Machine Intelligence In Mechanical Engineering
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| Author | : Kaushik Kumar |
| Publisher | : CRC Press |
| Total Pages | : 157 |
| Release | : 2021-06-20 |
| Genre | : Computers |
| ISBN | : 1000396932 |
Artificial Intelligence in Mechanical and Industrial Engineering offers a unified platform for the dissemination of basic and applied knowledge on the integration of artificial intelligence within the realm of mechanical and industrial engineering. The book covers the tools and information needed to build successful careers and a source of knowledge for those working with AI within these domains. The book offers a systematic approach to explicate fundamentals as well as recent advances. It incorporates various case studies for major topics as well as numerous examples. It will also include real-time intelligent automation and associated supporting methodologies and techniques, and cover decision-support systems, as well as applications of Chaos Theory and Fractals. The book will give scientists, researchers, instructors, students, and practitioners the tools and information needed to build successful careers and to be an impetus to advancements in next-generation mechanical and industrial engineering domains.
| Author | : Ryan G. McClarren |
| Publisher | : Springer Nature |
| Total Pages | : 252 |
| Release | : 2021-09-21 |
| Genre | : Technology & Engineering |
| ISBN | : 3030703886 |
All engineers and applied scientists will need to harness the power of machine learning to solve the highly complex and data intensive problems now emerging. This text teaches state-of-the-art machine learning technologies to students and practicing engineers from the traditionally “analog” disciplines—mechanical, aerospace, chemical, nuclear, and civil. Dr. McClarren examines these technologies from an engineering perspective and illustrates their specific value to engineers by presenting concrete examples based on physical systems. The book proceeds from basic learning models to deep neural networks, gradually increasing readers’ ability to apply modern machine learning techniques to their current work and to prepare them for future, as yet unknown, problems. Rather than taking a black box approach, the author teaches a broad range of techniques while conveying the kinds of problems best addressed by each. Examples and case studies in controls, dynamics, heat transfer, and other engineering applications are implemented in Python and the libraries scikit-learn and tensorflow, demonstrating how readers can apply the most up-to-date methods to their own problems. The book equally benefits undergraduate engineering students who wish to acquire the skills required by future employers, and practicing engineers who wish to expand and update their problem-solving toolkit.
| Author | : K. Palanikumar |
| Publisher | : Elsevier |
| Total Pages | : 451 |
| Release | : 2024-01-18 |
| Genre | : Technology & Engineering |
| ISBN | : 0443186456 |
Machine Intelligence in Mechanical Engineering explains the latest applications of machine intelligence and data-driven decision-making in mechanical engineering industries. By providing introductory theory, trouble-shooting case studies, detailed algorithms and implementation instructions, this interdisciplinary book will help readers explore additional applications in their own fields. Those with a mechanical background will learn the important tasks related to preprocessing of datasets, feature extraction, verification and validation of machine learning models which unlock these new methods. Machine Intelligence is currently a key topic in industrial automation, enabling machines to solve complex engineering tasks and driving efficiencies in the smart production line. Smart preventative maintenance systems can prevent machine downtime, smart monitoring and control can produce more effective workflows with less human intervention. Provides detailed case studies of how machine intelligence has been used in mechanical engineering applications Includes a basic introduction to machine learning algorithms and their implementation Addresses innovative applications of AR/VR technology in mechanical engineering
| Author | : Gebrail Bekdas |
| Publisher | : Engineering Science Reference |
| Total Pages | : 312 |
| Release | : 2019 |
| Genre | : Artificial intelligence |
| ISBN | : 9781799803027 |
"This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering"--
| Author | : Prashant Johri |
| Publisher | : Springer Nature |
| Total Pages | : 404 |
| Release | : 2020-05-04 |
| Genre | : Technology & Engineering |
| ISBN | : 9811533571 |
This book covers applications of machine learning in artificial intelligence. The specific topics covered include human language, heterogeneous and streaming data, unmanned systems, neural information processing, marketing and the social sciences, bioinformatics and robotics, etc. It also provides a broad range of techniques that can be successfully applied and adopted in different areas. Accordingly, the book offers an interesting and insightful read for scholars in the areas of computer vision, speech recognition, healthcare, business, marketing, and bioinformatics.
