Bio-Inspired Data Mining

Abstract

Bio-Inspired Approaches in Sequence and Data Streams.- Adaptive and Self-adaptive Techniques for Evolutionary Forecasting Applications Set in Dynamic and Uncertain Environments.- Sequence Pattern Mining.- Growing Self-Organizing Map for Online Continuous Clustering.- Synthesis of Spatio-temporal Models by the Evolution of Non-uniform Cellular Automata.- Bio-Inspired Approaches in Classification Problem.- Genetic Selection Algorithm and Cloning for Data Mining with GMDH Method.- Inducing Relational Fuzzy Classification Rules by Means of Cooperative Coevolution.- Post-processing Evolved Decision Trees.- Evolutionary Fuzzy and Swarm in Clustering Problems.- Evolutionary Fuzzy Clustering: An Overview and Efficiency Issues.- Stability-Based Model Order Selection for Clustering Using Multiple Cooperative Particle Swarms.- Genetic and Evolutionary Algorithms in Bioinformatics.- Data-Mining Protein Structure by Clustering, Segmentation and Evolutionary Algorithms.- A Clustering Genetic Algorithm for Genomic Data Mining.- Detection of Remote Protein Homologs Using Social Programming.- Bio-Inspired Approaches in Information Retrieval and Visualization.- Optimizing Information Retrieval Using Evolutionary Algorithms and Fuzzy Inference System.- Web Data Clustering.- Efficient Construction of Image Feature Extraction Programs by Using Linear Genetic Programming with Fitness Retrieval and Intermediate-Result Caching.- Mining Network Traffic Data for Attacks through MOVICAB-IDS.