GENIES is a decision support system for climate change adaptation that uses a system dynamics approach. It provides an open framework platform where users can build modular system dynamic models by linking existing model components and applications. GENIES helps users visualize complex systems, predict outcomes, and identify problems by simulating processes. It provides tools for risk assessment, cost-benefit analysis, and climate change uncertainty analysis to support decision-making for climate change adaptation. GENIES is being developed as a collaborative community of practice between research institutions, organizations, practitioners, and other stakeholders.
An overview of "resilience thinking" for participants at a meeting on resilience in the electricity space organized by the Electric Power Research Institute (EPRI).
An overview of "resilience thinking" for participants at a meeting on resilience in the electricity space organized by the Electric Power Research Institute (EPRI).
Exploring the Science of Complexity in Aid Policy and PracticeODI_Webmaster
A presentation given by Ben Ramalingam of the ODI on applying the concept of complexity to aid policy and practice. Part of an all-day seminar of the same name. See http://www.odi.org.uk/RAPID/events/Complexity for more information.
Summarization of Environmental Impact Assessment Methodology by Dr. I.M. Mis...Arvind Kumar
Summarization of Environmental Impact
Assessment Methodology by Dr. I.M. Mishra
Professor, Dept. of Chemical Engineering
Dean, Saharanpur Campus
Indian Institute of Technology, Roorkee
This chapter describes some of the simplest techniques and methods for EIA, and gives information to
help choose the most appropriate method for a given situation.
Operationalizing Safety II Using Participatory Action ResearchSpringboard Labs
How do you make a breakthrough in chronic workplace injuries across the silviculture sector in British Columbia? This presentation presents the results of a participatory action research conducted in 2102 that used a resilient systems approach to discover the system of factors affecting worker injuries for Worksafe British Columbia.
Environmental impact assessment methodology by Dr. I.M. Mishra Professor, Dep...Arvind Kumar
Environmental impact assessment methodology by Dr. I.M. Mishra Professor, Dept. of Chemical Engineering Dean, Saharanpur Campus Indian Institute of Technology, Roorkee
Systems Thinking in Public Health for Continuous Quality ImprovementCameron Norman
Opening presentation at the first meeting on CQI in Public Health in Ontario, held at the Dalla Lana School of Public Health at the University of Toronto. Practitioners from across the province gathered to learn more about quality assurance measures, metrics, theories and ideas. This presentation provides a simple overview of systems thinking as it might apply to CQI in public health. This simple overview looks at the nature of systems, how they apply to CQI, how design thinking and developmental design can aid public health in creating relevant, appropriate means of quality assessment in its work.
Managing in the presence of uncertaintyGlen Alleman
Uncertainty is the source of risk. Uncertainty comes in two types, aleatory and epistemic. It is important to understand both and deal with both in distinct ways, in order to produce a credible risk handling strategy.
Environmental Impact Assessment (EIA) in Project ManagementJoy Bhattacharjee
Environmental Impact Assessment is a systematic process by which we can identify what will be the future consequences of a projected or recent actions.
Exploring the Science of Complexity in Aid Policy and PracticeODI_Webmaster
A presentation given by Ben Ramalingam of the ODI on applying the concept of complexity to aid policy and practice. Part of an all-day seminar of the same name. See http://www.odi.org.uk/RAPID/events/Complexity for more information.
Summarization of Environmental Impact Assessment Methodology by Dr. I.M. Mis...Arvind Kumar
Summarization of Environmental Impact
Assessment Methodology by Dr. I.M. Mishra
Professor, Dept. of Chemical Engineering
Dean, Saharanpur Campus
Indian Institute of Technology, Roorkee
This chapter describes some of the simplest techniques and methods for EIA, and gives information to
help choose the most appropriate method for a given situation.
Operationalizing Safety II Using Participatory Action ResearchSpringboard Labs
How do you make a breakthrough in chronic workplace injuries across the silviculture sector in British Columbia? This presentation presents the results of a participatory action research conducted in 2102 that used a resilient systems approach to discover the system of factors affecting worker injuries for Worksafe British Columbia.
