Data-Driven Modeling

Arindam Mondal, Souvik Ganguli

• Publisher: Wiley-Scrivener
• Year: 2025
• Print ISBN: 9781394287895
• eBook ISBN: 9781394287901
• Edition: 1
• Topic: Computer Science
• Subtopic: Computer Science General
• Index: Computer Science

Equip yourself with the essentials of informed decision-making with this practical guide to mastering data-driven modeling and extracting actionable, meaningful patterns from the vast sea of modern data.

In an era defined by data, the ability to transform raw information into actionable insights is a skill set that transcends industries and disciplines. This book is a comprehensive guide designed to unravel the intricacies of extracting meaningful patterns from the vast sea of data that surrounds us. It explores the significance of data-driven modelling, comparing it to traditional approaches and setting the stage for understanding the transformative power and diverse applications of data-driven techniques. This comprehensive resource empowers readers to leverage data for informed decision-making. Whether you are a novice looking to grasp the fundamentals or an experienced professional seeking advanced techniques, this book serves as a practical guide through the dynamic landscape of data-driven modelling. Through clear explanations, hands-on examples, and real-world applications, readers will gain the skills needed to navigate the complexities of modern data analysis.

Table of contents

• Cover
• Table of Contents
• Series Page
• Title Page
• Copyright Page
• Preface
• 1 Fundamentals of Data Analysis and Preprocessing
• 2 Advanced Data Control Methods for Data-Driven Modeling: Techniques, Challenges, and Future Directions
• 3 Machine Learning Algorithms for Data-Driven Modeling
• 4 Neural Networks and Deep Learning in Data-Driven Modeling
• 5 Advances in Time-Series Analysis: Techniques and Applications for Predictive Forecasting
• 6 Ensemble Methods for Data-Driven Modeling in Agriculture and Applications
• 7 Artificial Intelligence–Enabled Ensemble Machine Learning Approaches for Solanaceae Crops
• 8 Dynamic Multitask Transfer Learning with Adaptive Feature Sharing for Heterogeneous Data and Continual Learning
• 9 Forecasting Solar Power Generation in the Future by ARIMA Approach and Stationary Transformation
• 10 Prognosticating Plays: ANN-Enabled Score Projection with the Help of FIS
• 11 Designing a PID Controller for the Two-Area LFC Problem Using Gradient Descent–Based Linear Regression
• 12 Implementing PID Controllers for Data‑Driven Recognizing for a Nonlinear System
• 13 Temporal Resilience Redux: BiLSTM for Short-Term Load Forecasting in Deep Learning Domain
• Index
• Also of Interest
• End User License Agreement