Dynamic Fuzzy Pattern Recognition with Applications to Finance and Engineering

Contents......Page 3
Figures......Page 7
Tables......Page 12
Foreword......Page 14
1 Introduction......Page 16
Goals & Tasks of the Book......Page 17
Structure of the Book......Page 19
Knowledge Discovery Process......Page 21
Problem of Pattern Recognition......Page 25
Problem of DPR......Page 34
Monitoring Process......Page 51
Adaptation Process......Page 71
4 Dynamic Fuzzy Classifier Design with Point-Prototype based Clustering Algorithms......Page 92
Formulation of Dynamic Clustering......Page 93
Requirements for Clustering Algorithm used for Dynamic Clustering & Classification......Page 99
Detection of New Clusters......Page 101
Merging of Clusters......Page 113
Splitting of Clusters......Page 131
Detection of Gradual Changes in Cluster Structure......Page 145
Adaptation Procedure......Page 146
Updating Template Set of Objects......Page 149
Cluster Validity Measures for Dynamic Classifiers......Page 156
Summary of Algorithm for Dynamic Fuzzy Classifier Design & Classification......Page 164
5 Similarity Concepts for Dynamic Objects in Pattern Recognition......Page 167
Extraction of Characteristic Values from Trajectories......Page 169
Similarity Notion for Trajectories......Page 172
Extension of Fuzzy Pattern Recognition Methods by Similarity Measures for Trajectories......Page 209
Bank Customer Segmentation based on Customer Behaviour......Page 211
Computer Network Optimisation based on Dynamic Network Load Classification......Page 245
7 Conclusions......Page 276
Refs......Page 279
Unsupervised Optimal Fuzzy Clustering Algorithm of Gath & Geva......Page 288
Description of implemented Software......Page 291
Index......Page 294