{"product_id":"composite-artificial-intelligence-fundamentals-challenges-and-applications-hardback-9781394393039","title":"Composite Artificial Intelligence; Fundamentals, Challenges, and Applications (Hardback) 9781394393039","description":"\u003cfont face=\"Georgia\"\u003e\r\n\u003cp\u003e\u003cfont size=\"6\"\u003eComposite Artificial Intelligence\u003c\/font\u003e\u003cbr\u003e\r\n\u003cfont size=\"5\"\u003eFundamentals, Challenges, and Applications\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\u003cp\u003e\u003cfont size=\"4\"\u003eT. S. Arun Samuel (Edited by), Arun Samuel (Author), L. Jerart Julus (Edited by), P. Kanimozhi (Edited by), T. Ananth Kumar (Edited by), S. Balamurugan (Edited by)\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e9781394393039, Wiley\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eHardback, published 29 June 2026\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e400 pages\u003cbr\u003e22.9 x 15.2 x 2.5 cm, 0.671 kg\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\r\n\r\n\r\n\u003cp align=\"justify\"\u003e\u003cstrong\u003e\u003cfont size=\"3\"\u003e\u003cp\u003e\u003cb\u003eUnlock the full potential of context-aware AI while navigating critical hurdles like bias mitigation and ethical governance with this definitive resource on the future of composite artificial intelligence.\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eIn the rapidly evolving landscape of artificial intelligence, the demand for more adaptive, intelligent, and context-aware systems has led to the emergence of composite artificial intelligence: a paradigm that integrates multiple AI techniques to solve complex real-world problems with higher efficiency and intelligence. This book is a groundbreaking exploration of the next evolution in AI, where diverse methodologies like machine learning, symbolic reasoning, and cognitive computing converge to solve complex, real-world problems with unprecedented intelligence and adaptability. Unlike traditional AI approaches that rely on singular techniques, composite AI harnesses the strengths of multiple paradigms, enabling systems that are more robust, interpretable, and capable of human-like decision-making. This book provides a comprehensive roadmap for understanding and implementing these advanced systems, from foundational theories to cutting-edge applications across industries such as healthcare, finance, and smart manufacturing. It delves into critical challenges, including bias mitigation, integration hurdles, and ethical governance, while showcasing real-world case studies that demonstrate the transformative potential of composite AI. With its balanced blend of theory, technical depth, and actionable insights, this book is a definitive resource for unlocking the full potential of AI in an increasingly complex world. \u003c\/p\u003e\n\u003cp\u003eReaders will find the volume: \u003c\/p\u003e\n\u003cul\u003e\n\u003cli\u003e Explores the intersection of machine learning, symbolic reasoning, and cognitive computing for solving real-world challenges smarter and faster;\u003c\/li\u003e \u003cli\u003e Introduces cutting-edge techniques for bias reduction, optimization, and seamless multi-method integration;\u003c\/li\u003e \u003cli\u003e Provides real-world case studies and scalable frameworks to demonstrate how composite AI is transforming industries; \u003c\/li\u003e \u003cli\u003e Presents ethical implications and current innovations to build trustworthy, compliant AI systems that align with regulations; \u003c\/li\u003e \u003c\/ul\u003e\n\u003cp\u003e\u003cb\u003eAudience\u003c\/b\u003e \u003c\/p\u003e\n\u003cp\u003eAcademics, policymakers, AI researchers, data scientists, AI and machine learning engineers and developers, and??industry professionals working in healthcare, finance, manufacturing, and cybersecurity who need robust, explainable, and adaptive AI solutions.