Read Books Online and Download eBooks, EPub, PDF, Mobi, Kindle, Text Full Free.
Multi Objective Optimization Using Artificial Intelligence Techniques
Download Multi Objective Optimization Using Artificial Intelligence Techniques full books in PDF, epub, and Kindle. Read online Multi Objective Optimization Using Artificial Intelligence Techniques ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!
Book Synopsis Multi-Objective Optimization using Artificial Intelligence Techniques by : Seyedali Mirjalili
Download or read book Multi-Objective Optimization using Artificial Intelligence Techniques written by Seyedali Mirjalili and published by Springer. This book was released on 2019-07-24 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
Book Synopsis Multi-Objective Optimization Using Artificial Intelligence Techniques by : Seyedali Mirjalili
Download or read book Multi-Objective Optimization Using Artificial Intelligence Techniques written by Seyedali Mirjalili and published by . This book was released on 2020 with total page 58 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on the most well-regarded and recent nature-inspired algorithms capable of solving optimization problems with multiple objectives. Firstly, it provides preliminaries and essential definitions in multi-objective problems and different paradigms to solve them. It then presents an in-depth explanations of the theory, literature review, and applications of several widely-used algorithms, such as Multi-objective Particle Swarm Optimizer, Multi-Objective Genetic Algorithm and Multi-objective GreyWolf Optimizer Due to the simplicity of the techniques and flexibility, readers from any field of study can employ them for solving multi-objective optimization problem. The book provides the source codes for all the proposed algorithms on a dedicated webpage.
Book Synopsis Multi-Objective Machine Learning by : Yaochu Jin
Download or read book Multi-Objective Machine Learning written by Yaochu Jin and published by Springer Science & Business Media. This book was released on 2007-06-10 with total page 657 pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, increasing interest has been shown in applying the concept of Pareto-optimality to machine learning, particularly inspired by the successful developments in evolutionary multi-objective optimization. It has been shown that the multi-objective approach to machine learning is particularly successful to improve the performance of the traditional single objective machine learning methods, to generate highly diverse multiple Pareto-optimal models for constructing ensembles models and, and to achieve a desired trade-off between accuracy and interpretability of neural networks or fuzzy systems. This monograph presents a selected collection of research work on multi-objective approach to machine learning, including multi-objective feature selection, multi-objective model selection in training multi-layer perceptrons, radial-basis-function networks, support vector machines, decision trees, and intelligent systems.
Book Synopsis Multi-Objective Optimization in Computational Intelligence: Theory and Practice by : Thu Bui, Lam
Download or read book Multi-Objective Optimization in Computational Intelligence: Theory and Practice written by Thu Bui, Lam and published by IGI Global. This book was released on 2008-05-31 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multi-objective optimization (MO) is a fast-developing field in computational intelligence research. Giving decision makers more options to choose from using some post-analysis preference information, there are a number of competitive MO techniques with an increasingly large number of MO real-world applications. Multi-Objective Optimization in Computational Intelligence: Theory and Practice explores the theoretical, as well as empirical, performance of MOs on a wide range of optimization issues including combinatorial, real-valued, dynamic, and noisy problems. This book provides scholars, academics, and practitioners with a fundamental, comprehensive collection of research on multi-objective optimization techniques, applications, and practices.
Book Synopsis Bio-Inspired Systems: Computational and Ambient Intelligence by : Joan Cabestany
Download or read book Bio-Inspired Systems: Computational and Ambient Intelligence written by Joan Cabestany and published by Springer Science & Business Media. This book was released on 2009-06-08 with total page 1403 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 10th International Work-Conference on Artificial Neural Networks, IWANN 2009, held in Salamanca, Spain in June 2009. The 167 revised full papers presented together with 3 invited lectures were carefully reviewed and selected from over 230 submissions. The papers are organized in thematic sections on theoretical foundations and models; learning and adaptation; self-organizing networks, methods and applications; fuzzy systems; evolutionary computation and genetic algoritms; pattern recognition; formal languages in linguistics; agents and multi-agent on intelligent systems; brain-computer interfaces (bci); multiobjetive optimization; robotics; bioinformatics; biomedical applications; ambient assisted living (aal) and ambient intelligence (ai); other applications.
Book Synopsis Computational Intelligence in Optimization by : Yoel Tenne
Download or read book Computational Intelligence in Optimization written by Yoel Tenne and published by Springer Science & Business Media. This book was released on 2010-06-30 with total page 412 pages. Available in PDF, EPUB and Kindle. Book excerpt: This collection of recent studies spans a range of computational intelligence applications, emphasizing their application to challenging real-world problems. Covers Intelligent agent-based algorithms, Hybrid intelligent systems, Machine learning and more.
