation, and corporate-level strategy including diversification, acquisitions, and joint ventures. Students will complete a project on strategy formulation, implementation, and evaluation. The course aims to help students learn the essential concepts and frameworks for developing business strategies.
The document discusses two scientific discoveries. The first is that an enzyme called UvrD was found to reverse stalled transcription machinery in E. coli, allowing RNA polymerase to backtrack and expose problems in the DNA strand to facilitate repair without terminating transcription. The second discovery found that a genetic mutation in the DNA repair gene POLB in mice unexpectedly caused lupus-like symptoms, identifying a potential genetic cause of the autoimmune disease lupus in humans. Finding the causes of diseases like lupus could help develop new and less toxic treatments. Both discoveries provide insights that could improve understanding of diseases and lead to better prevention and treatment options.
Simulation and modeling introduction.pptxShamasRehman4
This document discusses simulation and modeling. It begins by introducing systems, modeling, and simulation. Modeling creates a representation of a system, while simulation operates a model to study the behavior of the actual system. There are different types of simulation models including deterministic/stochastic and static/dynamic models. The document outlines steps for building simulation models, including defining goals, involving end users, choosing tools, and validating results. General purpose languages, simulation languages, and special purpose packages are options for developing simulation models.
This document provides an introduction to modeling and simulation. It discusses the goals of modeling, different types of models, and an overview of the simulation process. The key steps in simulation include defining an achievable goal, ensuring appropriate skills and involvement from end users, choosing simulation tools, validating the model, and analyzing statistical output. Pitfalls to avoid include lack of clear objectives, inappropriate model detail, and failure to validate models or account for randomness.
The document presents a method called influence functions that can explain the predictions of black-box models. Influence functions trace a model's prediction back to its training data by calculating how the prediction would change if a particular training point was removed or modified. The method scales to large models using techniques like conjugate gradients to efficiently approximate influence. Influence functions can be used to debug models, detect errors in training data, and generate adversarial examples.
This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.it/.
http://www.ivanomalavolta.com
Chapters 4,5 and 6Into policymaking and modeling in a comple.docxtiffanyd4
The document provides information about modeling and simulation approaches to support policymaking. It discusses complexity in real-world systems and the limitations of simplistic models. It covers adaptive robust decision-making using systems modeling and compares microsimulation, agent-based, and other modeling approaches. Key topics include building models, incorporating uncertainty, and using models to design adaptive policies.
Chapters 4,5 and 6Into policymaking and modeling in a comple.docxmccormicknadine86
Chapters 4,5 and 6
Into policymaking and modeling in a complex world
From Building a model to adaptive robust decision- making using systems modelling
Features and added value of simulation Models using different modelling approaches supporting policymaking: A comparative analysis.
Chapter Goals and Objectives Overall – students will learn and understand
consequences of complexity in the real-world, and meaningful ways to understand and manage such situations
the implications of complexity and that many social systems are unpredictable by nature, especially when in the presence of structural change (transitions)
natural tendency to criticize the approaches that ignore difficulties and pretend to predict using simplistic models
that managing a complex system requires a good understanding of the dynamics of the system in question—to know, before they occur, some of the real possibilities that might occur and be ready so they can be reacted to as responsively as possible.
4. Policymaking and modeling in a complex world
the word “complexity” can be used to indicate a variety of kinds of difficulties
identification of complexity and uncertainty in policy-making
in very simple physical systems, interactions may give rise to complex behavior, expressed in different types of behavior, ranging from very stable to chaotic
reasons why complex adaptive systems have a strong capacity to self-organize
two of the ways systems are oversimplified: quantification and compartmentalization
models are assessed by their ability to predict/mirror observed aspects of the environments
5. From building a model to adaptive robust decision-making using systems modeling
System Dynamics Modeling and Simulation of Old
✓ methods for modeling and simulating dynamically complex systems
✓ evolutions in modeling and simulation with recent explosive growth in computational power, data, social media, to support decision-making
Recent Innovations and Expected Evolutions
✓ Why often seemingly more revolutionary—innovations have been introduced and demonstrated, but that they have not been massively adopted yet
Current and Expected Evolutions
✓ Three current evolutions expected to further reinforce - “experiential art” to “computational science.”
