Overview
Explores computational intelligence techniques to perform software engineering tasks. It discusses techniques and case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, AI, time series forecasting models, etc.
This new volume explores the computational intelligence techniques necessary to carry out different software engineering tasks. Software undergoes various stages before deployment, such as requirements elicitation, software designing, software project planning, software coding, and software testing and maintenance. Every stage is bundled with a number of tasks or activities to be performed. Due to the large and complex nature of software, these tasks can become costly and error prone. This volume aims to help meet these challenges by presenting new research and practical applications in intelligent techniques in the field of software engineering.
Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.
Computational Intelligence Applications for Software Engineering Problems discusses techniques and presents case studies to solve engineering challenges using machine learning, deep learning, fuzzy-logic-based computation, statistical modeling, invasive weed meta-heuristic algorithms, artificial intelligence, the DevOps model, time series forecasting models, and more.
- | Author: Arun Prakash Agrawal, Vishal Jain, Parma Nand, Nitin Rakesh
- | Publisher: Apple Academic Press Inc.
- | Publication Date: Feb 10, 2023
- | Number of Pages:
- | Language:
- | Binding: Hardback
- | ISBN-13: 9781774910467
- | ISBN-10: 1774910462
