Metaheuristic Procedures for Training Neural Networks
Metaheuristic Procedures For Training Neural Networks provides successful implementations of metaheuristic methods for neural network training. Apart from Chapter 1, which reviews classical training methods, the chapters are divided into three main categories. The first one is devoted to local search based methods, including Simulated Annealing, Tabu Search, and Variable Neighborhood Search.
Metaheuristic Optimization via Memory and Evolution : Tabu Search and Scatter Search
Tabu Search (TS) and, more recently, Scatter Search (SS) have proved highly effective in solving a wide range of optimization problems, and have had a variety of applications in industry, science, and government. The goal of METAHEURISTIC OPTIMIZATION VIA MEMORY AND EVOLUTION: Tabu Search and Scatter Search is to report original research on algorithms and applications of tabu search, scatter search or both, as well as variations and extensions having "adaptive memory programming" as a primary focus. Individual chapters identify useful new implementations or new ways to integrate and apply the principles of TS and SS, or that prove new theoretical results, or describe the successful application of these methods to real world problems.The chapters of this book provide a series of landmarks along the way as we investigate and seek to better understand the elements of tabu search and scatter search that account for their successes in an astonishingly varied range of applications.
Meshfree Methods for Partial Differential Equations III
Meshfree methods for the numerical solution of partial differential equations are becoming more and more mainstream in many areas of applications. Their flexiblity and wide applicability are attracting engineers, scientists, and mathematicians to this very dynamic research area. This volume represents the state of the art in meshfree methods. It consists of articles which address the different meshfree techniques, their mathematical properties and their application in applied mathematics, physics and engineering.
Mechanisms, Symbols, and Models Underlying Cognition ; 1st International Work-Conference on the Interplay Between Natural and Artificial Computation, IWINAC 2005, Las Palmas, Canary Islands, Spain, June 15-18, 2005, Proceedings, Part I
Constitute the refereed proceedings of the First International Work-Conference on the Interplay between Natural and Artificial Computation, IWINAC 2005. This two-volume set contains papers that are related with the conceptual developments in the fields of Neurophysiology and cognitive science, and also to bioinspired programming strategies.
IoT and AI Technologies for Sustainable Living : A Practical Handbook
Brings together all the latest methodologies, tools and techniques related to the Internet of Things and Artificial Intelligence in a single volume to build insight into their use in sustainable living. The areas of application include agriculture, smart farming, healthcare, bioinformatics, self-diagnosis systems, body sensor networks, multimedia mining, and multimedia in forensics and security. Provides a comprehensive discussion of modeling and implementation in water resource optimization, recognizing pest patterns, traffic scheduling, web mining, cyber security and cyber forensics. It will help develop an understanding of the need for AI and IoT to have a sustainable era of human living. The tools covered include genetic algorithms, cloud computing, water resource management, web mining, machine learning, block chaining, learning algorithms, sentimental analysis and Natural Language Processing (NLP).
Introduction to Genetic Algorithms
This book is designed to provide an in-depth knowledge on the basic operational features and characteristics of Genetic Algorithms. The various operators and techniques given in the book are pertinent to carry out Genetic Algorithm Research Projects. The book also explores the different types are Genetic Algorithms available with their importance. Implementation of Genetic Algorithm concept has been performed using the universal language C/C++ and the discussion also extends to Genetic Algorithm MATLAB Toolbox. Few Genetic Algorithm problems are programmed using MATLAB and the simulated results are given for the ready reference of the reader. The applications of Genetic Algorithms in Machine learning, Mechanical Engineering, Electrical Engineering, Civil Engineering, Data Mining, Image Processing, and VLSI are dealt to make the readers understand where the concept can be applied.
Introduction to Engineering Statistics and Six Sigma : Statistical Quality Control and Design of Experiments and Systems
Introduction to Engineering Statistics and Six Sigma contains precise descriptions of all of the many related methods and details case studies showing how they have been applied in engineering and business to achieve millions of dollars of savings. Specifically, the methods introduced include many kinds of design of experiments (DOE) and statistical process control (SPC) charting approaches, failure mode and effects analysis (FMEA), formal optimization, genetic algorithms, gauge reproducibility and repeatability (R&R), linear regression, neural nets, simulation, quality function deployment (QFD) and Taguchi methods. A major goal of the book is to help the reader to determine exactly which methods to apply in which situation and to predict how and when the methods might not be effective.
