Soft Computing: Techniques in Engineering Sciences

About This Edited Volume

Engineering problems often involve uncertainty, imprecision, and complex interactions that resist traditional hard computing models. Soft computing offers a family of adaptive techniques—fuzzy logic, neural networks, evolutionary computing, and related statistical approaches—that tolerate such imprecision while still delivering useful solutions. This volume brings together contemporary research applying these methods to real-world engineering challenges.

Ten Focused Research Chapters

The collection is organized into ten contributed chapters, each addressing a distinct problem area:

• Neural network models for detecting and predicting freezing of gait in Parkinson’s disease
• A fuzzy de novo programming approach for optimal system design
• Probabilistic bilevel programming in Stackelberg games under fuzzy environments
• Intuitionistic fuzzy trigonometric distance and similarity measures
• Distributed activation energy modeling through transmutation of density functions
• Air quality forecasting using artificial neural networks and genetic programming
• Arithmetic operations on generalized semielliptic intuitionistic fuzzy numbers for multicriteria decision making
• An intuitionistic fuzzy assignment problem solved with a centroid ranking method
• Optimization of electric discharge machining using evolutionary computing and fuzzy MCDM
• Fuzzy reliability analysis of series, parallel, parallel–series, and series–parallel systems

Why Soft Computing Matters Here

Unlike conventional models that demand precise expressions and may struggle with incomplete data, soft computing methods learn from data, adapt to shifting conditions, and integrate multiple uncertainty-handling strategies. The studies in this volume show how these techniques can improve prediction, optimization, reliability evaluation, and decision-making across engineering domains.

Who Will Find It Useful

The editors have designed the book for scientists, engineers, managers, senior and postgraduate students, and research scholars. The mix of foundational concepts and applied case studies makes it suitable for readers who want to see how soft computing is deployed in practical engineering contexts.

About the Series

This is Volume 1 in the De Gruyter Series on the Applications of Mathematics in Engineering and Information Sciences. It is published open access, making the complete text freely available to readers worldwide under a Creative Commons license.