Book Synopsis Multiobjective Optimization by : Jürgen Branke
Download or read book Multiobjective Optimization written by Jürgen Branke and published by Springer. This book was released on 2008-10-18 with total page 470 pages. Available in PDF, EPUB and Kindle. Book excerpt: Multiobjective optimization deals with solving problems having not only one, but multiple, often conflicting, criteria. Such problems can arise in practically every field of science, engineering and business, and the need for efficient and reliable solution methods is increasing. The task is challenging due to the fact that, instead of a single optimal solution, multiobjective optimization results in a number of solutions with different trade-offs among criteria, also known as Pareto optimal or efficient solutions. Hence, a decision maker is needed to provide additional preference information and to identify the most satisfactory solution. Depending on the paradigm used, such information may be introduced before, during, or after the optimization process. Clearly, research and application in multiobjective optimization involve expertise in optimization as well as in decision support. This state-of-the-art survey originates from the International Seminar on Practical Approaches to Multiobjective Optimization, held in Dagstuhl Castle, Germany, in December 2006, which brought together leading experts from various contemporary multiobjective optimization fields, including evolutionary multiobjective optimization (EMO), multiple criteria decision making (MCDM) and multiple criteria decision aiding (MCDA). This book gives a unique and detailed account of the current status of research and applications in the field of multiobjective optimization. It contains 16 chapters grouped in the following 5 thematic sections: Basics on Multiobjective Optimization; Recent Interactive and Preference-Based Approaches; Visualization of Solutions; Modelling, Implementation and Applications; and Quality Assessment, Learning, and Future Challenges.
Book Synopsis Multi-Objective Optimization using Evolutionary Algorithms by : Kalyanmoy Deb
Download or read book Multi-Objective Optimization using Evolutionary Algorithms written by Kalyanmoy Deb and published by John Wiley & Sons. This book was released on 2001-07-05 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Optimierung mit mehreren Zielen, evolutionäre Algorithmen: Dieses Buch wendet sich vorrangig an Einsteiger, denn es werden kaum Vorkenntnisse vorausgesetzt. Geboten werden alle notwendigen Grundlagen, um die Theorie auf Probleme der Ingenieurtechnik, der Vorhersage und der Planung anzuwenden. Der Autor gibt auch einen Ausblick auf Forschungsaufgaben der Zukunft.
Book Synopsis Evolutionary Algorithms for Solving Multi-Objective Problems by : Carlos Coello Coello
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 2007-08-26 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.
Book Synopsis Applications Of Multi-objective Evolutionary Algorithms by : Carlos A Coello Coello
Download or read book Applications Of Multi-objective Evolutionary Algorithms written by Carlos A Coello Coello and published by World Scientific. This book was released on 2004-12-08 with total page 791 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents an extensive variety of multi-objective problems across diverse disciplines, along with statistical solutions using multi-objective evolutionary algorithms (MOEAs). The topics discussed serve to promote a wider understanding as well as the use of MOEAs, the aim being to find good solutions for high-dimensional real-world design applications. The book contains a large collection of MOEA applications from many researchers, and thus provides the practitioner with detailed algorithmic direction to achieve good results in their selected problem domain.
Book Synopsis Multi-Objective Decision Making by : Diederik M. Zhou
Download or read book Multi-Objective Decision Making written by Diederik M. Zhou and published by Springer Nature. This book was released on 2022-05-31 with total page 111 pages. Available in PDF, EPUB and Kindle. Book excerpt: Many real-world decision problems have multiple objectives. For example, when choosing a medical treatment plan, we want to maximize the efficacy of the treatment, but also minimize the side effects. These objectives typically conflict, e.g., we can often increase the efficacy of the treatment, but at the cost of more severe side effects. In this book, we outline how to deal with multiple objectives in decision-theoretic planning and reinforcement learning algorithms. To illustrate this, we employ the popular problem classes of multi-objective Markov decision processes (MOMDPs) and multi-objective coordination graphs (MO-CoGs). First, we discuss different use cases for multi-objective decision making, and why they often necessitate explicitly multi-objective algorithms. We advocate a utility-based approach to multi-objective decision making, i.e., that what constitutes an optimal solution to a multi-objective decision problem should be derived from the available information about user utility. We show how different assumptions about user utility and what types of policies are allowed lead to different solution concepts, which we outline in a taxonomy of multi-objective decision problems. Second, we show how to create new methods for multi-objective decision making using existing single-objective methods as a basis. Focusing on planning, we describe two ways to creating multi-objective algorithms: in the inner loop approach, the inner workings of a single-objective method are adapted to work with multi-objective solution concepts; in the outer loop approach, a wrapper is created around a single-objective method that solves the multi-objective problem as a series of single-objective problems. After discussing the creation of such methods for the planning setting, we discuss how these approaches apply to the learning setting. Next, we discuss three promising application domains for multi-objective decision making algorithms: energy, health, and infrastructure and transportation. Finally, we conclude by outlining important open problems and promising future directions.