\u003c\/p\u003e\u003c\/font\u003e\u003c\/strong\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003e\u003cp\u003eSeries Preface xv\u003cbr\u003ePreface xvii\u003cbr\u003eAcknowledgement xix\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart I: Foundational Concepts and Emerging Trends in Composite AI 1\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e1 Data Fusion Techniques in Composite AI 3\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eS. Sowmyayani, D. Dhanya, J. Kavitha and R. Roselinkiruba\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e1.1 Introduction 1\u003cbr\u003e1.2 Data Fusion Techniques in Composite AI 3\u003cbr\u003e1.4 Proposed Methodology Using Composite AI 12\u003cbr\u003e1.5 Experimental Results 17\u003cbr\u003e1.6 Conclusion 26\u003c\/p\u003e \u003cp\u003e\u003cb\u003e2 Composite AI in Natural Language Processing: A Paradigm Shift in Understanding and Generating Human Language 33\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eNarendran M., M. Beema Meharaj, D. Diana Julie, Sowmya Banala, G. Umadevi and A. Devi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e2.1 Introduction to Composite Artificial Intelligence (AI) 34\u003cbr\u003e2.2 Role of Composite AI in NLP 37\u003cbr\u003e2.3 Fundamental Elements of NLP Composite AI 42\u003cbr\u003e2.4 Case Studies and Use Cases of Composite AI in NLP 49\u003cbr\u003e2.5 Challenges and Future Directions 60\u003cbr\u003e2.6 Conclusion 62\u003c\/p\u003e \u003cp\u003e\u003cb\u003e3 A Composite Artificial Intelligence Framework for Enhanced and Intelligent Word Recognition of Handwritten Hindi 65\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eR. S. Rampriya, Sabarinathan, SahayaBeni Prathiba, C. Renit, R. Arumuga Arun and S. Bhuvana\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e3.1 Introduction 66\u003cbr\u003e3.2 Related Work 68\u003cbr\u003e3.3 Proposed Methodology 69\u003cbr\u003e3.4 Experimental Result and Analysis 75\u003cbr\u003e3.5 Conclusion 81\u003c\/p\u003e \u003cp\u003e\u003cb\u003e4 Machine Learning-Driven Optimization for Composite AI in Wireless Body Area Networks (WBAN) 85\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eKrishna Kumar M., Pricilla Mary S., James Nesaratnam R. and Sharon Geege A.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e4.1 Prelude 86\u003cbr\u003e4.2 Architectural Framework of WBAN Integrated with Composite AI 87\u003cbr\u003e4.3 Machine Learning Models for WBAN Optimization 89\u003cbr\u003e4.4 Deep Learning for Signal Processing in WBAN 91\u003cbr\u003e4.5 Security Challenges and AI-Based Solutions in WBAN 92\u003cbr\u003e4.6 AI-Driven Antenna Optimization in WBANs 94\u003cbr\u003e4.7 Conclusion and Research Trajectories 97\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart II: Advanced Methods and Technical Challenges in Composite AI 101\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e5 AI-Driven Hybrid Ant Colony and Golden Jackal Optimization Algorithm for Lung Disease Prediction and Classification 103\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eKarthikeyan A., Pradeep S., Boorneush M. and Dhivya P.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e5.1 Introduction 104\u003cbr\u003e5.2 Literature Survey 106\u003cbr\u003e5.3 System Design 109\u003cbr\u003e5.4 Results and Discussion 114\u003cbr\u003e5.5 Conclusion 120\u003cbr\u003e5.6 Future Scope 121\u003c\/p\u003e \u003cp\u003e\u003cb\u003e6 Removing Bias in Maritime Imagery: Advancing Gender Equality through Data-Driven Methods 125\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eJordan Taylor and J. Padmapriya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e6.1 Introduction 126\u003cbr\u003e6.2 Literature Review 129\u003cbr\u003e6.3 Methodology 134\u003cbr\u003e6.4 Results and Discussion 143\u003cbr\u003e6.5 Conclusion 146\u003c\/p\u003e \u003cp\u003e\u003cb\u003e7 Text-Based Analysis of Twitter Data with Machine Learning Models 151\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eN. Malathy, G. Sharmila, R. Yuvarshini and R. Lavanya\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e7.1 Introduction 152\u003cbr\u003e7.2 Objective 157\u003cbr\u003e7.3 Classification of Tweets 158\u003cbr\u003e7.4 Evaluation Metrics 172\u003cbr\u003e7.5 Conclusion and Future Work 175\u003c\/p\u003e \u003cp\u003e\u003cb\u003e8 Fingerprint Registration and Matching Based on Improved Convolutional Neural Network 181\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eLakshmanan B., Selvakumar B., Kasthuri K., Nivashini S. and Swetha R.