Environmental impact assessment methodology by Dr. I.M. Mishra Professor, Dep...Arvind Kumar
Environmental impact assessment methodology by Dr. I.M. Mishra Professor, Dept. of Chemical Engineering Dean, Saharanpur Campus Indian Institute of Technology, Roorkee
Systems Thinking in Public Health for Continuous Quality ImprovementCameron Norman
Opening presentation at the first meeting on CQI in Public Health in Ontario, held at the Dalla Lana School of Public Health at the University of Toronto. Practitioners from across the province gathered to learn more about quality assurance measures, metrics, theories and ideas. This presentation provides a simple overview of systems thinking as it might apply to CQI in public health. This simple overview looks at the nature of systems, how they apply to CQI, how design thinking and developmental design can aid public health in creating relevant, appropriate means of quality assessment in its work.
Managing in the presence of uncertaintyGlen Alleman
Uncertainty is the source of risk. Uncertainty comes in two types, aleatory and epistemic. It is important to understand both and deal with both in distinct ways, in order to produce a credible risk handling strategy.
Environmental Impact Assessment (EIA) in Project ManagementJoy Bhattacharjee
Environmental Impact Assessment is a systematic process by which we can identify what will be the future consequences of a projected or recent actions.
The series of presentations contains the information about "Management Information System" subject of SEIT for University of Pune.
Subject Teacher: Tushar B Kute (Sandip Institute of Technology and Research Centre, Nashik)
http://www.tusharkute.com
Sharda_dss11_im_01.docChapter 1An Overview of Analy.docxklinda1
Sharda_dss11_im_01.doc
Chapter 1:
An Overview of Analytics, and AI
Learning Objectives for Chapter 1
· Understand the need for computerized support of managerial decision making
· Understand the development of systems for providing decision-making support
· Recognize the evolution of such computerized support to the current state of analytics/data science and artificial intelligence
· Describe the business intelligence (BI) methodology and concepts
· Understand the different types of analytics and review selected applications
· Understand the basic concepts of artificial intelligence (AI) and see selected applications
· Understand the analytics ecosystem to identify various key players and career opportunities
CHAPTER OVERVIEW
The business environment (climate) is constantly changing, and it is becoming more and more complex. Organizations, both private and public, are under pressures that force them to respond quickly to changing conditions and to be innovative in the way they operate. Such activities require organizations to be agile and to make frequent and quick strategic, tactical, and operational decisions, some of which are very complex. Making such decisions may require considerable amounts of relevant data, information, and knowledge. Processing these in the framework of the needed decisions must be done quickly, frequently in real time, and usually requires some computerized support. As technologies are evolving, many decisions are being automated, leading to a major impact on knowledge work and workers in many ways. This book is about using business analytics and artificial intelligence (AI) as a computerized support portfolio for managerial decision making. It concentrates on the theoretical and conceptual foundations of decision support as well as on the commercial tools and techniques that are available. The book presents the fundamentals of the techniques and the manner in which these systems are constructed and used. We follow an EEE (exposure, experience, and exploration) approach to introducing these topics. The book primarily provides exposure to various analytics/AI techniques and their applications. The idea is that students will be inspired to learn from how various organizations have employed these technologies to make decisions or to gain a competitive edge. We believe that such exposure to what is being accomplished with analytics and that how it can be achieved is the key component of learning about analytics. In describing the techniques, we also give examples of specific software tools that can be used for developing such applications. However, the book is not limited to any one software tool, so students can experience these techniques using any number of available software tools. We hope that this exposure and experience enable and motivate readers to explore the potential of these techniques in their own domain. To facilitate such exploration, we include exercises that direct the reader to Teradata.
