Download or read book Performance of Constraint handling Techniques Applied to a Genetic Algorithm based Watershed Management Model written by Kwisun Park Yu and published by . This book was released on 2004 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Integrated Watershed Management Using a Genetic Algorithm based Approach written by Can Ali Kuterdem and published by . This book was released on 2001 with total page 25 pages. Available in PDF, EPUB and Kindle. Book excerpt: Keywords: watershed management, water quality, TMDL, decision support system, BASINS, HSPF, genetic algorithms, optimization.

Download or read book Integrated Watershed Management Using a Genetic Algorithm Based Approach written by and published by . This book was released on 2001 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Watershed management requires consideration of a multitude of factors affecting water quality at the watershed-scale while integrating point and non-point sources of pollution and control. While the existing water quality modeling systems and associated quantitative tools can assist in some aspects of Total Maximum Daily Load (TMDL) development for a watershed, their abilities to assist in determining efficient management strategies are limited. Typically, the best a user can do is employ these tools manually to explore the solution space via a trial-and-error process, which is inefficient for finding management strategies that consider water quality as well as a multitude of other design issues simultaneously. Recent implementation of the STAR (STrategy, Analysis, and Reporting) system incorporates a set of systems analytic tools to assist decisions-makers explore and identify alternative management strategies. The main engine of the STAR system is a genetic algorithm-based optimization technique, which is coupled with additional tools such as an uncertainty propagation tool, a solution reporting system, and an incremental strategy development system to form a decision support framework. This paper describes some of the capabilities of this framework through several illustrative scenarios for the Yellow River watershed in Gwinnett County, Georgia, which conducted a comprehensive, countywide TMDL investigation to assess the current water quality conditions. The STAR system's capabilities are employed to identify ways to achieve minimum total phosphorous (TP) levels via point and nonpoint source controls, as well as characterize the implications of future urban development on TP levels. Noninferior tradeoffs between urban development and TP levels at different degrees of point source controls are generated. The range of uses of the STAR system in considering the integrated effect of point and non-point sources in watershed management is demonstrated throughout these.

Download or read book Genetic Algorithm based Model for Determination of Efficient Management Strategies for Irrigation Canal Networks written by Talaat Taher El Gamel and published by . This book was released on 2004 with total page 189 pages. Available in PDF, EPUB and Kindle. Book excerpt: " An optimization model for the determination of efficient management strategies for an irrigation canal network is developed. The objective is to minimize the total water consumed while satisfying various system constraints. An unsteady flow model is used to simulate the flow in the network. A genetic algorithm-(GA-) based framework is used to solve the model. The sutiable GA parameters that should be used within the model, as well as the performance of various constraint-handling techniques, are studied. Uncertainties in crop pattern and water consumption rates are incorporated into the search procedure to identify more reliable solutions. A graphical interface is also developed to make the model more user-friendly"--Abstract.

Download or read book Water Management Challenges in Global Change written by B. Ulanicki and published by CRC Press. This book was released on 2020-11-26 with total page 712 pages. Available in PDF, EPUB and Kindle. Book excerpt: Water Management Challenges in Global Change contains the proceedings of the 9th Computing and Control for the Water Industry (CCWI2007) and the Sustainable Urban Water Management (SUWM2007) conferences. The rationale behind these conferences is to improve the management of urban water systems through the development of computerbased methods. Issues such as economic globalisation, climate changes and water shortages call for a new approach to water systems management, which addresses the relevant technical, social and economic aspects. This collection represents the views of academic and industrial experts from a number of countries, who provide technical solutions to current water management problems and present a vision for addressing the global questions. The themes underlying many of the contributions include energy and material savings, water savings and the integration of different aspects of water management. The papers are grouped into three themes covering water distribution systems, sustainable urban water management and modelling of wastewater treatment plants. The water distribution topics cover asset and information management, planning, monitoring and control, hydraulic modelling of steady state and transients, water quality and treatment, demand and leakage management, optimisation, design and decision support systems, as well as reliability and security of water distribution systems. The sustainable urban water management topics include urban drainage systems, water reuse, social aspects of water management and also selected facets of water resources and irrigation. Computer control of wastewater treatment plants has been seen as less advanced than that of clean water systems. To address this imbalance, this book presents a number of modelling techniques developed specifically for these plants. Water Management Challenges in Global Change will prove to be invaluable to water and environmental engineering researchers and academics; managers, engineers and planners; and postgraduate students.

