Shu-Heng Chen

L. C. Jain

Chung-Ching Tai

"This book identifies the economic as well as financial problems that may be solved efficiently with computational methods and explains why those problems should best be solved with computational methods"--Provided by publisher.

A Perspective from Computational Intelligence

Computational Economics

There is a trend to offer courses by virtual means. This approach has definite advantages. For example, virtual programs target professionals who would otherwise have to leave their jobs to pursue the degree. An enormous proportion of universities are in the process of developing courses in a virtual environment. This book deals with virtual environments for teaching and learning. The chapters can be considered to be representative of the many approaches taken and the diversity of applications. The different perspectives and different solutions adopted are the result of intense research in various countries in the area of e-learning. Contents: Use of Virtual Worlds to Teach the Sciences (B M Slator et al.); Traditional vs. Technology-Integrated Distance Education (Z Erlich et al.); Facilitators and Inhibitors of E-Learning (J Liu et al.); Developing and Accessing Adaptive Internet-Based Courses (R M Carro et al.); Towards Intelligent Media-Oriented E-Learning Environments (M Kayama & T Okamoto); An Intelligent Tutoring System for Student Guidance in Web-Based Courses (B uzdemir & F N Alpaslan); Automatic Generation of Problems in Web-Based Tutors (M V Belmonte et al.); The Design of Internet-Based Interactive Learning Models Using Agents and Their Applications (T Ichimura et al.); Supporting Personalization in Distance Education Virtual Communities (E Gaudioso & J G Boticario); An Intelligent System for Capturing Presentation on Desktop Manipulations C Supporting for Video Contents Production (Y Nakamura et al.). Readership: Academics and researchers in education and computer science."

Virtual Environments for Teaching & Learning

This book deals with virtual environments for teaching and learning. The selection of chapters provides different and diverse views of e-learning approaches in various countries and educational contexts. [p.xxviii, ed].

Virtual Environments for Teaching and Learning

Valentina Emilia Balas

George A. Tsihrintzis

Maria Virvou

Mika Sato-Ilic

Canicious Abeynayake

This book features research on the innovative applications of advanced computational intelligence paradigms. Coverage includes architectures of computational intelligence paradigms, knowledge discovery, pattern classification, and gene linkage analysis.

Innovative Applications

Computational Intelligence Paradigms

Vasile Palade

The two volumes LNAI 2773 and LNAI 2774 constitute the refereed proceedings of the 7th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2003, held in Oxford, UK in September 2003.The 390 revised papers and poster papers presented were carefully reviewed and selected from numerous submissions. Among the areas covered are knowledge-based systems, neural computing, fuzzy logic, uncertainty, machine learning, soft computing, agent systems, intelligent agents, data mining, knowledge discovery, hybrid intelligent systems, natural language processing, information retrieval, Web applications, case-based reasoning, evolutionary computing, signal processing, ontologies, decision making, human-computer interaction, intelligent user interfaces, neuroscience, intelligent agents, biocomputing, etc.

7th International Conference, KES 2003, Oxford, UK, September 3-5, 2003, Proceedings,

Knowledge-Based Intelligent Information and Engineering Systems 1.

Robert J. Howlett

Bogdan Gabrys

The three volume set LNAI 4251, LNAI 4252, and LNAI 4253 constitutes the refereed proceedings of the 10th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2006, held in Bournemouth, UK, in October 2006. The 480 revised papers presented were carefully reviewed and selected from about 1400 submissions. The papers present a wealth of original research results from the field of intelligent information processing.

10th International Conference, KES 2006, Bournemouth, UK, October 9-11 2006, Proceedings

Knowledge-Based Intelligent Information and Engineering Systems

Mircea Gh. Negoita

The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004.The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

8th International Conference, KES 2004, Wellington, New Zealand, September 20-25, 2004. Proceedings

Knowledge-Based Intelligent Information and Engineering Systems 2

The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

Annotation The three-volume set LNAI 3213, LNAI 3214, and LNAI 3215 constitutes the refereed proceedings of the 8th International Conference on Knowledge-Based Intelligent Information and Engineering Systems, KES 2004, held in Wellington, New Zealand in September 2004. The over 450 papers presented were carefully reviewed and selected from numerous submissions. The papers present a wealth of original research results from the field of intelligent information processing in the broadest sense; among the areas covered are artificial intelligence, computational intelligence, cognitive technologies, soft computing, data mining, knowledge processing, various new paradigms in biologically inspired computing, and applications in various domains like bioinformatics, finance, signal processing etc.

Knowledge-Based Intelligent Information and Engineering Systems 1

As new technological challenges are perpetually arising, Artificial Intelligence research interests are focusing on the incorporation of improvement abilities into machines in an effort to make them more efficient and more useful. Recent reports indicate that the demand for scientists with Artificial Intelligence skills significantly exceeds the market availability and that this shortage will intensify further in the years to come. A potential solution includes attracting more women into the field, as women currently make up only 26 percent of Artificial Intelligence positions in the workforce. The present book serves a dual purpose: On one hand, it sheds light on the very significant research led by women in areas of Artificial Intelligence, in hopes of inspiring other women to follow studies in the area and get involved in related research. On the other hand, it highlights the state-of-the-art and current research in selected Artificial Intelligence areas and applications. The book consists of an editorial note and an additional thirteen (13) chapters, all authored by invited women-researchers who work on various Artificial Intelligence areas and stand out for their significant research contributions. In more detail, the chapters in the book are organized into three parts, namely (i) Advances in Artificial Intelligence Paradigms, (ii) Advances in Artificial Intelligence Applications, and (iii) Recent Trends in Artificial Intelligence Areas and Applications. This research book is directed towards professors, researchers, scientists, engineers and students in Artificial Intelligence-related disciplines. It is also directed towards readers who come from other disciplines and are interested in becoming versed in some of the most recent Artificial Intelligence-based technologies. An extensive list of bibliographic references at the end of each chapter guides the readers to probe further into the Artificial Intelligence areas of interest to them.

World Outstanding Women in Artificial Intelligence

Advances in Selected Artificial Intelligence Areas

Neural networks represent a new generation of information processing paradigms designed to mimic-in a very limited sense-the human brain. They can learn, recall, and generalize from training data, and with their potential applications limited only by the imaginations of scientists and engineers, they are commanding tremendous popularity and research interest. Over the last four decades, researchers have reported a number of neural network paradigms, however, the newest of these have not appeared in book form-until now. Recent Advances in Artificial Neural Networks collects the latest neural network paradigms and reports on their promising new applications. World-renowned experts discuss the use of neural networks in pattern recognition, color induction, classification, cluster detection, and more. Application engineers, scientists, and research students from all disciplines with an interest in considering neural networks for solving real-world problems will find this collection useful.

Recent Advances in Artificial Neural Networks

E. Vonk

Ray P. Johnson

This book describes the application of evolutionary computation in the automatic generation of a neural network architecture. The architecture has a significant influence on the performance of the neural network. It is the usual practice to use trial and error to find a suitable neural network architecture for a given problem. The process of trial and error is not only time-consuming but may not generate an optimal network. The use of evolutionary computation is a step towards automation in neural network architecture generation.An overview of the field of evolutionary computation is presented, together with the biological background from which the field was inspired. The most commonly used approaches to a mathematical foundation of the field of genetic algorithms are given, as well as an overview of the hybridization between evolutionary computation and neural networks. Experiments on the implementation of automatic neural network generation using genetic programming and one using genetic algorithms are described, and the efficacy of genetic algorithms as a learning algorithm for a feedforward neural network is also investigated.

L. C. Jain

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