Soft Computing in Artificial Intelligence by Young Im ChoSoft Computing in Artificial Intelligence by Young Im Cho

Soft Computing in Artificial Intelligence

byYoung Im ChoEditorDonghan Kim, Eric T. Matson

Paperback | March 19, 2014

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This book explores the concept of artificial intelligence based on knowledge-based algorithms. Given the current hardware and software technologies and artificial intelligence theories, we can think of how efficient to provide a solution, how best to implement a model and how successful to achieve it. This edition provides readers with the most recent progress and novel solutions in artificial intelligence. This book aims at presenting the research results and solutions of applications in relevance with artificial intelligence technologies. We propose to researchers and practitioners some methods to advance the intelligent systems and apply artificial intelligence to specific or general purpose. This book consists of 13 contributions that feature fuzzy (r, s)-minimal pre- and β-open sets, handling big coocurrence matrices, Xie-Beni-type fuzzy cluster validation, fuzzy c-regression models, combination of genetic algorithm and ant colony optimization, building expert system, fuzzy logic and neural network, individual role adaptation for team sports, application of polynomial neural networks, recursive neuro-fuzzy algorithm for water management, application of interactive genetic algorithm, and Artificial Neural Network (ANN) model. This edition is published in original, peer reviewed contributions covering from initial design to final prototypes and verification.

Title:Soft Computing in Artificial IntelligenceFormat:PaperbackDimensions:153 pagesPublished:March 19, 2014Publisher:Springer-Verlag/Sci-Tech/TradeLanguage:English

The following ISBNs are associated with this title:

ISBN - 10:3319055143

ISBN - 13:9783319055145

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Table of Contents

Fuzzy (r, s)-minimal preopen sets and fuzzy (r, s)-M precontinuous mappings on (r, s)-fuzzy minimal spaces.-

On fuzzy (r, s)-minimal β-open sets on (r, s)-fuzzy minimal spaces.-

Handling Very Large Cooccurrence Matrices in Fuzzy Co-clustering by Sampling Approaches.-

Fuzzy c-Regression Models Based on Optimal Scaling of Categorical Observation with Tolerance.-

Building a Knowledge Base for Expert System in Information Security.-

Fuzzy logic and neural network based induction control in a diesel engine.-

Evaluation and Analysis of Relationship
and Individual Role Adaptation for
Team Sports using SOM.-

Recursive Neuro-Fuzzy Algorithm for Flow Prediction and Pump On-Off Minimization .-

Logotype Design Support System Based on Sketches.-

An Artificial Neural Network Based on the Architecture of the Cerebellum for Behavior Learning.