Machine Intelligence In Mechanical Engineering
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Artificial Intelligence In Mechanical And Industrial Engineering
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Author : Kaushik Kumar
language : en
Publisher: CRC Press
Release Date : 2021-06-20
Artificial Intelligence In Mechanical And Industrial Engineering written by Kaushik Kumar and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-20 with Computers categories.
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.
Artificial Intelligence And Machine Learning Applications In Civil Mechanical And Industrial Engineering
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Author : Gebrail Bekdas
language : en
Publisher: Engineering Science Reference
Release Date : 2019
Artificial Intelligence And Machine Learning Applications In Civil Mechanical And Industrial Engineering written by Gebrail Bekdas and has been published by Engineering Science Reference this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019 with Artificial intelligence categories.
"This book examines the application of artificial intelligence and machine learning civil, mechanical, and industrial engineering"--
Machine Intelligence In Mechanical Engineering
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Author : K. Palanikumar
language : en
Publisher: Elsevier
Release Date : 2024-01-18
Machine Intelligence In Mechanical Engineering written by K. Palanikumar and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-01-18 with Technology & Engineering categories.
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
Machine Learning For Engineers
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Author : Ryan G. McClarren
language : en
Publisher: Springer Nature
Release Date : 2021-09-21
Machine Learning For Engineers written by Ryan G. McClarren and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-21 with Technology & Engineering categories.
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.
Machine Learning And Systems Engineering
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Author : Sio-Iong Ao
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-10-05
Machine Learning And Systems Engineering written by Sio-Iong Ao and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-10-05 with Technology & Engineering categories.
A large international conference on Advances in Machine Learning and Systems Engineering was held in UC Berkeley, California, USA, October 20-22, 2009, under the auspices of the World Congress on Engineering and Computer Science (WCECS 2009). Machine Learning and Systems Engineering contains forty-six revised and extended research articles written by prominent researchers participating in the conference. Topics covered include Expert system, Intelligent decision making, Knowledge-based systems, Knowledge extraction, Data analysis tools, Computational biology, Optimization algorithms, Experiment designs, Complex system identification, Computational modeling, and industrial applications. Machine Learning and Systems Engineering offers the state of the art of tremendous advances in machine learning and systems engineering and also serves as an excellent reference text for researchers and graduate students, working on machine learning and systems engineering.
Computational Intelligence In Power Engineering
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Author : Bijaya Ketan Panigrahi
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-09-20
Computational Intelligence In Power Engineering written by Bijaya Ketan Panigrahi and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-09-20 with Computers categories.
This volume deals with different computational intelligence (CI) techniques for solving real world power industry problems. It will be extremely helpful for the researchers as well as the practicing engineers in the power industry.
Applications Of Machine Learning
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Author : Prashant Johri
language : en
Publisher: Springer Nature
Release Date : 2020-05-04
Applications Of Machine Learning written by Prashant Johri and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-04 with Technology & Engineering categories.
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.
Artificial Intelligence In Construction Engineering And Management
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Author : Limao Zhang
language : en
Publisher: Springer Nature
Release Date : 2021-06-18
Artificial Intelligence In Construction Engineering And Management written by Limao Zhang and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-18 with Technology & Engineering categories.
This book highlights the latest technologies and applications of Artificial Intelligence (AI) in the domain of construction engineering and management. The construction industry worldwide has been a late bloomer to adopting digital technology, where construction projects are predominantly managed with a heavy reliance on the knowledge and experience of construction professionals. AI works by combining large amounts of data with fast, iterative processing, and intelligent algorithms (e.g., neural networks, process mining, and deep learning), allowing the computer to learn automatically from patterns or features in the data. It provides a wide range of solutions to address many challenging construction problems, such as knowledge discovery, risk estimates, root cause analysis, damage assessment and prediction, and defect detection. A tremendous transformation has taken place in the past years with the emerging applications of AI. This enables industrial participants to operate projects more efficiently and safely, not only increasing the automation and productivity in construction but also enhancing the competitiveness globally.
Condition Monitoring Using Computational Intelligence Methods
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Author : Tshilidzi Marwala
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-01-23
Condition Monitoring Using Computational Intelligence Methods written by Tshilidzi Marwala and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-01-23 with Technology & Engineering categories.
Condition Monitoring Using Computational Intelligence Methods promotes the various approaches gathered under the umbrella of computational intelligence to show how condition monitoring can be used to avoid equipment failures and lengthen its useful life, minimize downtime and reduce maintenance costs. The text introduces various signal-processing and pre-processing techniques, wavelets and principal component analysis, for example, together with their uses in condition monitoring and details the development of effective feature extraction techniques classified into frequency-, time-frequency- and time-domain analysis. Data generated by these techniques can then be used for condition classification employing tools such as: • fuzzy systems; rough and neuro-rough sets; neural and Bayesian networks;hidden Markov and Gaussian mixture models; and support vector machines.
Machine Learning Applications In Non Conventional Machining Processes
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Author : Bose, Goutam Kumar
language : en
Publisher: IGI Global
Release Date : 2021-02-05
Machine Learning Applications In Non Conventional Machining Processes written by Bose, Goutam Kumar and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-02-05 with Computers categories.
Traditional machining has many limitations in today’s technology-driven world, which has caused industrial professionals to begin implementing various optimization techniques within their machining processes. The application of methods including machine learning and genetic algorithms has recently transformed the manufacturing industry and created countless opportunities in non-traditional machining methods. Significant research in this area, however, is still considerably lacking. Machine Learning Applications in Non-Conventional Machining Processes is a collection of innovative research on the advancement of intelligent technology in industrial environments and its applications within the manufacturing field. While highlighting topics including evolutionary algorithms, micro-machining, and artificial neural networks, this book is ideally designed for researchers, academicians, engineers, managers, developers, practitioners, industrialists, and students seeking current research on intelligence-based machining processes in today’s technology-driven market.