Future State of Practice of Systems Modeling and Simulation
✓ modeling and simulation with sparse data to modeling and simulation with (near real-time) big data;
✓ simulating and analyzing a few simulation runs to simulating and simultaneously analyzing well-selected ensembles of runs;
✓ using models for intuitive policy testing to using models as instruments for designing adaptive robust robust policies;
✓ developing educational flight simulators to fully integrated decision support.
Features and added value of simulation models using different modelling approaches to policy-making: A Comparative analysis
Foundations of Simulation Modelling
✓ model simplification definitions—smaller, less detailed, le ...
- The document provides an overview of the simulation and modelling process, which begins with defining a system and problem to address. This results in a project description.
- The project description is then refined into a conceptual model using formalisms like equations, diagrams, and code. This conceptual model captures the system's structure and behavior precisely.
- The conceptual model is then transformed into a simulation model - an executable computer program. This simulation model is augmented with additional code to support tasks like data collection, forming the final simulation program.
- Key steps in the process include defining the system and problem, developing a conceptual model, transforming this into a simulation model, and adding supporting code to create the simulation program used for experimentation
Modeling should be an independent scientific disciplineJordi Cabot
This document proposes that modeling should become an independent scientific discipline to better realize its full potential. Currently, modeling is seen primarily as a tool within software engineering, but it is applicable across many domains. An independent modeling discipline could bring together experts from different fields, develop a common body of knowledge and terminology, and help modeling gain more recognition and resources. Some initial steps suggested include making modeling tools more usable and accessible across domains, identifying economic benefits to promote adoption, and facilitating interdisciplinary publishing and education around modeling concepts and applications. The overarching goal is for modeling to serve all domains through a transdisciplinary approach.
This document provides instructions for a group project on designing an intelligent interface system. Students will work in groups of up to 5 people to identify a problem and design an innovative technology or system solution. They will illustrate their idea through interface design using prototyping tools and present their design. The project aims to stimulate creativity and problem solving. It covers tasks like conducting research, designing the interface, and disseminating the idea in a report. The document provides background on creativity, AI models, and expected results. It also includes the project format, submission instructions, assessment criteria and due date. Groups will be judged on criteria like how well their design achieves its mission and communicates. The best designs will receive higher marks.
This presentation is about a lecture I gave within the "Software systems and services" immigration course at the Gran Sasso Science Institute, L'Aquila (Italy): http://cs.gssi.infn.it/.
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CS251 Intro. to SE [Lec. 0 - Course Introduction & Plan] Spring 2022.pdfTitoMido1
This document provides an overview of an introductory software engineering course, including course details, instructor information, topics to be covered, learning objectives, logistics, and a tentative weekly plan. The instructor's name is Dr. Amr S. Ghoneim and he received his PhD from the University of New South Wales in Australia. Main topics include software processes, requirements engineering, design, implementation, testing, and additional selected topics. Assessment consists of a group project, midterm exam, and final exam. Students are expected to attend lectures, study independently, complete assignments, and follow academic integrity and classroom conduct policies.
This document discusses modeling and simulation. It defines a model as a representation of an object, system, or idea that is different from the actual entity. Models are used to test systems without creating real versions, predict future behavior, train users safely, and investigate systems in detail. The document outlines different types of modeling including physics-based, finite element, data-based, multi-scale, mathematical, and hybrid modeling. It also discusses conceptual modeling and creating block diagrams to represent systems as subsystems and connections. Criteria for separating systems into subsystems include anatomy, function, and measurability of inputs and outputs.
The document describes a course on software engineering. It includes the course objectives, which are to understand various phases of a software project like requirements engineering and analysis modeling. It also aims to teach object-oriented concepts, enterprise integration, deployment techniques, and testing and project management methods. The document lists the course outcomes and syllabus covering topics like software processes, requirements analysis, object-oriented concepts, software design, and testing and project management over 5 units. It also provides references and learning resources.
