Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies (Premier Reference Source)

As the applications of data mining, the non-trivial extraction of implicit information in a data set, have expanded in recent years, so has the need for techniques that are tolerable to imprecision, uncertainty, and approximation. Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies is a compendium that addresses this need. It integrates contrasting techniques of conventional hard computing and soft computing to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low-cost solution. This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities, forming a foundation for the development of the field. Title ......Page 2 List of Reviewers......Page 5 Table of Contents......Page 7 Detailed Table of Contents......Page 11 Foreword......Page 20 Preface......Page 21 Introduction to the Experimental Design in the Data Mining Tool KEEL......Page 24 Cat Swarm Optimization Supported Data Mining......Page 49 Dynamic Discovery of Fuzzy Functional Dependencies Using Partitions......Page 67 An Intelligent Data Mining System Through Integration of Electromagnetism-Like Mechanism And Fuzzy Neural Network......Page 84 Computational Intelligence-Revisited......Page 108 Artificial Clonal Selection Model and Its Application......Page 123 Risk-Management Models Based on the PortfolioTheory Using Historical Data under Uncertainty......Page 146 Neuro-Fuzzy System Modeling......Page 170 Network Based Fusion of Global and Local Information in Time Series Prediction with The Use of Soft-Computing Techniques......Page 199 Weights Direct Determination of Feedforward Neural Networks without Iterative BP-Training......Page 220 The Hopfield-Tank Neural Network for the Mobile Agent Planning Problem......Page 249 A Novel Neural Fuzzy Network Using a Hybrid Evolutionary Learning Algorithm......Page 273 Power System Load Frequency Control Using Combined Intelligent Techniques......Page 297 Computational Intelligence Clustering for Dynamic Video Watermarking......Page 321 Data Mining Meets Internet and Web Performance......Page 342 Predicting Similarity of Web Services Using WordNet......Page 377 Finding Explicit and Implicit Knowledge: Biomedical Text Data Mining......Page 393 Rainstorm Forecasting By Mining Heterogeneous Remote Sensed Datasets......Page 410 Learning Verifiable Ensembles for Classification Problems with High Safety Requirements......Page 428 Compilation of References......Page 455 About the Contributors......Page 497 Index......Page 507

As the applications of data mining, the non-trivial extraction of implicit information in a data set, have expanded in recent years, so has the need for techniques that are tolerable to imprecision, uncertainty, and approximation.

Intelligent Soft Computation and Evolving Data Mining: Integrating Advanced Technologies is a compendium that addresses this need. It integrates contrasting techniques of conventional hard computing and soft computing to exploit the tolerance for imprecision, uncertainty, partial truth, and approximation to achieve tractability, robustness and low-cost solution. This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities, forming a foundation for the development of the field.

'This book provides a reference to researchers, practitioners, and students in both soft computing and data mining communities for generating creative ideas of securing and managing data mining'--Provided by publisher.