Optimized Genetic Programming Applications: Emerging Research and Opportunities

Optimized Genetic Programming Applications: Emerging Research and Opportunities

Bahrudin Hrnjica (University of Bihac, Bosnia and Herzegovina) and Ali Danandeh Mehr (Antalya Bilim University, Turkey)
Release Date: July, 2018|Copyright: © 2019 |Pages: 310
ISBN13: 9781522560050|ISBN10: 152256005X|EISBN13: 9781522560067|DOI: 10.4018/978-1-5225-6005-0

Description

Data is more valuable than ever in the twenty-first century, and tremendous amounts of data are being generated every second. With a fast-growing information industry, engineers are required to develop new tools and techniques that increase human capabilities of mining useful knowledge from the vast amounts of data.

Optimized Genetic Programming Applications: Emerging Research and Opportunities is an essential reference source that explores the concept of genetic programming and its role in managing engineering problems. It also examines genetic programming as a supervised machine learning technique, focusing on implementation and application. As a resource that details both the theoretical aspects and implementation of genetic programming, this book is a useful source for academicians, biological engineers, computer programmers, scientists, researchers, and upper-level students seeking the latest research on genetic programming.

Topics Covered

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

  • Fitness Function
  • Fracture Mechanics
  • Gene Expression Programming
  • Initialization Method
  • Multiclass Classification
  • Multigene Genetic Programming
  • Parallel Implementation
  • Supervised Machine Learning
  • Training Data
  • Visual Studio Code

Table of Contents and List of Contributors

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Author(s)/Editor(s) Biography

Bahrudin Hrnjica holds a Ph.D. in Mechanical Engineering from University in Bihac. Currently, he is assistant professor at the University, teaching students in fields of numerical analysis, mathematical modelling and machine learning. Beside teaching, he is in software industry for many years, working on custom solutions based on Microsoft development technologies e.g. .NET, .NET Core and Visual Studio, developing Mobile/Desktop/Web/Cloud solutions. As an expert in development technologies, Microsoft recognized him as a Most Valuable Professional (Microsoft MVP) first time in 2011. He is an author of several books, many online articles, opensource projects, as well as speaker on many local and regional conferences, code camps, workshops etc. His current research is development and application of evolutionary algorithms and deep learning in various engineering fields.
Ali Danandeh Mehr holds a Ph.D. in Civil Engineering from Istanbul Technical University (ITU). Currently, he is an assistant professor at Civil Engineering Department of Antalya Bilim University (ABU), Turkey. Prior to joining ABU, he worked as vice chair of Civil Engineering Department at Near East University. Dr. Danandeh mehr has also worked as an academic member and postdoctoral research fellow at ITU-TRNC Campuses and University of Tabriz, respectively. He has published several refereed publications and collaborated as subject editor/reviewer for different international scholarly journals. His current research focuses on the hydroinformatics and developing evolutionary algorithms to solve different problems in water resources systems.