eBook Biologically-Inspired Techniques for Knowledge Discovery and Data Mining, 1st Edition

  • Shafiq Alam
  • Published By:
  • ISBN-10: 1466660791
  • ISBN-13: 9781466660793
  • DDC: 006.3
  • Grade Level Range: College Freshman - College Senior
  • 311 Pages | eBook
  • Original Copyright 2014 | Published/Released December 2015
  • This publication's content originally published in print form: 2014
  • Price:  Sign in for price

About

Overview

Biologically-inspired data mining has a wide variety of applications in areas such as data clustering, classification, sequential pattern mining, and information extraction in healthcare and bioinformatics. Over the past decade, research materials in this area have dramatically increased, providing clear evidence of the popularity of these techniques. Biologically-Inspired Techniques for Knowledge Discovery and Data Mining exemplifies prestigious research and shares the practices that have allowed these areas to grow and flourish. This essential reference publication highlights contemporary findings in the area of biologically-inspired techniques in data mining domains and their implementation in real-life problems. Providing quality work from established researchers, this publication serves to extend existing knowledge within the research communities of data mining and knowledge discovery, as well as for academicians and students in the field.

Table of Contents

Front Cover._x000D_
Title Page._x000D_
Copyright Page._x000D_
Advances in Data Mining and Database Management (ADMDM) Book Series._x000D_
Titles in This Series._x000D_
Other Frontmatter._x000D_
Table of Contents._x000D_
Detailed Table of Contents._x000D_
Foreword._x000D_
Preface._x000D_
1: Biologically Inspired Techniques for Data Mining: A Brief Overview of Particle Swarm Optimization for KDD._x000D_
2: Probabilistic Control and Swarm Dynamics in Mobile Robots and Ants._x000D_
3: A Measure Optimized Cost-Sensitive Learning Framework for Imbalanced Data._x000D_
4: Towards an Improved Ensemble Learning Model of Artificial Neural Networks: Lessons Learned on Using Randomized Numbers of Hidden Neurons._x000D_
5: Ant Programming Algorithms for Classification._x000D_
6: Machine Fault Diagnosis and Prognosis using Self-Organizing Map._x000D_
7: An Enhanced Artificial Bee Colony Optimizer for Predictive Analysis of Heating Oil Prices using Least Squares Support Vector Machines._x000D_
8: Comparison of Linguistic Summaries and Fuzzy Functional Dependencies Related to Data Mining._x000D_
9: Application of Artificial Neural Network and Genetic Programming in Civil Engineering._x000D_
10: A Promising Direction towards Automatic Construction of Relevance Measures._x000D_
11: Adaptive Scheduling for Real Time Distributed Systems._x000D_
12: Discovery of Emergent Sorting Behavior using Swarm Intelligence and Grid-Enabled Genetic Algorithms._x000D_
13: Application of Biologically Inspired Techniques for Industrial and Environmental Research via Air Quality Monitoring Network._x000D_
14: Online Prediction of Blood Glucose Levels using Genetic Algorithm._x000D_
15: Security of Wireless Devices using Biological-Inspired RF Fingerprinting Technique._x000D_
Compilation of References._x000D_
About the Contributors._x000D_
Index._x000D_