Intelligent Multimedia Processing with Soft Computing
This edited monograph presents novel applications of soft computing in multimedia processing. It includes contributions by leading experts in their fields addressing important and timely problems in multimedia computing.
Intelligent Information Technology ; 7th International Conference on Information Technology, CIT 2004, Hyderabad, India, December 20-23, 2004, Proceedings
Focused on the latest research findings on all topics in the area of information technology. Although the natural focus was on computer science issues, research results contributed from management, business and other disciplines formed an integral part. We received more than 200 papers from over 27 countries in the areas of com- tational intelligence, neural networks, mobile and adhoc networks, security, databases, software engineering, signal and image processing, and Internet and WWW-based computing. The programme committee, consisting of eminent researchers, academicians and practitioners, finally selected 43 full papers on the basis of reviewer grades. This proceedings contains the research papers selected for presentation at the c- ference and this is the first time that the proceedings have been published in the Lecture Notes in Computer Science (LNCS) series. The poster papers are being printed as a separate conference proceedings.
Integration of Fuzzy Logic and Chaos Theory
Attempts to present some current research progress and results on the interplay of fuzzy logic and chaos theory. More specifically, this book includes a collection of some state-of-theart surveys, tutorials, and application examples written by some experts working in the interdisciplinary fields overlapping fuzzy logic and chaos theory.
Innovations in Machine Learning : Theory and Applications
Machine learning is currently one of the most rapidly growing areas of research in computer science. In compiling this volume we have brought together contributions from some of the most prestigious researchers in this field. This book covers the three main learning systems; symbolic learning, neural networks and genetic algorithms as well as providing a tutorial on learning casual influences. Each of the nine chapters is self-contained. Both theoreticians and application scientists/engineers in the broad area of artificial intelligence will find this volume valuable. It also provides a useful sourcebook for Postgraduate since it shows the direction of current research.
Innovations in Hybrid Intelligent Systems
Hybrid Artificial Intelligence Systems (HAIS) combines symbolic and sub-symbolic techniques to construct more robust and reliable problem solving models. This volume focused on "Hybrid Artificial Intelligence Systems" contains a collection of papers that were presented at the 2nd International Workshop on Hybrid Artificial Intelligence Systems, held in 12 - 13 November, 2007, Salamanca, Spain. This carefully edited book provides a comprehensive overview of the recent advances in the hybrid intelligent systems and covers a wide range of application areas, including data analysis and data mining, intelligent control, pattern recognition, robotics, optimization, etc. The book is aimed at researchers, practitioners and postgraduate students who are engaged in developing and applying advanced intelligent systems principles to solving real-world problems.
Innovations and Advanced Techniques in Computer and Information Sciences and Engineering
Innovations and Advanced Techniques in Computer and Information Sciences and Engineering is a collection of world class paper articles addressing the following topics: Signal and Image Processing: Content Based Video Retrieval, Character Recognition, Incremental Learning for Speech Recognition, Signal Processing Theory and Methods, and Vision-based Monitoring Systems. Software and Systems: Activity-Based Software Estimation, Algorithms, Genetic Algorithms, Information Systems Security, Programming Languages, Software Protection Techniques, Software Protection Techniques, and User Interfaces. Distributed Processing: Asynchronous Message Passing System, Heterogeneous Software Environments, Mobile Ad Hoc Networks, Resource Allocation, and Sensor Networks. Advanced and innovative techniques in computing: e-Science and Virtual Instrumentation, Fault-Tolerant Scheduling, Grid Computing, Microcracking in Cortical Bones, Service-oriented Architectures, and Virtualization in Data Warehouses.
Information Retrieval Technology ; Vol. 4182 ; 3rd Asia Information Retrieval Symposium, AIRS 2006, Singapore, October 16-18, 2006, Proceedings
Asia Information Retrieval Symposium (AIRS) 2006 was the third AIRS conf- ence in the series established in 2004.The ?rst AIRS washeld in Beijing, China, and the 2nd AIRS was held in Cheju, Korea. The AIRS conference series traces its roots to the successful Information Retrieval with Asian Languages (IRAL) workshop series which started in 1996. The AIRS series aims to bring together international researchers and dev- opers to exchange new ideas and the latest results in information retrieval. The scope of the conference encompassed the theory and practice of all aspects of information retrieval in text, audio, image, video, and multimedia data. Wearehappyto reportthatAIRS2006received148submissions,thehighest number since the conference series started in 2004. Submissions came from Asia and Australasia, Europe, and North America. We accepted 34 submissions as regular papers (23%) and 24 as poster papers (16%). We would like to thank all the authors who submitted papers to the conf- ence, the seven area chairs, who worked tirelessly to recruit the program c- mittee members and oversaw the review process, and the program committee members and their secondary reviewers who reviewed all the submissions.
