Keywords
Machine Learning applications,Artificial Intelligence in healthcare,Deep learning research papers,AI-based disease prediction,Solar power forecasting using LSTM,IoT cybersecurity and botnet detection,Skin disease detection using AI,Cardiac disease prediction models,AI in newable energy systems,Smart healthcare analytics,Deep learning in medical diagnosis,Predictive nalytics in healthcare,AI for crop disease detection,Sleep disorder classification using machine learning,Edge AI in cybersecurity,Hybrid deep learning models,AI in education and student retention,Computer vision in medical imaging,Data-driven health risk prediction,Intelligent systems and machine learning researchArtificial Intelligence and Machine Learning Methods for Engineering Systems: Forecasting and Mathematical Insights
edited by: Nirmal Kumar Pandey,Vatsala Anand & Rupendra Kumar PachauriLength: 22.9 mm | Breadth: 14.25 mm | Height: 1.550 mm | Imprint: NIPA | Weight: GMS
This book will be available from 05-Aug-2026
This book presents a comprehensive exploration of advanced Artificial Intelligence and Machine Learning applications across diverse real-world domains. It brings together cutting-edge research in healthcare, renewable energy, cybersecurity, agriculture, and human behavior analytics, demonstrating how intelligent systems are transforming modern society. The volume covers deep learning architectures, predictive modeling, IoT security frameworks, medical diagnosis systems, and energy forecasting techniques, offering both theoretical foundations and practical implementations.
With contributions from contemporary research, the book highlights innovative solutions such as disease prediction systems, solar energy forecasting using LSTM networks, AI-based intrusion detection, and smart healthcare analytics. It also emphasizes hybrid models, edge AI, and data-driven decision-making approaches.
Designed for researchers, academicians, industry professionals, and postgraduate students, this book serves as a valuable resource for understanding how AI-powered technologies are shaping the future of intelligent systems and sustainable innovation across multiple disciplines.
Chapter 1.Proactive Student Retention: A Machine Learning-Based Solution
Chapter 2.Short-Term Solar Power Forecasting with LSTM Neural Networks: A Study of COER University’s Solar Panel
Chapter 3.Deep Asana:AI Powered Yoga Pose Classifier Using Deep Learning
Chapter 4.Edge-AI Enabled Hybrid Deep Learning Framework for Botnet Intrusion Detection in Modern IoT-Driven Cyber Ecosystems
Chapter 5.CNN-Based Transfer Learning Approach for Skin Disease Identification
Chapter 6.Enhancing Industrial Energy Systems: AI-Based Power Quality Strategies for Electric vehicles
Chapter 7.Cardiac Disease Prediction Using ML: A Comprehensive Analysis of Predictive Models and Risk Factors
Chapter 8.Evaluating the Impact of Age and Treatment Modalities on Sleep Health in Breast Cancer Patients
Chapter 9.Skin Cancer Detection Using Deep Learning: A Review and Proposed Architecture
Chapter 10.Sleep Disorders Classification using Multidimensional Health and Behavioral Data: A Machine Learning Approach
Chapter 11.Multi-Class Classification of Nutrition Deficiencies in Crop Leaves Using Hybrid CNN with LSTM and BiLSTM
Chapter 12.Optimized Convolutional Architectures for Dermatological Malignancy Identification
Chapter 13.Predicting Extroversion and Introversion from Social Activity Data Using Supervised Machine Learning
Chapter 14.Influence of Behavioural and Lifestyle Factors on Academic
Chapter 15.A Comparative Performance Study of Early Stroke Risk Identification Using Machine Learning.