| Author | : Paul R. Daugherty |
| Publisher | : Harvard Business Press |
| Total Pages | : 264 |
| Release | : 2018-03-20 |
| Genre | : Computers |
| ISBN | : 1633693872 |
AI is radically transforming business. Are you ready? Look around you. Artificial intelligence is no longer just a futuristic notion. It's here right now--in software that senses what we need, supply chains that "think" in real time, and robots that respond to changes in their environment. Twenty-first-century pioneer companies are already using AI to innovate and grow fast. The bottom line is this: Businesses that understand how to harness AI can surge ahead. Those that neglect it will fall behind. Which side are you on? In Human + Machine, Accenture leaders Paul R. Daugherty and H. James (Jim) Wilson show that the essence of the AI paradigm shift is the transformation of all business processes within an organization--whether related to breakthrough innovation, everyday customer service, or personal productivity habits. As humans and smart machines collaborate ever more closely, work processes become more fluid and adaptive, enabling companies to change them on the fly--or to completely reimagine them. AI is changing all the rules of how companies operate. Based on the authors' experience and research with 1,500 organizations, the book reveals how companies are using the new rules of AI to leap ahead on innovation and profitability, as well as what you can do to achieve similar results. It describes six entirely new types of hybrid human + machine roles that every company must develop, and it includes a "leader’s guide" with the five crucial principles required to become an AI-fueled business. Human + Machine provides the missing and much-needed management playbook for success in our new age of AI. BOOK PROCEEDS FOR THE AI GENERATION The authors' goal in publishing Human + Machine is to help executives, workers, students and others navigate the changes that AI is making to business and the economy. They believe AI will bring innovations that truly improve the way the world works and lives. However, AI will cause disruption, and many people will need education, training and support to prepare for the newly created jobs. To support this need, the authors are donating the royalties received from the sale of this book to fund education and retraining programs focused on developing fusion skills for the age of artificial intelligence.
| Author | : Wen Zhe Chen |
| Publisher | : Trans Tech Publications Ltd |
| Total Pages | : 2810 |
| Release | : 2012-02-27 |
| Genre | : Technology & Engineering |
| ISBN | : 3038138053 |
This massive compendium presents full coverage of the current state of knowledge with regard to manufacturing science and engineering, focusing on Advanced Mechanical Design. The 525 peer-reviewed papers are grouped into 17 chapters: Materials Design; Mechanical Dynamics and Its Applications; Mechanical Transmission Theory and Applications; Mechanical Reliability Theory and Engineering; Theory and Application of Friction and Wear; Vibration, Noise Analysis and Control; Dynamic Mechanical Analysis, Optimization and Control; Innovative Design Methodology; Product Life-Cycle Design; Intelligent Optimization Design; Structural Strength and Robustness; Reverse Engineering; Chapter 13: Green Design and Manufacturing; Chapter 14: Design for Sustainability; Chapter 15: New Mechanisms and Robotics; Complex Electro-Mechanical System Design; Advanced CAE Technique.
| Author | : Ketan Kotecha |
| Publisher | : Springer Nature |
| Total Pages | : 556 |
| Release | : 2020-06-17 |
| Genre | : Technology & Engineering |
| ISBN | : 9811544743 |
This book includes selected papers from the International Conference on Data Science and Intelligent Applications (ICDSIA 2020), hosted by Gandhinagar Institute of Technology (GIT), Gujarat, India, on January 24–25, 2020. The proceedings present original and high-quality contributions on theory and practice concerning emerging technologies in the areas of data science and intelligent applications. The conference provides a forum for researchers from academia and industry to present and share their ideas, views and results, while also helping them approach the challenges of technological advancements from different viewpoints. The contributions cover a broad range of topics, including: collective intelligence, intelligent systems, IoT, fuzzy systems, Bayesian networks, ant colony optimization, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, speech processing, machine learning and deep learning, and intelligent applications and systems. Helping strengthen the links between academia and industry, the book offers a valuable resource for instructors, students, industry practitioners, engineers, managers, researchers, and scientists alike.
| Author | : Shubhabrata Datta |
| Publisher | : Springer Nature |
| Total Pages | : 202 |
| Release | : 2021-07-24 |
| Genre | : Technology & Engineering |
| ISBN | : 3030758478 |
This book covers different machine learning techniques such as artificial neural network, support vector machine, rough set theory and deep learning. It points out the difference between the techniques and their suitability for specific applications. This book also describes different applications of machine learning techniques for industrial problems. The book includes several case studies, helping researchers in academia and industries aspiring to use machine learning for solving practical industrial problems.
| Author | : Michał Kleiber |
| Publisher | : Ellis Horwood |
| Total Pages | : 264 |
| Release | : 1990 |
| Genre | : Computers |
| ISBN | : |
This monograph on the use of AI techniques in engineering emphasizes those subjects which traditionally rely on novel computer techniques (e.g. computational mechanics, computer-aided design, and optimization methods), and presents successful applications of AI techniques in solving realistic problems. Annotation copyrighted by Book News, Inc., Portland, OR
