"Artificial Intelligence in Engineering: Discovering Unknown Patterns and Solutions" is an guide that explores the integration of Artificial Intelligence into engineering. The book begins by providing a clear definition of Artificial Intelligence and delving into its historical development while also exploring the various types of AI, including weak, strong, and general AI. In subsequent sections, the book explores the discovery of unknown patterns and solutions through AI, showcasing its capabilities in detecting and describing patterns. It further explores specific applications in urban planning, infrastructure construction, and risk evaluation for landslides and hillside slips. The book also covers utilizing automated learning systems within the engineering context, including linear regression, decision trees, and neural networks. Moving on to the practical applications of Artificial Intelligence in Engineering, the book highlights the significant advancements it has brought to current simulation and mathematical calculation methods. Finally, it examines the challenges associated with implementing AI in engineering, such as limited knowledge and experience, incomplete or poor-quality data, and ethical considerations. A dedicated chapter discusses the comparison between traditional simulation and mathematical calculation models and AI-based models, highlighting the significant benefits of integrating AI into these areas. Finally, the book concludes by providing insights into the development process of AI applications in engineering and offers recommendations and future perspectives on implementing AI within the field. This book is essential reading for engineers and anyone interested in harnessing the power of Artificial Intelligence within the engineering realm. It provides a comprehensive overview of AI in engineering, encompassing its applications, challenges, and prospects, making it a beginning resource for those seeking to incorporate AI into their work. TABLE OF CONTENTS: Chapter 1: Introduction to Artificial Intelligence Defining Artificial Intelligence Historical Overview Types of Artificial Intelligence Chapter 2: Applications of Artificial Intelligence in Engineering Challenges and Considerations in Implementation Data Protection, Privacy, and Ethical Implications Chapter 3: Discovering Unknown Patterns and Solutions Deep Learning Neural Networks Clustering Analysis Chapter 4: Automatic Learning Systems in Engineering Linear Regression Decision Trees Neural Networks Chapter 5: Simulation and Mathematical Calculation Models Traditional Models vs. AI-based Models Chapter 6: Examples of Artificial Intelligence Applications in Engineering Chapter 7: Conclusions and Recommendations Implementing AI in Engineering Future Perspectives Don't miss the chance to read this book.
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