Download or read book Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering written by Kim, Dookie and published by IGI Global. This book was released on 2018-06-15 with total page 644 pages. Available in PDF, EPUB and Kindle. Book excerpt: The disciplines of science and engineering rely heavily on the forecasting of prospective constraints for concepts that have not yet been proven to exist, especially in areas such as artificial intelligence. Obtaining quality solutions to the problems presented becomes increasingly difficult due to the number of steps required to sift through the possible solutions, and the ability to solve such problems relies on the recognition of patterns and the categorization of data into specific sets. Predictive modeling and optimization methods allow unknown events to be categorized based on statistics and classifiers input by researchers. The Handbook of Research on Predictive Modeling and Optimization Methods in Science and Engineering is a critical reference source that provides comprehensive information on the use of optimization techniques and predictive models to solve real-life engineering and science problems. Through discussions on techniques such as robust design optimization, water level prediction, and the prediction of human actions, this publication identifies solutions to developing problems and new solutions for existing problems, making this publication a valuable resource for engineers, researchers, graduate students, and other professionals.

Download or read book Advances in Hydrologic Forecasts and Water Resources Management written by Fi-John Chang and published by MDPI. This book was released on 2021-01-20 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: The impacts of climate change on water resource management, as well as increasingly severe natural disasters over the last decades, have caught global attention. Reliable and accurate hydrological forecasts are essential for efficient water resource management and the mitigation of natural disasters. While the notorious nonlinear hydrological processes make accurate forecasts a very challenging task, it requires advanced techniques to build accurate forecast models and reliable management systems. One of the newest techniques for modeling complex systems is artificial intelligence (AI). AI can replicate the way humans learn and has great capability to efficiently extract crucial information from large amounts of data to solve complex problems. The fourteen research papers published in this Special Issue contribute significantly to the uncertainty assessment of operational hydrologic forecasting under changing environmental conditions and the promotion of water resources management by using the latest advanced techniques, such as AI techniques. The fourteen contributions across four major research areas: (1) machine learning approaches to hydrologic forecasting; (2) uncertainty analysis and assessment on hydrological modeling under changing environments; (3) AI techniques for optimizing multi-objective reservoir operation; (4) adaption strategies of extreme hydrological events for hazard mitigation. The papers published in this issue will not only advance water sciences but also help policymakers to achieve more sustainable and effective water resource management.

Download or read book Development of a Decision Support Framework ForIntegrated Watershed Water Quality Management and a Generic Genetic Algorithm Based Optimizer written by and published by . This book was released on 1908 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The watershed management approach is a framework for addressing water quality problems at a watershed scale in an integrated manner that considers many conflicting issues including cost, environmental impact and equity in evaluating alternative control strategies. This framework enhances the capabilities of current environmental analysis frameworks by the inclusion of additional systems analytic tools such as optimization algorithms that enable efficient search for cost effective control strategies and uncertainty analysis procedures that estimate the reliability in achieving water quality targets. Traditional optimization procedures impose severe restrictions in using complex nonlinear environmental processes within a systematic search. Hence, genetic algorithms (GAs), a class of general, probabilistic, heuristic, global, search procedures, are used. Current implementation of this framework is coupled with US EPA's BASINS software system. A component of the current research is also the development of GA object classes and optimization model classes for generic use. A graphical user interface allows users to formulate mathematical programming problems and solve them using GA methodology. This set of GA object and the user interface classes together comprise the Generic Genetic Algorithm Based Optimizer (GeGAOpt), which is demonstrated through applications in solving interactively several unconstrained as well as constrained function optimization problems. Design of these systems is based on object oriented paradigm and current software engineering practices such as object oriented analysis (OOA) and object oriented design (OOD). The development follows the waterfall model for software development. The Unified Modeling Language (UML) is used for the design. The implementation is carried out using the JavaTM programming environment.

