High-Performance Automation Methods for Computational Intelligent Systems Challenges, Opportunities, and Applications

High-Performance Automation Methods for Computational Intelligent Systems Challenges, Opportunities, and Applications by Vijay Kumar Sharma is a comprehensive exploration of intelligent computation, published by Taylor & Francis Group on September 17, 2025. This 374-page book is written in English and addresses the significant role of automation methods in enhancing the quality of life and developing efficient systems. It discusses the implementation of various theories and concepts aimed at solving complex societal problems through intelligent automation.
Readers will find a thorough examination of current trends in automation, including performance analysis and comparisons of machine learning techniques, energy-efficient hybrid algorithms, and applications of quantum cellular computing methods. The book also delves into cybersecurity strategies and the detection of leaf diseases using computational intelligence. Aimed primarily at senior undergraduates, graduate students, and academic researchers in electrical engineering, computer science, and related fields, this edition outlines a pathway for future developments in automated systems while identifying gaps in current methodologies.
Official synopsis Publisher
Intelligent computation is the need of the current society. This field attracts significant attention due to its application‑oriented systems. It is essential for implementing various society‑related solutions. Automation methods help improve the quality of life and support the development of efficient systems. The available theories and concepts are implemented for the benefit of society, drastically changing the world. The advancement of the existing ideas is simulated in the scenario of future intelligent automation systems. The complicated problems can be easily solved using the mentioned approaches. The decisive nature of the algorithms builds the system more intelligent. This book targets current trends in the relevant field and outlines a path for the development of future automated systems. The intelligence behaviour of the systems is the prime requirement for the age development. The gaps in the current development scenarios need to be identified and bridged by incorporating highly efficient algorithms, ideas, and working prototypes.
This book:
- Presents a comprehensive survey, performance analysis, and time complexity comparison of machine learning techniques in network security
- Discusses energy‑efficient hybrid algorithms for reconfiguration in radial distribution systems
- Covers a detailed examination of automation approaches for the study and detection of disparate leaf diseases using computational intelligent systems
- Illustrates applications of quantum cellular energy‑efficient computing methods for automation
- Explain cybersecurity strategies for advanced computational intelligence and customer segmentation through machine learning techniques
The book is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, computer science and engineering, and information technology.
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