Independent Component Analysis and Blind Signal Separation ; 6th International Conference, ICA 2006, Charleston, SC, USA, March 5-8, 2006, Proceedings
This book constitutes the refereed proceedings of the 6th International Conference on Independent Component Analysis and Blind Source Separation, ICA 2006, held in Charleston, SC, USA, in March 2006. The 120 revised papers presented were carefully reviewed and selected from 183 submissions. The papers are organized in topical sections on algorithms and architectures, applications, medical applications, speech and signal processing, theory, and visual and sensory processing.
Hybrid metaheuristics ; Vol. 4030 ; 3rd International Workshop, HM 2006, Gran Canaria, Spain, October 13-14, 2006, Proceedings
The selection of papers for HM 2006 consolidated some of the mainstream issues that have emerged from the past editions. Firstly, there are prominent examples of e?ective hybrid techniques whose design and implementation were motivated by challenging real-world applications. We believe this is particularly important for two reasons: on the one hand, researchers are conscious that the primary goal of developing algorithms is to solve relevant real-life problems; on the other hand, the path towarde?cient solving methods for practical problems is a source of new outstanding ideas and theories. A second important issue is that the research community on metaheur- tics has become increasingly interested in and open to techniques and methods known from arti?cial intelligence (AI) and operations research (OR). So far, the most representative examples of such integration have been the use of AI/OR techniques as subordinates of metaheuristic methods. As a historical and - ymological note, this is in perfect accordance with the original meaning of a metaheuristic as a “general strategy controlling a subordinate heuristic. ” The awareness of the need for a sound experimental methodology is a third keypoint.
Hybrid metaheuristics ; Vol. 3636 ; 2nd International Workshop, HM 2005, Barcelona, Spain, August 29-30, 2005. Proceedings
Constitutes the refereed proceedings of the Second International Workshop on Hybrid Metaheuristics, HM 2005, held in Barcelona, Spain, in August 2005. In this book, the papers addresses topics such as: low-level hybridization, high-level hybridization, portfolio techniques, expert systems, co-operative search, taxonomy, terminology, and more.
Hybrid metaheuristics ; 4th International Workshop,HM 2007, Dortmund, Germany, October 8-9, 2007, Proceedings
This book constitutes the refereed proceedings of the 4th International Workshop on Hybrid Metaheuristics, HM 2007, held in Dortmund, Germany. The 14 revised full papers discuss specific aspects of hybridization of metaheuristics, hybrid metaheuristics design, development and testing.
Hybrid Intelligent Systems for Pattern Recognition Using Soft Computing : An Evolutionary Approach for Neural Networks and Fuzzy Systems
This monograph describes new methods for intelligent pattern recognition using soft computing techniques including neural networks, fuzzy logic, and genetic algorithms. Hybrid intelligent systems that combine several soft computing techniques are needed due to the complexity of pattern recognition problems.
Hybrid Intelligent Systems : Analysis and Design
The objective of this edited volume is to offer a general view at the recent conceptual developments of Soft Computing (SC) regarded as a general methodology supporting the design of hybrid systems along with their diversified applications to modeling, simulation and control of non-linear dynamical systems. As of now, SC methodologies embrace neural networks, fuzzy logic, genetic algorithms and chaos theory. Each of these methodologies exhibits well delineated advantages and disadvantages. Interestingly, they have been found useful in solving a broad range of problems. However, many real-world complex problems require a prudent, carefully orchestrated integration of several of these methodologies to fully achieve the required efficiency, accuracy, and interpretability of the solutions. In this edited volume, an overview of SC methodologies, and their applications to modeling, simulation and control, will be given in an introductory paper by the Editors. Then, detailed methods for integrating the different SC methodologies in solving real-world problems will be given in the papers by the other authors in the book. The edited volume will cover a wide spectrum of applications including areas such as: robotic dynamic systems, non-linear plants, manufacturing systems, and time series prediction.



