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e8.1 Introduction 182\u003cbr\u003e8.2 Related Works 182\u003cbr\u003e8.3 Dataset Description 185\u003cbr\u003e8.4 Proposed Work 185\u003cbr\u003e8.5 Results and Discussion 191\u003cbr\u003e8.6 Conclusion 195\u003c\/p\u003e \u003cp\u003e\u003cb\u003ePart III: Real-World Applications of Composite AI in Healthcare and Beyond 199\u003c\/b\u003e\u003c\/p\u003e \u003cp\u003e\u003cb\u003e9 A Novel Transfer Learning-Based Composite AI Model for Skin Disease Classification 201\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eR. Karthick Manoj and S. Aasha Nandhini\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e9.1 Introduction 202\u003cbr\u003e9.2 Literature Survey 203\u003cbr\u003e9.3 Proposed Methodology 208\u003cbr\u003e9.4 Result and Discussion 213\u003cbr\u003e9.5 Conclusion 218\u003c\/p\u003e \u003cp\u003e\u003cb\u003e10 Composite AI-Driven Music Recommendation: Integrating Emotion, Aural Analysis and Song Similarity 223\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eAyushmaan Das and Rajalakshmi Shenbaga Moorthy\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e10.1 Introduction 224\u003cbr\u003e10.2 Literature Survey 228\u003cbr\u003e10.3 Proposed Composite AI-Driven Music Recommendation Engine 232\u003cbr\u003e10.4 Results and Discussions 239\u003cbr\u003e10.5 Conclusion 244\u003c\/p\u003e \u003cp\u003e\u003cb\u003e11 A Composite Artificial Intelligence Based Framework for Heart Disease Prediction 249\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eM. Suresh, M. S. Anbarasi, R. Rajmohan and A. Anbarasi\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e11.1 Introduction 250\u003cbr\u003e11.2 Smart Health Monitoring Systems 254\u003cbr\u003e11.3 Materials and Methods 257\u003cbr\u003e11.4 Results and Discussions 270\u003cbr\u003e11.5 Conclusions 275\u003c\/p\u003e \u003cp\u003e\u003cb\u003e12 Composite AI for Predictive Analysis of Autism Spectrum Disorder Using Facial Features 279\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eS. Usharani, A. Ganesh, N. Muralidharan and G. Glorindal\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e12.1 Introduction 280\u003cbr\u003e12.2 Related Work 280\u003cbr\u003e12.3 Overview of Composite AI in Predictive Analysis 284\u003cbr\u003e12.4 Proposed Methodology 285\u003cbr\u003e12.5 Experimental Setup 291\u003cbr\u003e12.6 Results and Outputs 295\u003cbr\u003e12.7 Conclusion 296\u003c\/p\u003e \u003cp\u003e\u003cb\u003e13 Integrating Imaging and Genomic Data with Composite AI to Enhance Breast Cancer Diagnosis and Early Detection 303\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eP. Manju Bala, S. Usharani, A. Balachandar, Sunday Adeola Ajagbe and Matthew Olusegun Adigun\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e13.1 Introduction 304\u003cbr\u003e13.2 Materials and Methods 307\u003cbr\u003e13.3 Model Training and Evaluation 313\u003cbr\u003e13.4 Evaluation Results 314\u003cbr\u003e13.5 Conclusion 319\u003c\/p\u003e \u003cp\u003e\u003cb\u003e14 Cognitive Analytics AI for Predictive Diagnostics and Neurological Forecasting in Brain Tumor Management 325\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eS. Usharani, P. Manju Bala, A. Balachandar and Olukayode A.\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e14.1 Introduction 326\u003cbr\u003e14.2 Related Works 327\u003cbr\u003e14.3 Proposed Predictive Analytics Framework for Predicting Brain Tumors and Neurological Disorders 331\u003cbr\u003e14.4 Experimental Setup for Predictive Analytics in Prediction of Brain Tumor and Neurological Disorder 334\u003cbr\u003e14.5 Results and Analysis 340\u003cbr\u003e14.6 Conclusion 341\u003c\/p\u003e \u003cp\u003e\u003cb\u003e15 Applications for Composite AI in Healthcare 345\u003c\/b\u003e\u003cbr\u003e\u003ci\u003eR. Vijayarajeswari, David Samuel Azariya S., Anto Lourdu Xavier Raj Arockia Selvarathinam, Priyabrata Thatoi, Abhinaya Saravanan and Nisha Soms\u003c\/i\u003e\u003c\/p\u003e \u003cp\u003e15.1 Introduction 346\u003cbr\u003e15.2 Fundamentals of Composite AI 347\u003cbr\u003e15.3 Applications for Composite AI in Healthcare 351\u003cbr\u003e15.4 Case Studies in Composite AI Applications in Healthcare 356\u003cbr\u003e15.5 Challenges and Future Directions 357\u003cbr\u003e15.6 Conclusion 362\u003c\/p\u003e \u003cp\u003eReferences 364\u003cbr\u003eIndex 367\u003c\/p\u003e\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\u003cp\u003e\u003cfont size=\"3\"\u003eSubject Areas: Computer science [\u003ca title=\"See our other books on Computer science\" href=\"https:\/\/freshlyprintedbooks.co.uk\/search?q=%22Computer%20science%20%5BUY%5D%22\"\u003eUY\u003c\/a\u003e]\u003c\/font\u003e\u003c\/p\u003e\r\n\r\n\r\n\u003c\/font\u003e","brand":"Wiley-Scrivener","offers":[{"title":"Brand New","offer_id":52433832902936,"sku":"9781394393039","price":154.59,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0730\/2037\/5320\/files\/9781394393039.jpg?v=1784854807","url":"https:\/\/freshlyprintedbooks.co.uk\/products\/composite-artificial-intelligence-fundamentals-challenges-and-applications-hardback-9781394393039","provider":"Freshly Printed Books","version":"1.0","type":"link"}