Computer simulations are computer programs that simulate abstract models of real systems. They present theoretical or simplified visualizations and interactive experiences. Simulations allow experiments to be conducted on a system to understand its behavior or evaluate strategies without implementing them in the real world. There are two main types of computer simulations - equation-based and agent-based. Simulations are increasingly being combined with other elements like humans or additional hardware to enhance realism, especially in training and entertainment. Simulations have advantages over real experiments in terms of safety, cost, independence of time and place, and ability to alter time dimensions. They are used for research, design, analysis, training, education, and entertainment.
Computer simulations are computer programs that simulate abstract models of real systems. They present theoretical or simplified visualizations and interactive experiences. Simulations allow experiments to be conducted on a system to understand its behavior or evaluate strategies without implementing them in the real world. There are two main types of computer simulations - equation-based and agent-based. Simulations are increasingly being combined with other elements like humans or additional hardware to provide more realistic training and entertainment experiences. Characteristics of computer simulations include being model-based, interactive, interface-driven, and scaffolded. They have advantages over real experiments in areas like safety, cost, independence of time and place, and allowing parameters to be altered. Simulations find uses in research, design,
Computer simulations are computer programs that simulate abstract models of real systems. They present theoretical or simplified visualizations and interactive experiences. Simulations allow experiments to be conducted on a system to understand its behavior or evaluate strategies without implementing them in the real world. There are two main types of computer simulations - equation-based and agent-based. Simulations are increasingly being combined with other elements like humans or additional hardware to enhance realism, especially in training and entertainment. Simulations have advantages over real experiments in terms of safety, cost, independence of time and place, and ability to alter time dimensions. They are used for research, design, analysis, training, education, and entertainment.
Computer simulations are computer programs that simulate abstract models of real systems. They present theoretical or simplified visualizations and interactive experiences. Simulations allow experiments to be conducted on a system to understand its behavior or evaluate strategies without implementing them in the real world. There are two main types of computer simulations - equation-based and agent-based. Simulations are increasingly being combined with other elements like humans or additional hardware to enhance realism, especially in training and entertainment. Simulations have advantages over real experiments in terms of safety, cost, independence of time and place, and ability to alter time dimensions. They are used for research, design, analysis, training, education, and entertainment.
Computer simulations are computer programs that simulate abstract models of real systems. They present theoretical or simplified visualizations and interactive experiences. Simulations allow experiments to be conducted on a system to understand its behavior or evaluate strategies without implementing them in the real world. There are two main types of computer simulations - equation-based and agent-based. Simulations are increasingly being combined with other elements like humans or additional hardware to enhance realism, especially in training and entertainment. Simulations have advantages over real experiments in terms of safety, cost, independence of time and place, and ability to alter time dimensions. They are used for research, design, analysis, training, education, and entertainment.
2. Goals Of This Course
Introduce Modeling
Introduce Simulation
Develop an Appreciation for the Need for
Simulation
Develop Facility in Simulation Model
Building
“Learn by Doing”--Lots of Case Studies
Introduction 2
3. What Is A Model ?
A Representation of an object, a
system, or an idea in some form
other than that of the entity itself.
(Shannon)
Introduction 3
4. Types of Models:
Physical
(Scale models, prototype plants,…)
Mathematical
(Analytical queueing models, linear
programs, simulation)
Introduction 4
5. What is Simulation?
A Simulation of a system is the operation of a
model, which is a representation of that system.
The model is amenable to manipulation which
would be impossible, too expensive, or too
impractical to perform on the system which it
portrays.
The operation of the model can be studied, and,
from this, properties concerning the behavior of
the actual system can be inferred.