Download or read book Computational Intelligence Techniques for Combating COVID 19 written by Sandeep Kautish and published by Springer Nature. This book was released on 2021 with total page 392 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the latest cutting edge research, theoretical methods, and novel applications in the field of computational intelligence and computational biological approaches that are aiming to combat COVID-19. The book gives the technological key drivers behind using AI to find drugs that target the virus, shedding light on the structure of COVID-19, detecting the outbreak and spread of new diseases, spotting signs of a COVID-19 infection in medical images, monitoring how the virus and lockdown is affecting mental health, and forecasting how COVID-19 cases and deaths will spread across cities and why. Further, the book helps readers understand computational intelligence techniques combating COVID-19 in a simple and systematic way. Provides a comprehensive reference covering innovations and development of theories, conceptual models and computational algorithms focused on COVID-19; Asserts all relevant research, key themes, complex adaptive systems, metrics and paradigms dedicated towards COVID-19, enabled with evolutionary methods of computational sciences; Explores how AI and computational techniques can help to predict which patients with the virus would go on to develop Acute Respiratory Distress Syndrome (ARDS).

Download or read book Handbook of Formal Optimization written by Anand J. Kulkarni and published by Springer Nature. This book was released on with total page 1406 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Women in Soft Computing written by Vanita Garg and published by Springer Nature. This book was released on 2023-12-18 with total page 161 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book gives a detailed information of various soft computing techniques across various fields for solving relevant, real-life problems. The authors, all female leaders in the field, show how soft computing uses approximate calculations to provide imprecise yet usable solutions to complex computational problems. This enables solutions for problems that may be either unsolvable or too time-consuming to solve with current hardware. The authors show how these techniques, when applied, have proven to be efficient and robust in many difficult situations. As an important part of the Women in Science and Engineering book series, the work highlights the contribution of women leaders in soft computing, inspiring women and men, girls and boys to enter and apply themselves to secure the future in the field.

Download or read book Exploring the Consequences of the COVID 19 Pandemic written by Usha Rana and published by CRC Press. This book was released on 2022-06-08 with total page 512 pages. Available in PDF, EPUB and Kindle. Book excerpt: This unique and topical book assesses the impact of coronavirus disease (COVID-19) on a multitude of different aspects of human life. With chapters from researchers from a diverse selection of countries, this new volume, Exploring the Consequences of the COVID-19 Pandemic: Social, Cultural, Economic, and Psychological Insights and Perspectives, provides an insightful understanding of the challenges and impacts of COVID-19 on mental health, health care, gender issues, education, social institutions, and more. The diverse studies in this volume look at community responses and social challenges during COVID-19, covering topics such as social protection challenges and measures, the responsibility of the state to its citizens, and human rights and inhuman wrongs. The volume also examines health challenges and consequences of COVID-19, such as the impact on maternal and reproductive health, on mental health, the psychological effects of isolation, and more. The volume also includes studies on gender issues such as the plight of women migrant workers during the pandemic, feminist activism during quarantine, the impact on vulnerable groups of society, and how the pandemic affected interpersonal relations and behavior. The volume also takes a look at the roles of different organizations and professions and their reactions to the health crisis, including police, journalists and the media, and educators. The issues of the closure of schools and colleges and remote learning are also addressed. There is even a mathematical study of optimum budget allocation for social projects to control the COVID-19 pandemic. The enlightening volume provides an in-depth understanding of sociocultural responses to the COVID-19 and its consequences on society and will be of value to many sectors of society, including government and nongovernment organizations, policymakers and policy analysts, medical research organizations, schools and universities, healthcare practitioners, sociologists, and many others.