Book Synopsis AI 2008: Advances in Artificial Intelligence by : Wayne Wobcke
Download or read book AI 2008: Advances in Artificial Intelligence written by Wayne Wobcke and published by Springer Science & Business Media. This book was released on 2008-11-13 with total page 631 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 21th Australasian Joint Conference on Artificial Intelligence, AI 2008, held in Auckland, New Zealand, in December 2008. The 42 revised full papers and 21 revised short papers presented together with 1 invited lecture were carefully reviewed and selected from 143 submissions. The papers are organized in topical sections on knowledge representation, constraints, planning, grammar and language processing, statistical learning, machine learning, data mining, knowledge discovery, soft computing, vision and image processing, and AI applications.
Book Synopsis Neural Networks and Artificial Intelligence by : Vladimir Golovko
Download or read book Neural Networks and Artificial Intelligence written by Vladimir Golovko and published by Springer. This book was released on 2014-05-27 with total page 211 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the 8th International Conference on Neural Networks and Artificial Intelligence, ICNNAI 2014, held in Brest, Belarus, in June 2014. The 19 revised full papers presented were carefully reviewed and selected from 27 submissions. The papers are organized in topical sections on forest resource management; artificial intelligence by neural networks; optimization; classification; fuzzy approach; machine intelligence; analytical approach; mobile robot; real world application.
Book Synopsis Cohort Intelligence: A Socio-inspired Optimization Method by : Anand Jayant Kulkarni
Download or read book Cohort Intelligence: A Socio-inspired Optimization Method written by Anand Jayant Kulkarni and published by Springer. This book was released on 2016-09-22 with total page 134 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Volume discusses the underlying principles and analysis of the different concepts associated with an emerging socio-inspired optimization tool referred to as Cohort Intelligence (CI). CI algorithms have been coded in Matlab and are freely available from the link provided inside the book. The book demonstrates the ability of CI methodology for solving combinatorial problems such as Traveling Salesman Problem and Knapsack Problem in addition to real world applications from the healthcare, inventory, supply chain optimization and Cross-Border transportation. The inherent ability of handling constraints based on probability distribution is also revealed and proved using these problems.
Book Synopsis Multi-Objective Optimization by : Jyotsna K. Mandal
Download or read book Multi-Objective Optimization written by Jyotsna K. Mandal and published by Springer. This book was released on 2018-08-18 with total page 318 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together the latest findings on efficient solutions of multi/many-objective optimization problems from the leading researchers in the field. The focus is on solving real-world optimization problems using strategies ranging from evolutionary to hybrid frameworks, and involving various computation platforms. The topics covered include solution frameworks using evolutionary to hybrid models in application areas like Analytics, Cancer Research, Traffic Management, Networks and Communications, E-Governance, Quantum Technology, Image Processing, etc. As such, the book offers a valuable resource for all postgraduate students and researchers interested in exploring solution frameworks for multi/many-objective optimization problems.
Book Synopsis Applied Multi-objective Optimization by : Nilanjan Dey
Download or read book Applied Multi-objective Optimization written by Nilanjan Dey and published by Springer Nature. This book was released on 2024 with total page 181 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book explains basic ideas behind several kinds of applied multi-objective optimization and shows how it will be applied in practical contexts in the domain of healthcare, engineering design, and manufacturing. The book discusses how meta-heuristic algorithms are successful in resolving challenging, multi-objective optimization issues in various disciplines, including engineering, economics, medical and environmental management. The topic is useful for graduates, researchers and lecturers in optimization, engineering, management science and computer science.
Book Synopsis Evolutionary Algorithms for Solving Multi-Objective Problems by : Carlos Coello Coello
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 2007-09-18 with total page 810 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook is a second edition of Evolutionary Algorithms for Solving Multi-Objective Problems, significantly expanded and adapted for the classroom. The various features of multi-objective evolutionary algorithms are presented here in an innovative and student-friendly fashion, incorporating state-of-the-art research. The book disseminates the application of evolutionary algorithm techniques to a variety of practical problems. It contains exhaustive appendices, index and bibliography and links to a complete set of teaching tutorials, exercises and solutions.