Introduction 5
6. Applications:
Designing and analyzing manufacturing
systems
Evaluating H/W and S/W requirements for a
computer system
Evaluating a new military weapons system or
tactics
Determining ordering policies for an
inventory system
Designing communications systems and
message protocols for them
Introduction 6
7. Applications:(continued)
Designing and operating transportation
facilities such as freeways, airports,
subways, or ports
Evaluating designs for service organizations
such as hospitals, post offices, or fast-food
restaurants
Analyzing financial or economic systems
Introduction 7
8. Steps In Simulation and
Model Building
1. Define an achievable goal
2. Put together a complete mix of skills on the
team
3. Involve the end-user
4. Choose the appropriate simulation tools
5. Model the appropriate level(s) of detail
6. Start early to collect the necessary input
data
Introduction 8
9. Why Teach with Simulations?
1.Deep Learning
• Instructional simulations have the potential to engage
students in "deep learning" that empowers understanding
as opposed to "surface learning" that requires only
memorization.
• A good summary of how deep learning contrasts with
surface learning is given at the Engineering Subject Centre
10. Deep learning means student can learn scientific
methods including
• the importance of model building.
• Experiments and simulations are the way scientists do their
work.
• Using instructional simulations gives students concrete
formats of what it means to think like a scientist and do
scientific work.
• the relationships among variables in a model or models.
Simulation allows students to change parameter values and
see what happens.
• Students develop a feel for what variables are important
and the significance of magnitude changes in parameters.
11. • data issues, probability and sampling theory.
Simulations help students understand probability and
sampling theory.
• Instructional simulations have proven their worth many
times over in the statistics based fields.
• The ability to match simulation results with an analytically
derived conclusion is especially valuable in beginning
classes, where students often struggle with sampling
theory.
• Given the utility of data simulation, it is not surprising that
SERC has an existing module on
teaching with data simulation.
• how to use a model to predict outcomes.
• Simulations help students understand that scientific
knowledge rests on the foundation of testable hypotheses.
12. Learn to reflect on and extend knowledge
by:
• actively engaging in student-student or instructor-
student conversations needed to conduct a simulation.
Instructional simulations by their very nature cannot be
passive learning.
• Students are active participants in selecting parameter
values, anticipating outcomes, and formulating new
questions to ask.
• transferring knowledge to new problems and situations.
A well done simulation is constructed to include an
extension to a new problem or new set of parameters that
requires students to extend what they have learned in an
earlier context.
13. • understanding and refining their own thought
processes. A well done simulation includes a
strong reflection summary that requires students to
think about how and why they behaved as they did
during the simulation.
• seeing social processes and social interactions
in action. This is one of the most significant
outcomes of simulation in social science
disciplines such as sociology and political science.
14. How to Teach with Simulations?
Instructor Preparation is Crucial
• The good news is that instructional
simulations can be very effective in
stimulating student understanding.
• The bad news is that many simulations
require intensive pre-simulation lesson
preparation.
• Lesson preparation varies with the type and
complexity of the simulation
15. Active Student Participation is Crucial
• Students learn through instructional simulations when they
are actively engaged.
• Students should predict and explain the outcome they
expect the simulation to generate.
• Every effort should be made to make it difficult for
students to become passive during the simulation. Students
must submit timely input and not rely on classmates to
play for them.
• Instructors should anticipate ways the simulation can go
wrong and include this in their pre-simulation discussion
with the class.
16. Post-Simulation Discussion is Crucial
• Post-simulation discussion with students leads to deeper
learning. The instructor should:
• 1. Provide sufficient time for students to reflect on and
discuss what they learned from the simulation
• 2. Integrate the course goals into the post-simulation
discussion
• 3. Ask students explicitly asked how the simulation helped
them understand the course goals or how it may have made
the goals more confusing.
Extremely significant or important=crucial
17. Steps In Simulation and
Model Building(cont’d)
7. Provide adequate and on-going
documentation
8. Develop a plan for adequate model
verification
(Did we get the “right answers ?”)
9. Develop a plan for model validation
(Did we ask the “right questions ?”)
10. Develop a plan for statistical output
analysis
Introduction 17
18. Define An Achievable Goal
“To model the…” is NOT a goal!
“To model the…in order to
select/determine feasibility/…is a goal.
