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