Download or read book Interactive Genetic Algorithms for Watershed Planning written by Adriana Debora Piemonti and published by . This book was released on 2016 with total page 197 pages. Available in PDF, EPUB and Kindle. Book excerpt: Degradation of watersheds is a major concern in areas where adverse climate effects and unsustainable use of the natural resources have caused extensive stresses to watershed systems (e.g., increased floods, increased droughts, worsened in-stream water quality) through the years. While considerable efforts are being made to generate technical solutions that focus on plans of spatially-distributed conservation practices (e.g., Wetlands, Filter Strips, Grassed Waterways, Crop Management practices, etc.) for restoration of existing conditions in the watersheds, adoption and implementation of these solutions require a better understanding of constraints faced by affected stakeholders and decision makers. Participatory modeling and design approaches have, as a result, become popular in the recent past to support a community's engagement during the modeling process and during development of potential scenarios of plans (or, design alternatives). And now, with new and ongoing developments in Web 2.0 technologies, there is an even greater need for research that examines how large number of stakeholders can be engaged in the development of design alternatives via the internet-based, decision support environments. The overarching goal of this research is to investigate how stakeholder participation ("humans") and Interactive Genetic Algorithms ("computer") can be coupled in a web-based watershed decision support system (DSS) called WRESTORE (Watershed REstoration using Spatio Temporal Optimization of REsources- http://wrestore.iupui.edu/), in order to generate user-preferred design alternatives of distributed conservation practices on a watershed landscape. An important component of this goal is to also improve the understanding of how human behavior on the graphical user interface (GUI) of the DSS can be observed and evaluated in real-time, and then learned from to further improve the performance of the underlying search algorithm. Four specific objectives were addressed in this work to accomplish the overall goal: · Objective 1: Observe interactions of multiple users with the GUI of a web-based watershed DSS (WRESTORE, http://wrestore.iupui.edu/) during interactive search experiments, and then use Usability metrics (response times, clicking events and confidence levels) to evaluate the differences and similarities in user behaviors and interactions. · Objective 2: Examine relationships between the type of users (e.g., stakeholders versus surrogates), the Usability metrics, and patterns in the watershed-scale plans of conservation practices generated by the multi-objective Interactive Genetic Algorithm embedded in WRESTORE. · Objective 3: Examine relationships between the type of users, the Usability metrics, and patterns in the user-preferred, sub-basin-scale plans of conservation practices generated by the multi-objective Interactive Genetic Algorithm embedded in WRESTORE. · Objective 4: Develop and test novel human-guided search operators that adaptively learn for patterns in user-preferred alternatives generated by the multi-objective Interactive Genetic Algorithm, and, as a result, improve the convergence rate of the search algorithm for generating design alternatives that conserve these learned patterns. Results show that there is a clear difference on how different types of users interact with the Interactive Optimization system. The observed relationship between confidence levels, time spent on a task, and number of mouse clicking events, indicated that participants who were able to use the WRESTORE GUI to gather more information and had a higher rate of time per number of clicks, tended to increase their levels of self-confidence in their own feedback. Also, when engaging with watershed stakeholders versus non-stakeholders (or, surrogates), 67% of the stakeholder participants steadily increased their average self-confidence levels as they continued to interact with the tool, in contrast to only 29% of surrogate participants who also showed an increase in their self-confidence levels through time. Such usability and confidence level evaluations provide assessments on which participant was potentially generating reliable feedback data for the search algorithm to use. An analysis of design alternatives generated by the individuals in both stakeholder and non-stakeholder groups showed that a majority (67%) of the stakeholder participants found a higher percentage (on and average 52%) of preferred design alternatives via the interactive search process. Also, users who were focused on assessing the suitability of design alternatives for the entire watershed trended to demonstrate a bias for one of the watershed-scale objective functions. In contrast, users, who were focused on assessing the suitability of design alternatives at only a few local sub-basins in the watershed, did not demonstrate any clear bias for any one of the watershed-scale objective functions. Additionally, patterns were observed in the design of decision alternatives generated by the human-centered search process, which further divulged potential user preferences related to the decision space for example, whether a specific participant preferred a certain practice over another, or a certain location over another for a specific practice. Finally, to improve the convergence rates of the Interactive Genetic Algorithm in WRESTORE, we investigated whether observed patterns in decisions (especially, when users were focused on local sub-regions of the watershed) can be used to improve the search for user-desire designs. A novel Interactive Genetic Algorithm with adaptive, human-guided, selection, crossover and mutation operators was proposed. The new algorithm was tested with six types of simulated participants (three deterministic and three probabilistic users) developed from the feedback data of three real participants. Results of search experiments with the novel adaptive IGA operators indicated a faster convergence than the default IGA, for two out of three deterministic simulated users. However, none of the probabilistic user showed a convergence different than the default values. This indicates that while current results indicate promise, there is need for additional research on adaptive, human-guided IGA operators, especially when noisy/stochastic users participate in the search. Additionally, adaptation of search operators have the potential to improve convergence rates when participatory design is done via Interactive Genetic Algorithms.

