High-Performance Automation Methods for Computational Intelligent Systems : Challenges, Opportunities, and Applications (Computational Intelligence in Signal Processing and Automation)

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High-Performance Automation Methods for Computational Intelligent Systems : Challenges, Opportunities, and Applications (Computational Intelligence in Signal Processing and Automation)

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  • 製本 Hardcover:ハードカバー版/ページ数 384 p.
  • 言語 ENG
  • 商品コード 9781032908106

Full Description

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 soci-ety, drastically changing the world. The advancement of the existing ideas is simulated in the scenario of future intelligent automation systems. The com-plicated problems can be easily solved using the mentioned approaches. The decisive nature of the algorithms builds the system more intelligent. This book proposal 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 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.

It 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.

Contents

1. Cybersecurity for the intelligent computational systems - Internet of Drones. 2. A Comprehensive Survey of Artificial Intelligence in Cybersecurity. 3. High Performance Self- Bias Transistor Multipliers for Computing Applications. 4. Multi-Tasking Bot for Customized Automation: Social Networking and Knowledge Transfer for IR 4.0 and Knowledge Management. 5. Integrated Computational Intelligence Models to Ensure Food Security Withstanding Climate Change. 6. A Comprehensive Review of Hybrid Variants of Artificial Bee Colony Algorithm. 7. Development of Various Current Genetic Algorithms. 8. Integration of Cyber Security and Intelligent Computational Systems. 9. Deciphering Parkinson's: A Thorough Review of Techniques for Illness Identification and Prevention. 10. Future prospects of natural language processing. 11. Prospects and Trends in the Future of natural language processing. 12. Detection of Moving Objects and Elimination of Shadows from Color Video. 13. Emotion Recognition from Facial Expression Using Deep Learning Technique. 14. Nanotechnology in Agriculture.

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