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Intelligent Systems : Emerging Trends and Challenges in Deep Neuro-Fuzzy Models and Explainable Artificial Intelligence

Intelligent Systems : Emerging Trends and Challenges in Deep Neuro-Fuzzy Models and Explainable Artificial Intelligence (Hardcover)

Siddhartha Roy, Agostino Cortesi, Soumya Sen (엮은이)
CRC Press
402,020원

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Intelligent Systems : Emerging Trends and Challenges in Deep Neuro-Fuzzy Models and Explainable Artificial Intelligence
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책 정보

· 제목 : Intelligent Systems : Emerging Trends and Challenges in Deep Neuro-Fuzzy Models and Explainable Artificial Intelligence (Hardcover) 
· 분류 : 외국도서 > 기술공학 > 기술공학 > 전력자원 > 전기 에너지
· ISBN : 9781032889085
· 쪽수 : 394쪽
· 출판일 : 2026-02-25

목차

Chapter 0. Front Matter.? ?Section I. Foundations of Machine Learning and Intelligent Systems. Chapter 1. Engineering Students Employability for Campus Placement: A State-of-the-Art Survey Using Machine Learning-Based Approaches. Chapter 2. Enhancing E-commerce Sales Prediction: Overcoming Data and Complexity Challenges with LSTM Models. Chapter 3. A Review: How to Employ Generative AI to Build Informative Recommendation Systems.? Section II. Computational Intelligence, Optimization, and Cybersecurity. Chapter 4. Applications of Computational Intelligence. Chapter 5. Optimizing and Improving the Quality of Mined Association Rules Using a Hybrid Genetic Algorithm and Grey Wolf Algorithm.? Chapter 6. Critical Role of Artificial Intelligence in Cybersecurity in the Digital Era.? ?Section III. AI Applications in Business, IoT, and Human Behavior. Chapter 7. Gender Dynamics in AI-Driven Online Fashion Purchases: An Impulse Buying Analysis. Chapter 8. Machine Learning Algorithms Enable Data-Driven Decision-Making by Internet of Things Devices.? ?Section IV. AI in Healthcare and Bioinformatics.? Chapter 9. Applications of Machine Learning for Cardiovascular Diseases Prediction.? Chapter 10. Comparative Performance Analysis of Machine Learning and Hardware Techniques for DNA Sequence Alignment.? Chapter 11. Biological Sequence Alignment Using Burrows-Wheeler Transformation: An Implementation Roadmap.? Chapter 12. Early Detection of Parkinson's Disease Using Machine Learning and Deep Learning Techniques: A Multimodal Analysis of Voice and Spiral Image Data.? ?Section V. Networking, Cloud, and Steganography.? Chapter 13. Machine Learning for Networking and Cybersecurity.? Chapter 14. AI-Driven Predictive Analytics for Multi-Cloud Management.? ?Chapter 15. Local Feature-Based Steganographic Scheme Using Chaos Theory and Arnold Scrambling.? Chapter 16. The Convergence of Artificial Intelligence and 5G/6G Networks: Challenges, Recent Advancements, and Future Trends.? ?Section VI. Defense, Emotion Recognition, and Explainable AI.? Chapter 17. Vidya Cipher: Revolutionizing Financial Security with Cryptographic Intelligence. Chapter 18. Army Vehicle Detection Using YOLO-v7, YOLO-v8, and YOLO-v9.? Chapter 19. Emotion Detection and Anomaly Recognition in Crowds: Spotting Suspicious Behaviour. Chapter 20. Explainable AI: Bridging the Gap Between Machine Learning and Interpretability Potential in Humans.? ?Section VII. Real-Time Systems and Agriculture. Chapter 21. Emergency Medical System Based on Users’ Real-Time Location. Chapter 22. A Perspective Analysis of Agricultural Yield Prediction with Advanced AI and Intelligent Systems.

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