Machine Learning And Systems Engineering

Machine Learning and Systems Engineering
Publisher Springer Science & Business Media
Release Date
Category Computers
Total Pages 614
ISBN 9048194199
Rating 4/5 from 21 reviews
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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.

Machine Learning and Systems Engineering
  • Author : Sio-Iong Ao,Burghard B. Rieger,Mahyar Amouzegar
  • Publisher : Springer Science & Business Media
  • Release Date : 2010-10-05

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

GET BOOK
Machine Learning and Systems Engineering
  • Author : Sio-Iong Ao,Burghard B. Rieger,Mahyar Amouzegar
  • Publisher : Springer
  • Release Date : 2010-10-09

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

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Applications of Artificial Intelligence in Process Systems Engineering
  • Author : Jingzheng Ren,Weifeng Shen,Yi Man,Lichun DOng
  • Publisher : Elsevier
  • Release Date : 2021-06-05

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

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Machine Learning and Knowledge Discovery for Engineering Systems Health Management
  • Author : Ashok N. Srivastava,Jiawei Han
  • Publisher : CRC Press
  • Release Date : 2016-04-19

This volume presents state-of-the-art tools and techniques for automatically detecting, diagnosing, and predicting the effects of adverse events in an engineered system. It emphasizes the importance of these techniques in managing the intricate interactions within and between engineering systems to maintain a high degree of reliability. Reflecting the interdisciplinary nature

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Predictive Modelling for Energy Management and Power Systems Engineering
  • Author : Ravinesh Deo,Pijush Samui,Sanjiban Sekhar Roy
  • Publisher : Elsevier
  • Release Date : 2020-09-30

Predictive Modeling for Energy Management and Power Systems Engineering introduces readers to the cutting-edge use of big data and large computational infrastructures in energy demand estimation and power management systems. The book supports engineers and scientists who seek to become familiar with advanced optimization techniques for power systems designs, optimization

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

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

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Engineering Smarter Systems
  • Author : Barclay R. Brown
  • Publisher : Wiley
  • Release Date : 2021-01-20

This book brings an integrated perspective to several major current themes in the engineering of technological and business systems. Part I begins with an introduction that explains and applies ideas and practices from the fields of Systems Engineering, Systems Thinking, User Centric Design and Artificial Intelligence/Machine Learning. Part II

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Systems Engineering
  • Author : Howard Eisner
  • Publisher : CRC Press
  • Release Date : 2020-07-14

The author has spent approximately 50 years in the field of systems engineering. This Focus book provides a "looking back" at his 50-year run and the lessons he learned and would like to share with other engineers, so they can use these lessons in their day-to-day work in systems engineering and

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Advances in Artificial Intelligence  Software and Systems Engineering
  • Author : Tareq Z. Ahram
  • Publisher : Springer
  • Release Date : 2018-06-28

This book focuses on emerging issues following the integration of artificial intelligence systems in our daily lives. It focuses on the cognitive, visual, social and analytical aspects of computing and intelligent technologies, highlighting ways to improve technology acceptance, effectiveness, and efficiency. Topics such as responsibility, integration and training are discussed

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Data Driven Science and Engineering
  • Author : Steven L. Brunton,J. Nathan Kutz
  • Publisher : Cambridge University Press
  • Release Date : 2019-02-28

This beginning graduate textbook teaches data science and machine learning methods for modeling, prediction, and control of complex systems.

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Progress in Systems Engineering
  • Author : Henry Selvaraj,Dawid Zydek,Grzegorz Chmaj
  • Publisher : Springer
  • Release Date : 2014-08-12

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

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Big Data Application in Power Systems
  • Author : Reza Arghandeh,Yuxun Zhou
  • Publisher : Elsevier
  • Release Date : 2017-11-27

Big Data Application in Power Systems brings together experts from academia, industry and regulatory agencies who share their understanding and discuss the big data analytics applications for power systems diagnostics, operation and control. Recent developments in monitoring systems and sensor networks dramatically increase the variety, volume and velocity of measurement

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Advances in Artificial Intelligence  Software and Systems Engineering
  • Author : Tareq Ahram
  • Publisher : Springer
  • Release Date : 2019-06-10

This book addresses emerging issues resulting from the integration of artificial intelligence systems in our daily lives. It focuses on the cognitive, visual, social and analytical aspects of computing and intelligent technologies, highlighting ways to improve the acceptance, effectiveness, and efficiency of said technologies. Topics such as responsibility, integration and

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Deep Learning and Parallel Computing Environment for Bioengineering Systems
  • Author : Dr. Arun Kumar Sangaiah
  • Publisher : Academic Press
  • Release Date : 2019-07-26

Deep Learning and Parallel Computing Environment for Bioengineering Systems delivers a significant forum for the technical advancement of deep learning in parallel computing environment across bio-engineering diversified domains and its applications. Pursuing an interdisciplinary approach, it focuses on methods used to identify and acquire valid, potentially useful knowledge sources. Managing

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Machine Learning and Data Science in the Power Generation Industry
  • Author : Patrick Bangert
  • Publisher : Elsevier
  • Release Date : 2021-01-25

Machine Learning and Data Science in the Power Generation Industry explores current best practices and quantifies the value-add in developing data-oriented computational programs in the power industry, with a particular focus on thoughtfully chosen real-world case studies. It provides a set of realistic pathways for organizations seeking to develop machine

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