Download or read book Hydrology Hydraulics and Water Resources Management written by K.L. Katsifarakis and published by WIT Press. This book was released on 2012-07-11 with total page 175 pages. Available in PDF, EPUB and Kindle. Book excerpt: With population of our planet exceeding seven billion, funds for infrastructure works being limited worldwide and climate change affecting water resources, their optimal development and management is literally vital. This volume deals with application of some non-traditional optimization techniques to hydraulics, hydrology and water resources management and aims at helping scientists dealing with these issues to reach the best decisions. Chapter 1 is a brief introduction to optimization and its application to water resources management. Chapter 2 is dedicated to genetic algorithms. Chapter 3 focuses on applications of genetic algorithms to hydraulic networks, mainly irrigation ones. Chapter 4 is dedicated to simulated annealing. The particle swarm method (PSO) is discussed in Chapter 5. In Chapter 6 the basic concepts and features of Tabu search are presented and its coupling with other heuristic optimizers is discussed. Chapter 7 is dedicated to the Harmony Search method. Finally, Chapter 8 deals with the Outer Approximation method. This book is aimed at engineers and other scientists working on water resources management and hydraulic networks.

Download or read book Evolutionary Algorithms for Solving Multi Objective Problems written by Carlos Coello Coello and published by Springer Science & Business Media. This book was released on 2013-03-09 with total page 600 pages. Available in PDF, EPUB and Kindle. Book excerpt: Researchers and practitioners alike are increasingly turning to search, op timization, and machine-learning procedures based on natural selection and natural genetics to solve problems across the spectrum of human endeavor. These genetic algorithms and techniques of evolutionary computation are solv ing problems and inventing new hardware and software that rival human designs. The Kluwer Series on Genetic Algorithms and Evolutionary Computation pub lishes research monographs, edited collections, and graduate-level texts in this rapidly growing field. Primary areas of coverage include the theory, implemen tation, and application of genetic algorithms (GAs), evolution strategies (ESs), evolutionary programming (EP), learning classifier systems (LCSs) and other variants of genetic and evolutionary computation (GEC). The series also pub lishes texts in related fields such as artificial life, adaptive behavior, artificial immune systems, agent-based systems, neural computing, fuzzy systems, and quantum computing as long as GEC techniques are part of or inspiration for the system being described. This encyclopedic volume on the use of the algorithms of genetic and evolu tionary computation for the solution of multi-objective problems is a landmark addition to the literature that comes just in the nick of time. Multi-objective evolutionary algorithms (MOEAs) are receiving increasing and unprecedented attention. Researchers and practitioners are finding an irresistible match be tween the popUlation available in most genetic and evolutionary algorithms and the need in multi-objective problems to approximate the Pareto trade-off curve or surface.

Download or read book Intelligent Techniques in Engineering Management written by Cengiz Kahraman and published by Springer. This book was released on 2015-05-05 with total page 747 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recently developed intelligent techniques with applications and theory in the area of engineering management. The involved applications of intelligent techniques such as neural networks, fuzzy sets, Tabu search, genetic algorithms, etc. will be useful for engineering managers, postgraduate students, researchers, and lecturers. The book has been written considering the contents of a classical engineering management book but intelligent techniques are used for handling the engineering management problem areas. This comprehensive characteristics of the book makes it an excellent reference for the solution of complex problems of engineering management. The authors of the chapters are well-known researchers with their previous works in the area of engineering management.

Download or read book Music Inspired Harmony Search Algorithm written by Zong Woo Geem and published by Springer. This book was released on 2009-02-19 with total page 210 pages. Available in PDF, EPUB and Kindle. Book excerpt: Calculus has been used in solving many scientific and engineering problems. For optimization problems, however, the differential calculus technique sometimes has a drawback when the objective function is step-wise, discontinuous, or multi-modal, or when decision variables are discrete rather than continuous. Thus, researchers have recently turned their interests into metaheuristic algorithms that have been inspired by natural phenomena such as evolution, animal behavior, or metallic annealing. This book especially focuses on a music-inspired metaheuristic algorithm, harmony search. Interestingly, there exists an analogy between music and optimization: each musical instrument corresponds to each decision variable; musical note corresponds to variable value; and harmony corresponds to solution vector. Just like musicians in Jazz improvisation play notes randomly or based on experiences in order to find fantastic harmony, variables in the harmony search algorithm have random values or previously-memorized good values in order to find optimal solution.