Artificial Intelligence Engine Optimization Aieo
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Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines
Artificial Intelligence and Data Driven Optimization of Internal Combustion Engines summarizes recent developments in Artificial Intelligence (AI)/Machine Learning (ML) and data driven optimization and calibration techniques for internal combustion engines. The book covers AI/ML and data driven methods to optimize fuel formulations and engine combustion systems, predict cycle to cycle variations, and optimize after-treatment systems and experimental engine calibration. It contains all the details of the latest optimization techniques along with their application to ICE, making it ideal for automotive engineers, mechanical engineers, OEMs and R&D centers involved in engine design. - Provides AI/ML and data driven optimization techniques in combination with Computational Fluid Dynamics (CFD) to optimize engine combustion systems - Features a comprehensive overview of how AI/ML techniques are used in conjunction with simulations and experiments - Discusses data driven optimization techniques for fuel formulations and vehicle control calibration
Artificial Intelligence for Business Optimization
This book explains how AI and Machine Learning can be applied to help businesses solve problems, support critical thinking and ultimately create customer value and increase profit. By considering business strategies, business process modeling, quality assurance, cybersecurity, governance and big data and focusing on functions, processes, and people’s behaviors it helps businesses take a truly holistic approach to business optimization. It contains practical examples that make it easy to understand the concepts and apply them. It is written for practitioners (consultants, senior executives, decision-makers) dealing with real-life business problems on a daily basis, who are keen to develop systematic strategies for the application of AI/ML/BD technologies to business automation and optimization, as well as researchers who want to explore the industrial applications of AI and higher-level students.
AI for Engines
Author: Rakesh Kumar
language: en
Publisher: Independently Published
Release Date: 2024-04-04
In the realm of modern engineering, the integration of artificial intelligence (AI) has revolutionized the way engines are designed, operated, and maintained. From automotive powertrains to industrial turbines, AI technologies offer unprecedented opportunities to optimize performance, enhance reliability, and reduce environmental impact. This book, "AI for Engines," delves into the multifaceted applications of AI in the domain of engines, offering insights into how these advanced technologies are reshaping the landscape of engine design, control, and maintenance. Engines, whether they power vehicles, industrial machinery, or renewable energy systems, serve as the heart of countless applications across various sectors. Traditionally, the optimization of engine performance and the prediction of maintenance needs have relied on empirical methods and manual intervention. However, with the advent of AI and machine learning algorithms, engineers now have access to powerful tools capable of analyzing vast amounts of data, detecting patterns, and making intelligent decisions in real-time. This book explores the diverse ways in which AI is transforming the field of engines. It begins by tracing the evolution of AI in engineering and discussing its importance in engine design and maintenance. Subsequent chapters delve into the various types of engines, including internal combustion, electric, and turbine engines, elucidating the unique challenges and opportunities presented by each. Through in-depth discussions and practical examples, readers will gain insights into the fundamental components and functionalities of engines, as well as the key performance metrics used to evaluate their operation. Furthermore, the book explores advanced AI techniques such as machine learning, genetic algorithms, and neural networks, demonstrating how these methods can be leveraged to optimize engine design, control systems, and predictive maintenance strategies. From autonomous vehicle engines to energy-efficient power generation systems, this book covers a wide range of AI applications in engine control, performance optimization, and fault diagnosis. Real-world case studies and examples illustrate the transformative impact of AI on engine technology, highlighting success stories and lessons learned from industry implementations. Ultimately, "AI for Engines" serves as a comprehensive guide for engineers, researchers, and enthusiasts seeking to harness the power of AI to unlock new possibilities in engine innovation, efficiency, and sustainability. Whether you're a seasoned professional or a curious newcomer to the field, this book provides valuable insights into the cutting-edge intersection of artificial intelligence and engine technology.