Goal selection is not cast in concrete
Goals change with increasing insight
Introduction 18
19. Put together a complete
mix of skills on the team
We Need:
-Knowledge of the system under investigation
-System analyst skills (model formulation)
-Model building skills (model Programming)
-Data collection skills
-Statistical skills (input data representation)
Introduction 19
20. Put together a complete
mix of skills on the team(continued)
We Need:
-More statistical skills (output data analysis)
-Even more statistical skills (design of
experiments)
-Management skills (to get everyone pulling in
the same direction)
Introduction 20
21. INVOLVE THE END USER
-Modeling is a selling job!
-Does anyone believe the results?
-Will anyone put the results into action?
-The End-user (your customer) can (and must)
do all of the above BUT, first he must be
convinced!
-He must believe it is HIS Model!
Introduction 21
22. Choose The Appropriate
Simulation Tools
Assuming Simulation is the appropriate
means, three alternatives exist:
1. Build Model in a General Purpose
Language
2. Build Model in a General Simulation
Language
3. Use a Special Purpose Simulation
Package
Introduction 22
23. MODELLING W/ GENERAL
PURPOSE LANGUAGES
Advantages:
– Little or no additional software cost
– Universally available (portable)
– No additional training (Everybody knows…(language X) ! )
Disadvantages:
– Every model starts from scratch
– Very little reusable code
– Long development cycle for each model
– Difficult verification phase
Introduction 23
24. GEN. PURPOSE LANGUAGES
USED FOR SIMULATION
FORTRAN
– Probably more models than any other language.
PASCAL
– Not as universal as FORTRAN
MODULA
– Many improvements over PASCAL
ADA
– Department of Defense attempt at standardization
C, C++
– Object-oriented programming language
Introduction 24
25. MODELING W/ GENERAL
SIMULATION LANGUAGES
Advantages:
– Standardized features often needed in modeling
– Shorter development cycle for each model
– Much assistance in model verification
– Very readable code
Disadvantages:
– Higher software cost (up-front)
– Additional training required
– Limited portability
Introduction 25
26. GENERAL PURPOSE
SIMULATION LANGUAGES
GPSS
– Block-structured Language
– Interpretive Execution
– FORTRAN-based (Help blocks)
– World-view: Transactions/Facilities
SIMSCRIPT II.5
– English-like Problem Description Language
– Compiled Programs
– Complete language (no other underlying language)
– World-view: Processes/ Resources/ Continuous
Introduction 26
27. GEN. PURPOSE SIMULATION
LANGUAGES (continued)
MODSIM III
– Modern Object-Oriented Language
– Modularity Compiled Programs
– Based on Modula2 (but compiles into C)
– World-view: Processes
SIMULA
– ALGOL-based Problem Description Language
– Compiled Programs
– World-view: Processes
Introduction 27
28. GEN. PURPOSE SIMULATION
LANGUAGES (continued)
SLAM
– Block-structured Language
– Interpretive Execution
– FORTRAN-based (and extended)
– World-view: Network / event / continuous
CSIM
– process-oriented language
– C-based (C++ based)
– World-view: Processes
Introduction 28
29. MODELING W/ SPECIAL-
PURPOSE SIMUL. PACKAGES
Advantages
– Very quick development of complex models
– Short learning cycle
– No programming--minimal errors in usage
Disadvantages
– High cost of software
– Limited scope of applicability
– Limited flexibility (may not fit your specific
application)
Introduction 29
30. SPECIAL PURPOSE
PACKAGES USED FOR SIMUL.
NETWORK II.5
– Simulator for computer systems
OPNET
– Simulator for communication networks, including
wireless networks
COMNET III
– Simulator for communications networks
SIMFACTORY
– Simulator for manufacturing operations
Introduction 30
31. THE REAL COST OF
SIMULATION
Many people think of the cost of a simulation
only in terms of the software package price.
There are actually at least three components to
the cost of simulation:
1. Purchase price of the software
2. Programmer / Analyst time
3. “Timeliness of Results”
Introduction 31
32. TERMINOLOGY
System
– A group of objects that are joined together in
some regular interaction or interdependence
toward the accomplishment of some purpose.
