Trends in AI-Driven Prediction: Advances, Applications, and Future Directions of Intelligent Systems

This book presents a comprehensive exploration of AI-driven prediction and intelligent systems, highlighting real-world applications of machine learning and deep learning across multiple domains. The chapters address a wide range of predictive and analytical challenges, including sentiment analysis, job migration analysis, financial risk evaluation, fraud detection, stock market prediction, and climate-aware decision support.Readers are introduced to intelligent healthcare solutions such as disease prediction, medical image analysis, and risk assessment, along with computer vision applications including emotion recognition, object detection, image classification, and human activity recognition. The book also explores advances in environmental intelligence, covering crop recommendation systems, air quality monitoring, rainfall and flood forecasting, and the impact of climate change on agriculture.To address these real-world problems, advanced deep learning and computer vision techniques such as CNNs, LSTMs, YOLO, and video classification models are effectively employed.