Издательство Springer, 2014, -157 pp.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 preand 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 neurofuzzy 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 verifications.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 CooccurrenceMatrices in Fuzzy Co-clustering by Sampling Approaches
Xie-Beni-Type Fuzzy Cluster Validation in Fuzzy Co-clustering of Documents and Keywords
Fuzzy c-Regression Models Based on Optimal Scaling of Categorical Observation with Tolerance
Combination of Genetic Algorithm and Ant Colony Optimization for QoS Multicast Routing
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 between Roles and Individual’s Role Adaptation in Team Sports Using SOM: Data Analysis and Introduction of Theory
Design of Radial Basis Function Classifier Based on Polynomial Neural Networks
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

Издательство Springer, 2014, -157 pp.本书探讨了基于知识的算法的人工智能概念。鉴于目前的硬件和软件技术以及人工智能理论，我们可以思考如何高效地提供解决方案，如何最好地实现一个模型，以及如何成功地实现它。本版为读者提供了人工智能的最新进展和新颖的解决方案。本书旨在介绍与人工智能技术相关的研究结果和应用解决方案。我们向研究人员和从业人员提出了一些推进智能系统的方法，并将人工智能应用于特定或一般目的。本书由13篇论文组成，主要内容包括：模糊（r，s）-最小前和β-开放集、处理大共现矩阵、Xie-Beni型模糊聚类验证、模糊C-回归模型、遗传算法和蚁群优化相结合、建立专家系统。模糊逻辑和神经网络、团队运动的个人角色适应、多项式神经网络的应用、水管理的递归神经模糊算法、交互式遗传算法的应用以及人工神经网络（ANN）模型。本版以原创、同行评审的稿件形式出版，涵盖了从最初的设计到最终的原型和验证。模糊(r,s)-最小预开集和(r,s)-模糊最小空间上的模糊(r,s)-M预连续贴图

(r,s)-模糊最小空间上的模糊(r,s)-最小β-开放集

用抽样方法处理模糊协同聚类中的大共现矩阵

文件和关键词模糊聚类中的谢贝尼式模糊聚类验证

基于容许度的分类观察的最佳比例的模糊C-回归模型

遗传算法与蚁群优化相结合的QoS多播路由研究

为信息安全专家系统建立知识库

基于模糊逻辑和神经网络的柴油机诱导控制

利用SOM评价和分析团队运动中角色与个人角色适应之间的关系：数据分析和理论介绍

基于多项式神经网络的径向基函数分类器的设计

用于流量预测和泵开停最小化的递归神经模糊算法

基于草图的标识设计支持系统

基于小脑结构的行为学习的人工神经网络