Soft computing in artificial intelligence [electronic resource] / Young Im Cho, Dongham Kim, Eric T. Matson, editors.
Cho, Young Im.; Kim, Dongham.; Matson, Eric T.
2014
QA76.76.E95
Available Online

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Title Soft computing in artificial intelligence [electronic resource] / Young Im Cho, Dongham Kim, Eric T. Matson, editors.
ISBN 9783319055152 electronic book
3319055151 electronic book
9783319055145
DOI https://doi.org/10.1007/978-3-319-05515-2
Published Cham ; New York : Springer, [2014]
Language English
Description 1 online resource.
Item Number 10.1007/978-3-319-05515-2 doi
Call Number QA76.76.E95
Dewey Decimal Classification 006.33
Summary 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 c-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.
Bibliography, etc. Note Includes bibliographical references.
Access Note Access limited to authorized users.
Source of Description Description based on online resource; title from PDF title page (viewed Apr. 7, 2014).
Added Author Cho, Young Im.
Kim, Dongham.
Matson, Eric T.
Series Advances in intelligent systems and computing ; v. 270.
Available in Other Form Print version: 9783319055145
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All Resources
Fuzzy (r, s)-minimal preopen sets and fuzzy (r, s)-M precontinuous mappings on (r, s)-fuzzy minimal spaces
On fuzzy (r, s)-minimal c-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.

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