Genetic algorithms "Green Buildings"
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This document discusses green buildings and how genetic algorithms can be used for construction optimization. It defines green buildings as structures that are environmentally responsible throughout their lifecycle. It also notes that the construction industry accounts for a significant portion of greenhouse gas emissions. The document then discusses genetic algorithms, noting they are a type of evolutionary algorithm that can be used to find near-optimal solutions to complex problems. It outlines the five phases of a genetic algorithm: initial population, fitness function, selection, crossover, and mutation. Finally, it provides steps for how genetic algorithms could be applied to optimize construction materials, crew, equipment, and schedule to minimize time, cost and environmental impact.
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In this paper, a study was carried out to aid in
adequate allocation of resources in the College of Natural
Sciences, TYZ University (not real name because of ethical
issue). Questionnaires were administered to the highranking officials of one the Colleges, College of Pure and
Applied Sciences, to examine how resources were allocated
for three consecutive sessions(the sessions were 2009/2010,
2010/2011 and 2011/2012),then used the data gathered and
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outputs (variables)formed for the purpose of the study.
These variables are: 1
x
represents the quality of graduates
produced;
2
x
stands for research papers, Seminars,
Journals articles etc. published by faculties and
3
x
denotes service delivery within the three sessions under study.
Simplex Method of Linear Programming was used to solve
the model formulated.
Similar to Genetic algorithms "Green Buildings" (20)
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The popularity of functional foods among scientists and common people has been increasing day by day. Awareness and modernization make the consumer think better regarding food and nutrition. Now a day’s individual knows very well about the relation between food consumption and disease prevalence. Humans have a diversity of microbes in the gut that together form the gut microflora. Probiotics are the health-promoting live microbial cells improve host health through gut and brain connection and fighting against harmful bacteria. Bifidobacterium and Lactobacillus are the two bacterial genera which are considered to be probiotic. These good bacteria are facing challenges of viability. There are so many factors such as sensitivity to heat, pH, acidity, osmotic effect, mechanical shear, chemical components, freezing and storage time as well which affects the viability of probiotics in the dairy food matrix as well as in the gut. Multiple efforts have been done in the past and ongoing in present for these beneficial microbial population stability until their destination in the gut. One of a useful technique known as microencapsulation makes the probiotic effective in the diversified conditions and maintain these microbe’s community to the optimum level for achieving targeted benefits. Dairy products are found to be an ideal vehicle for probiotic incorporation. It has been seen that the encapsulated microbial cells show higher viability than the free cells in different processing and storage conditions as well as against bile salts in the gut. They make the food functional when incorporated, without affecting the product sensory characteristics.
一比一原版(UMTC毕业证书)明尼苏达大学双城分校毕业证如何办理
原件一模一样【微信：6496090】【(UMTC毕业证书)明尼苏达大学双城分校毕业证成绩单学位证】【微信：6496090】（留信学历认证永久存档查询）采用学校原版纸张、特殊工艺完全按照原版一比一制作（包括：隐形水印，阴影底纹，钢印LOGO烫金烫银，LOGO烫金烫银复合重叠，文字图案浮雕，激光镭射，紫外荧光，温感，复印防伪）行业标杆！精益求精，诚心合作，真诚制作！多年品质 ,按需精细制作，24小时接单,全套进口原装设备，十五年致力于帮助留学生解决难题，业务范围有加拿大、英国、澳洲、韩国、美国、新加坡，新西兰等学历材料，包您满意。
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对于老客户或者被老客户介绍过来的朋友，我们都会适当给一些优惠。
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Genetic algorithms "Green Buildings"
- 1. Green Buildings Genetic Algorithms Esraa Hussein 14104622 Ayman Mohamed 14105247
- 2. Green Buildings refers to both a structure and the application of processes that are environmentally responsible and resource- efficient throughout a building's life-cycle: from planning to design, construction, operation, maintenance, renovation, and demolition.
- 3. – EPA 2009 “The construction industry generated approximately 1.7% of total greenhouse gas emissions (GHG) in the United States, which is equivalent to 6% of total industry-related GHG emissions in the country and puts the construction industry at the third place among key industrial sectors. ”
- 4. Construction & Environment • Project objectives: • Time • cost • Quality • Scope Environment
- 5. Algoritms Types • Heuristic method • Mathematical Programming • Evolutionary algorithms (Genetic algorithms)
- 6. Genetic Algorithm • Genetic Algorithm has been used extensively "as a powerful tool to solve various optimization problems such as integer nonlinear problems (INLP). “GA" is one of the meta-heuristics that has been frequently utilized to find near-optimum solutions of many combinational problems.
- 8. Five phases are considered in a genetic algorithm: 1. Initial population 2. Fitness function 3. Selection 4. Crossover 5. Mutation
- 10. One chromosome represents one solution
- 11. 2. Fitness Function The fitness function determines how fit an individual is (the ability of an individual to compete with other individuals). It gives a fitness score to each individual. The probability that an individual will be selected for reproduction is based on its fitness score.
- 12. 3. Selection
- 13. 4. Crossover
- 15. 4. Mutation
- 19. Steps of calculations 1. Defining construction materials, crew, and equipment alternatives associated with each activity. 2. Determining project schedule, cost, and GWP for each solution of the project. 3. Performing analysis.
- 24. • By this way, the relative effect of a change in each factor can be observed on the project objective. The change in factors and the project objective are plotted, and the linear best-fit is drawn for each factor. The factor having the highest slope of the best-fit line is regarded as the most sensitive parameter for this project.
- 25. References • Time, Cost, and Environmental Impact Analysis on Construction Operation Optimization Using Genetic Algorithms Gulbin Ozcan-Deniz, M.ASCE1; Yimin Zhu, M.ASCE2; and Victor Ceron3
- 26. Thank You