– Entity
– An object of interest in the system.
– E.g., customers at a bank
Introduction 32
33. TERMINOLOGY (continued)
Attribute
– a property of an entity
– E.g., checking account balance
Activity
– Represents a time period of specified length.
– Collection of operations that transform the state
of an entity
– E.g., making bank deposits
Introduction 33
34. TERMINOLOGY (continued)
Event:
– change in the system state.
– E.g., arrival; beginning of a new execution;
departure
State Variables
– Define the state of the system
– Can restart simulation from state variables
– E.g., length of the job queue.
Introduction 34
35. TERMINOLOGY (continued)
Process
– Sequence of events ordered on time
Note:
– the three concepts(event, process,and activity)
give rise to three alternative ways of building
discrete simulation models
Introduction 35
36. A GRAPHIC COMPARISON OF
DISCRETE SIMUL. METHODOLOGIES
A1 A2
P1
E1 E2 /E3 E4
A1 A2
P2
E1’ E2’ E3’ E4’
Simulation Time
Introduction 36
37. EXAMPLES OF SYSTEMS
AND COMPONENTS
System Entities Attributes Activities Events State
Variables
Banking Customers Checking Making Arrival; # of busy
account deposits Departure tellers; # of
balance customers
waiting
Note: State Variables may change continuously (continuous sys.)
over time or they may change only at a discrete set of points
(discrete sys.) in time.
Introduction 37
39. Examples Of Both Type Models
Continuous Time and Discrete Time
Models:
CPU scheduling model vs. number of
students attending the class.
Introduction 39
40. Examples (continued)
Continuous State and Discrete State
Models:
Example: Time spent by students in a
weekly class vs. Number of jobs in Q.
Introduction 40
41. Other Type Models
Deterministic and Probabilistic Models:
Output
Output
Input Input
Static and Dynamic Models:
CPU scheduling model vs. E = mc2
Introduction 41
42. Stochastic vs. Deterministic
System Model
1
Deterministic Deterministic
3
2
Stochastic Stochastic
4
Introduction 42
43. MODEL THE APPROPRIATE
LEVEL(S) OF DETAIL
Define the boundaries of the system to be
modeled.
Some characteristics of “the environment”
(outside the boundaries) may need to be
included in the model.
Not all subsystems will require the same
level of detail.
Control the tendency to model in great detail
those elements of the system which are well
understood, while skimming over other, less
well - understood sections.
Introduction 43
44. START EARLY TO COLLECT
THE NECESSARY INPUT DATA
Data comes in two quantities:
TOO MUCH!!
TOO LITTLE!!
With too much data, we need techniques for
reducing it to a form usable in our model.
With too little data, we need information
which can be represented by statistical
distributions.
Introduction 44
45. PROVIDE ADEQUATE AND
ON-GOING DOCUMENTATION
In general, programmers hate to document.
(They love to program!)
Documentation is always their lowest priority
item. (Usually scheduled for just after the
budget runs out!)
They believe that “only wimps read manuals.”
What can we do?
– Use self-documenting languages
– Insist on built-in user instructions(help screens)
– Set (or insist on) standards for coding style
Introduction 45
46. DEVELOP PLAN FOR ADEQUATE
MODEL VERIFICATION
Did we get the “right answers?”
(No such thing!!)
Simulation provides something that no other
technique does:
Step by step tracing of the model execution.
This provides a very natural way of checking
the internal consistency of the model.
Introduction 46
47. DEVELOP A PLAN FOR
MODEL VALIDATION
VALIDATION: “Doing the right thing”
Or “Asking the right questions”
How do we know our model represents the
system under investigation?
– Compare to existing system?
– Deterministic Case?
Introduction 47
48. DEVELOP A PLAN FOR
STATISTICAL OUTPUT ANALYSIS
How much is enough?
Long runs versus Replications
Techniques for Analysis
Introduction 48