Sharda_dss11_im_01.docChapter 1An Overview of Analy.docxlesleyryder69361
Sharda_dss11_im_01.doc
Chapter 1:
An Overview of Analytics, and AI
Learning Objectives for Chapter 1
· Understand the need for computerized support of managerial decision making
· Understand the development of systems for providing decision-making support
· Recognize the evolution of such computerized support to the current state of analytics/data science and artificial intelligence
· Describe the business intelligence (BI) methodology and concepts
· Understand the different types of analytics and review selected applications
· Understand the basic concepts of artificial intelligence (AI) and see selected applications
· Understand the analytics ecosystem to identify various key players and career opportunities
CHAPTER OVERVIEW
The business environment (climate) is constantly changing, and it is becoming more and more complex. Organizations, both private and public, are under pressures that force them to respond quickly to changing conditions and to be innovative in the way they operate. Such activities require organizations to be agile and to make frequent and quick strategic, tactical, and operational decisions, some of which are very complex. Making such decisions may require considerable amounts of relevant data, information, and knowledge. Processing these in the framework of the needed decisions must be done quickly, frequently in real time, and usually requires some computerized support. As technologies are evolving, many decisions are being automated, leading to a major impact on knowledge work and workers in many ways. This book is about using business analytics and artificial intelligence (AI) as a computerized support portfolio for managerial decision making. It concentrates on the theoretical and conceptual foundations of decision support as well as on the commercial tools and techniques that are available. The book presents the fundamentals of the techniques and the manner in which these systems are constructed and used. We follow an EEE (exposure, experience, and exploration) approach to introducing these topics. The book primarily provides exposure to various analytics/AI techniques and their applications. The idea is that students will be inspired to learn from how various organizations have employed these technologies to make decisions or to gain a competitive edge. We believe that such exposure to what is being accomplished with analytics and that how it can be achieved is the key component of learning about analytics. In describing the techniques, we also give examples of specific software tools that can be used for developing such applications. However, the book is not limited to any one software tool, so students can experience these techniques using any number of available software tools. We hope that this exposure and experience enable and motivate readers to explore the potential of these techniques in their own domain. To facilitate such exploration, we include exercises that direct the reader to Teradata.
Decision support systems, group decision support systems,expert systems-manag...clincy cleetus
concept of decision making,decision making process-intelligence phase-design phase-choice phase,types of decisions,meaning and definition of decision support systems(dss),evolution of dss,characteristics of dss,decision support and repetitiveness of decisions,objectives and importance of dss,classification of dss,components of dss,functions of dss,development of dss,support for different phases of decision making,benefits and risk of dss,group decision support systems, gdss software, gdss benefits and risks,expert systems,difference between dss and es, comparison between dss and es
Systems Thinking Tools for Climate Resilience Programming Workshop - Nov 2015Eric Momanyi
Policy House is pleased to present a workshop on Systems Thinking Tools for Climate Resilience Programming. This workshop will equip researchers, senior climate change program staff, climate negotiators, government officials, policy analysts and researchers with the skills to study climate resilience and design effective climate mitigation, adaptation, resilience and green growth.
3. Climate change adaptation
Adjustment in natural or human systems in response to
actual or expected climatic stimuli or their effects, which
moderates harm or exploits beneficial opportunities (IPCC,
2007).
Adaptation involves changes in social-ecological systems in
response to actual and expected impacts of climate change in
the context of interacting non-climatic changes. Adaptation
strategies and actions can range from short-term coping to
longer-term, deeper transformations, aim to meet more than
climate change goals alone, and may or may not succeed in
moderating harm or exploiting beneficial opportunities (Moser
and Ekstrom, 2010).
4. Decision making is often perceived
and practiced as a linear activity
following simple steps of
• problem
• research
• Information
• decision
• implementation.
Decision-making for climate change adaptation
5. Despite the large amounts of time, effort and money
invested into developing (S)DSSs, many of them have
not been utilised in practice (Wenkel et al., 2013).
The possible causes are:
• Inadequately tailored to users’ needs
• Insufficiently related to the specific problem at hand
• Too complicated and rarely interactive, and lack of
transparency
• Lack of suitable data impedes the use and transfer of
existing decision support tools.
(Spatial) Decision Support Systems
in Reality
6. Climate change adaptation falls squarely in
the category of wicked problems.
The notion of ‘wicked’ problem
“A class of social problems which are ill-formulated, where the
information is confusing, where there are many clients and
decision makers with conflicting values, and where the
ramifications in the whole system are thoroughly confusing”.
Complex (Wicked) Problems
7. Challenges for climate change adaptation
• Tightly Coupled
“Everything influences everything else”
“You can’t just do one thing”
• Dynamic
Change occurs at many spatial and time scales
• Policy Resistant
Many obvious solutions to problems fail or actually worsen the
situation.
• Counterintuitive
Cause and effect are distant in time and space
• Exhibit Tradeoffs
Long term behavior is often different from short term behavior
8. New challenge and new solution
Decision making for climate change adaptation
is a complex and dynamic process.
From both scientific and social view points,
these challenges require collective learning and
new modes of decision making and
collaboration.
Perhaps, systems thinking/system dynamics is a
potential solution.
9. Systems Thinking & System Dynamics
Systems Thinking (ST) is a scientific tool and language for
understanding complexity and creating consensus within multi-
actor decision environments. Systems thinking can help integrate
social, economic and environmental factors which can help
decision makers to understand all implications of their decisions
and make trade-offs.
