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Machine Learning And Systems Engineering


Machine Learning And Systems Engineering
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Machine Learning And Systems Engineering


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.



Engineering Artificially Intelligent Systems


Engineering Artificially Intelligent Systems
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Author : William F. Lawless
language : en
Publisher: Springer Nature
Release Date : 2021-11-16

Engineering Artificially Intelligent Systems written by William F. Lawless and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-16 with Computers categories.


Many current AI and machine learning algorithms and data and information fusion processes attempt in software to estimate situations in our complex world of nested feedback loops. Such algorithms and processes must gracefully and efficiently adapt to technical challenges such as data quality induced by these loops, and interdependencies that vary in complexity, space, and time. To realize effective and efficient designs of computational systems, a Systems Engineering perspective may provide a framework for identifying the interrelationships and patterns of change between components rather than static snapshots. We must study cascading interdependencies through this perspective to understand their behavior and to successfully adopt complex system-of-systems in society. This book derives in part from the presentations given at the AAAI 2021 Spring Symposium session on Leveraging Systems Engineering to Realize Synergistic AI / Machine Learning Capabilities. Its 16 chapters offer an emphasis on pragmatic aspects and address topics in systems engineering; AI, machine learning, and reasoning; data and information fusion; intelligent systems; autonomous systems; interdependence and teamwork; human-computer interaction; trust; and resilience.



Applications Of Artificial Intelligence In Process Systems Engineering


Applications Of Artificial Intelligence In Process Systems Engineering
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Author : Jingzheng Ren
language : en
Publisher: Elsevier
Release Date : 2021-06-17

Applications Of Artificial Intelligence In Process Systems Engineering written by Jingzheng Ren and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-06-17 with Technology & Engineering categories.


Applications of Artificial Intelligence in Process Systems Engineering offers a broad perspective on the issues related to artificial intelligence technologies and their applications in chemical and process engineering. The book comprehensively introduces the methodology and applications of AI technologies in process systems engineering, making it an indispensable reference for researchers and students. As chemical processes and systems are usually non-linear and complex, thus making it challenging to apply AI methods and technologies, this book is an ideal resource on emerging areas such as cloud computing, big data, the industrial Internet of Things and deep learning. With process systems engineering's potential to become one of the driving forces for the development of AI technologies, this book covers all the right bases. Explains the concept of machine learning, deep learning and state-of-the-art intelligent algorithms Discusses AI-based applications in process modeling and simulation, process integration and optimization, process control, and fault detection and diagnosis Gives direction to future development trends of AI technologies in chemical and process engineering



Building Intelligent Systems


Building Intelligent Systems
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Author : Geoff Hulten
language : en
Publisher: Apress
Release Date : 2018-03-06

Building Intelligent Systems written by Geoff Hulten and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-06 with Computers categories.


Produce a fully functioning Intelligent System that leverages machine learning and data from user interactions to improve over time and achieve success. This book teaches you how to build an Intelligent System from end to end and leverage machine learning in practice. You will understand how to apply your existing skills in software engineering, data science, machine learning, management, and program management to produce working systems. Building Intelligent Systems is based on more than a decade of experience building Internet-scale Intelligent Systems that have hundreds of millions of user interactions per day in some of the largest and most important software systems in the world. What You’ll Learn Understand the concept of an Intelligent System: What it is good for, when you need one, and how to set it up for success Design an intelligent user experience: Produce data to help make the Intelligent System better over time Implement an Intelligent System: Execute, manage, and measure Intelligent Systems in practice Create intelligence: Use different approaches, including machine learning Orchestrate an Intelligent System: Bring the parts together throughout its life cycle and achieve the impact you want Who This Book Is For Software engineers, machine learning practitioners, and technical managers who want to build effective intelligent systems



Machine Learning For Engineers


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.



Data Driven Science And Engineering


Data Driven Science And Engineering
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Author : Steven L. Brunton
language : en
Publisher: Cambridge University Press
Release Date : 2022-05-05

Data Driven Science And Engineering written by Steven L. Brunton and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-05 with Computers categories.


A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.



Machine Learning Based Fault Diagnosis For Industrial Engineering Systems


Machine Learning Based Fault Diagnosis For Industrial Engineering Systems
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Author : Rui Yang
language : en
Publisher: CRC Press
Release Date : 2022-06-16

Machine Learning Based Fault Diagnosis For Industrial Engineering Systems written by Rui Yang and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-16 with Technology & Engineering categories.


This book provides advanced techniques for precision compensation and fault diagnosis of precision motion systems and rotating machinery. Techniques and applications through experiments and case studies for intelligent precision compensation and fault diagnosis are offered along with the introduction of machine learning and deep learning methods. Machine Learning-Based Fault Diagnosis for Industrial Engineering Systems discusses how to formulate and solve precision compensation and fault diagnosis problems. The book includes experimental results on hardware equipment used as practical examples throughout the book. Machine learning and deep learning methods used in intelligent precision compensation and intelligent fault diagnosis are introduced. Applications to deal with relevant problems concerning CNC machining and rotating machinery in industrial engineering systems are provided in detail along with applications used in precision motion systems. Methods, applications, and concepts offered in this book can help all professional engineers and students across many areas of engineering and operations management that are involved in any part of Industry 4.0 transformation.



Progress In Systems Engineering


Progress In Systems Engineering
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Author : Henry Selvaraj
language : en
Publisher: Springer
Release Date : 2014-08-12

Progress In Systems Engineering written by Henry Selvaraj and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-08-12 with Technology & Engineering categories.


This collection of proceedings from the International Conference on Systems Engineering, Las Vegas, 2014 is orientated toward systems engineering, including topics like aero-space, power systems, industrial automation and robotics, systems theory, control theory, artificial intelligence, signal processing, decision support, pattern recognition and machine learning, information and communication technologies, image processing, and computer vision as well as its applications. The volume’s main focus is on models, algorithms, and software tools that facilitate efficient and convenient utilization of modern achievements in systems engineering.



Artificial Intelligence And Digital Systems Engineering


Artificial Intelligence And Digital Systems Engineering
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Author : Adedeji B. Badiru
language : en
Publisher: CRC Press
Release Date : 2021-08-11

Artificial Intelligence And Digital Systems Engineering written by Adedeji B. Badiru and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-11 with Computers categories.


The resurgence of artificial intelligence has been fueled by the availability of the present generation of high-performance computational tools and techniques. This book is designed to provide introductory guidance to artificial intelligence, particularly from the perspective of digital systems engineering. Artificial Intelligence and Digital Systems Engineering provides a general introduction to the origin of AI and covers the wide application areas and software and hardware interfaces. It will prove to be instrumental in helping new users expand their knowledge horizon to the growing market of AI tools, as well as showing how AI is applicable to the development of games, simulation, and consumer products, particularly using artificial neural networks. This book is for the general reader, university students, and instructors of industrial, production, civil, mechanical, and manufacturing engineering. It will also be of interest to managers of technology, projects, business, plants, and operations.