Intelligent Techniques for Data Analysis in Diverse Settings

Intelligent Techniques for Data Analysis in Diverse Settings

Numan Celebi (Sakarya University, Turkey)
Release Date: April, 2016|Copyright: © 2016 |Pages: 353
ISBN13: 9781522500759|ISBN10: 1522500758|EISBN13: 9781522500766|DOI: 10.4018/978-1-5225-0075-9

Description

Data analysis forms the basis of many forms of research ranging from the scientific to the governmental. With the advent of machine intelligence and neural networks, extracting, modeling, and approaching data has been unimpeachably altered. These changes, seemingly small, affect the way societies organize themselves, deliver services, or interact with each other.

Intelligent Techniques for Data Analysis in Diverse Settings addresses the specialized requirements of data analysis in a comprehensive way. This title contains a comprehensive overview of the most innovative recent approaches borne from intelligent techniques such as neural networks, rough sets, fuzzy sets, and metaheuristics. Combining new data analysis technologies, applications, emerging trends, and case studies, this publication reviews the intelligent, technological, and organizational aspects of the field. This book is ideally designed for IT professionals and students, data analysis specialists, healthcare providers, and policy makers.

Topics Covered

The many academic areas covered in this publication include, but are not limited to:

  • Fuzzy Logic
  • Heuristic Algorithms
  • Information Systems
  • Knowledge Management
  • Legal Aspects
  • Neural Networks
  • Privacy issues
  • Rough Set
  • Statistical Analysis

Reviews and Testimonials

In this book, editor Numan Celebi presents readers with a collection of academic and professional contributions on the current specialized requirements of data analysis. The fifteen selections that make up the main body of the text are devoted to unified wavelet transform analysis adapted to different biomedical applications, image mining as techniques for feature extraction, a soft computing approach to customer segmentation, data mining for multicriteria single facility location problems, and many other related subjects.

– ProtoView Reviews

[...]. Fifteen chapters examine a variety of approaches to Intelligent Data Analysis (IDA), exploring such techniques and concepts as wavelet transform, heuristic and metaheuristic algorithms, grey modeling, image mining, fuzzy logic and much more. Some chapters showcase the practical applications of these methods. Chapter three, for example, explores the elements that affect housing demand in Turkey via grey theory, while chapter five tests several IDA methods in search of the optimal forecast of electrical loads. Applications in the healthcare, Internet, and financial sectors are also profiled in this volume, while the specific problems of shelf space management, signal processing, facility location, and supplier selection, among others, are addressed.
This volume definitely benefits from the inclusion of a preface, which works to establish the volume’s organization as well as its highly specialized mission. References are listed at the end of each chapter and compiled again at the end of the book, alongside brief contributor biographies and an index. IT professionals, educators, and students, in addition to data analysis specialists throughout a variety of fields, would be interested in this material.

– ARBA Staff Reviewer

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Numan Çelebi received his M.Sc.in electrical engineer from Istanbul Technical University, Turkey in 1989. He received his Ph.D. in Industrial Engineering from Sakarya University, Turkey, in 2004. He was in Auburn University, USA in 2009-2011 as a visiting scholar funded by TUBITAK, Turkey. His current research interest in in the area of data mining on rough set theory. In addition, Dr. Çelebi is interested in the area of metaheuristic algorithms and their applications in computer science.