System dynamics (SD) is a perspective and set of conceptual tools
that enable us to understand the structure and dynamics of
complex systems. System dynamics is also a rigorous modelling
method that enables us to build formal computer simulations of
complex systems and use them to design more effective policies
and organizations.
15. The behavior of a system
cannot be known just by
knowing the elements of
which the system is made.
The blind men & the elephant
Moral of the Story
People tend to understand
only a tiny portion of Reality
and then extrapolate all
manner of dogmas from that,
each claiming only his one is
the correct version
16. Systems Thinking & System Dynamics
- see the world
From:
reductionist, narrow, short-run, static view
To:
a holistic, broad, long-term, dynamic view.
17. Steps in the System Dynamics World
1. Identify a problem,
2. Develop a dynamic hypothesis explaining the
cause of the problem,
3. Build a computer simulation model of the system
at the root of the problem,
4. Test the model to be certain that it reproduces the
behaviour seen in the real world,
5. Devise and test in the model alternative policies
that alleviate the problem,
6. Implement the solution.
Often these steps have to be reviewed and refined going back to an earlier step. For
instance, the first problem identified may be only a symptom of a still greater problem.
19. SimCLIM(exists) and GENIES (evolving)
Climate
change and
sea level
scenarios
Generic
impact
models/tools
Risk
assessment
Specific
impact tools
build by end
users
Adaptation
social
economic
analysis
Climate change
data library
Enabling
Decision
making
support
Direct User
involvement
Focusing on
urban area
planning
20. Criteria
for decision support systems in climate change science and adaptation
Development Science Application
• Related to specific
problems to be
solved
• Oriented to the
demands of
users/stakeholders
• Involvement of users
from the very
beginning
• Close cooperation
between scientists,
developers of
climate projections,
software developers
and users
• Adapted model
theory
• High quality of input
data
• Coupled models
from different
backgrounds
• Reliability of model
output
• Assessment of
uncertainty
• Scenario building
• Flexibility
• Interactive use
• Communication of
state-of-the-art
knowledge
• Communication of
the system’s
limitations and
uncertainties
• User friendliness of
the system
• Clear visualization of
results
• Reliability and legal
aspects
http://circle-era.eu
22. GENIES - Model/Block library
Each block in the library can be dragged into the
canvas to be configured and used as a
component of a model. The blocks can be linked
to each other according to their data and
function nature.
The blocks are classified according their
functions. More blocks and categories will be
added with the progress of GENIES.
23. GENIES - Coral reef concept model
- example for Systems Thinking
25. Summary: GENIES Functions
GENIES is an easy-to-use, yet extremely powerful, tool for simulating
processes. It helps you understand complex systems and produce better
results faster. With GENIES you can:
• Predict the course and results of certain actions
• Gain insight and stimulate creative thinking
• Visualize your processes logically or in a virtual environment
• Identify problem areas before implementation
• Explore the potential effects of modifications
• Confirm that all variables are known
• Optimize your operations
• Evaluate ideas and identify inefficiencies
• Understand why observed events occur
• Communicate the integrity and feasibility of your plans
26. Summary : GENIES Features
•Modular design
build on and link to existing models and related applications
•Open framework
allowing for multi-scale, multi-disciplinary impact assessment
easily can be customized case-by-case to suit each city
•Climate change adaptation oriented
Integrated analysis of adaptation and mitigation options
Climate change uncertainty analysis
•Multiple toolboxes
risk and cost-benefit analysis tools
scripting
AHP and Decision tree
•Visualization
spatial
temporal
spatio-temporal
27. GENIES Community of Practice
Get together
Workshops
visiting
Remote
communication
Stay
together
Presentations
Discussion
Common
interests
identification
Work
together
Work plan
SCI. & Tech.
collaboration
Build up the
community
Knowledge and
tool sharing
Contributions
Synergy
Initiatives
Membership
Climate change
Good practice
28. Progress on GENIES Community of
Practice (existing members)
• Research institutes and universities
- IAP, CAS, Yonsei, Ji’nan, Delhi, Nanjing, Waikato
• International Climate Change Organizations
- MAIRS, CORDEX, CMIP, OCMIP, ALM
• Planning institute
- Guangzhou, Beijing, New Zealand, Australia, Vietnam, Philippines
• Practioners
- AECOM, ARUP, CH2MHILL, ESRI …
• IFIs
-ADB, WB…