Deep Learning Applications And Intelligent Decision Making In Engineering
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Deep Learning Applications And Intelligent Decision Making In Engineering
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Author : Senthilnathan, Karthikrajan
language : en
Publisher: IGI Global
Release Date : 2020-10-23
Deep Learning Applications And Intelligent Decision Making In Engineering written by Senthilnathan, Karthikrajan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-10-23 with Technology & Engineering categories.
Deep learning includes a subset of machine learning for processing the unsupervised data with artificial neural network functions. The major advantage of deep learning is to process big data analytics for better analysis and self-adaptive algorithms to handle more data. When applied to engineering, deep learning can have a great impact on the decision-making process. Deep Learning Applications and Intelligent Decision Making in Engineering is a pivotal reference source that provides practical applications of deep learning to improve decision-making methods and construct smart environments. Highlighting topics such as smart transportation, e-commerce, and cyber physical systems, this book is ideally designed for engineers, computer scientists, programmers, software engineers, research scholars, IT professionals, academicians, and postgraduate students seeking current research on the implementation of automation and deep learning in various engineering disciplines.
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 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.
Applied Intelligent Decision Making In Machine Learning
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Author : Himansu Das
language : en
Publisher: CRC Press
Release Date : 2020-11-18
Applied Intelligent Decision Making In Machine Learning written by Himansu Das and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-11-18 with Computers categories.
The objective of this edited book is to share the outcomes from various research domains to develop efficient, adaptive, and intelligent models to handle the challenges related to decision making. It incorporates the advances in machine intelligent techniques such as data streaming, classification, clustering, pattern matching, feature selection, and deep learning in the decision-making process for several diversified applications such as agriculture, character recognition, landslide susceptibility, recommendation systems, forecasting air quality, healthcare, exchange rate prediction, and image dehazing. It also provides a premier interdisciplinary platform for scientists, researchers, practitioners, and educators to share their thoughts in the context of recent innovations, trends, developments, practical challenges, and advancements in the field of data mining, machine learning, soft computing, and decision science. It also focuses on the usefulness of applied intelligent techniques in the decision-making process in several aspects. To address these objectives, this edited book includes a dozen chapters contributed by authors from around the globe. The authors attempt to solve these complex problems using several intelligent machine-learning techniques. This allows researchers to understand the mechanism needed to harness the decision-making process using machine-learning techniques for their own respective endeavors.
Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches
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Author : K. Gayathri Devi
language : en
Publisher:
Release Date : 2024-10-04
Artificial Intelligence Trends For Data Analytics Using Machine Learning And Deep Learning Approaches written by K. Gayathri Devi and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-04 with Computers categories.
This book focuses on the implementation of various elementary and advanced approaches in AI that can be used in various domains to solve real-time decision-making problems.
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
Progress In Intelligent Decision Science
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Author : Tofigh Allahviranloo
language : en
Publisher: Springer Nature
Release Date : 2021-01-29
Progress In Intelligent Decision Science written by Tofigh Allahviranloo and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-01-29 with Technology & Engineering categories.
This book contains the topics of artificial intelligence and deep learning that do have much application in real-life problems. The concept of uncertainty has long been used in applied science, especially decision making and a logical decision must be made in the field of uncertainty or in the real-life environment that is formed and combined with vague concepts and data. The chapters of this book are connected to the new concepts and aspects of decision making with uncertainty. Besides, other chapters are involved with the concept of data mining and decision making under uncertain computations.
Context Aware Machine Learning And Mobile Data Analytics
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Author : Iqbal Sarker
language : en
Publisher:
Release Date : 2021
Context Aware Machine Learning And Mobile Data Analytics written by Iqbal Sarker and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021 with categories.
This book offers a clear understanding of the concept of context-aware machine learning including an automated rule-based framework within the broad area of data science and analytics, particularly, with the aim of data-driven intelligent decision making. Thus, we have bestowed a comprehensive study on this topic that explores multi-dimensional contexts in machine learning modeling, context discretization with time-series modeling, contextual rule discovery and predictive analytics, recent-pattern or rule-based behavior modeling, and their usefulness in various context-aware intelligent applications and services. The presented machine learning-based techniques can be employed in a wide range of real-world application areas ranging from personalized mobile services to security intelligence, highlighted in the book. As the interpretability of a rule-based system is high, the automation in discovering rules from contextual raw data can make this book more impactful for the application developers as well as researchers. Overall, this book provides a good reference for both academia and industry people in the broad area of data science, machine learning, AI-Driven computing, human-centered computing and personalization, behavioral analytics, IoT and mobile applications, and cybersecurity intelligence.
Deep Learning Applications Volume 4
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Author : M. Arif Wani
language : en
Publisher: Springer Nature
Release Date : 2022-11-25
Deep Learning Applications Volume 4 written by M. Arif Wani and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-25 with Technology & Engineering categories.
This book presents a compilation of extended versions of selected papers from 20th IEEE International Conference on Machine Learning and Applications (IEEE ICMLA 2021). It focuses on deep learning networks and their applications in domains such as healthcare, security and threat detection, fault diagnosis and accident analysis, and robotic control in industrial environments. It highlights novel ways of using deep neural networks to solve real-world problems, and also offers insights into deep learning architectures and algorithms, making it an essential reference guide for academic researchers, professionals, software engineers in industry, and innovative product developers. The book is fourth in the series published since 2017.
Handbook Of Research On Deep Learning Based Image Analysis Under Constrained And Unconstrained Environments
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Author : Raj, Alex Noel Joseph
language : en
Publisher: IGI Global
Release Date : 2020-12-25
Handbook Of Research On Deep Learning Based Image Analysis Under Constrained And Unconstrained Environments written by Raj, Alex Noel Joseph and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-12-25 with Computers categories.
Recent advancements in imaging techniques and image analysis has broadened the horizons for their applications in various domains. Image analysis has become an influential technique in medical image analysis, optical character recognition, geology, remote sensing, and more. However, analysis of images under constrained and unconstrained environments require efficient representation of the data and complex models for accurate interpretation and classification of data. Deep learning methods, with their hierarchical/multilayered architecture, allow the systems to learn complex mathematical models to provide improved performance in the required task. The Handbook of Research on Deep Learning-Based Image Analysis Under Constrained and Unconstrained Environments provides a critical examination of the latest advancements, developments, methods, systems, futuristic approaches, and algorithms for image analysis and addresses its challenges. Highlighting concepts, methods, and tools including convolutional neural networks, edge enhancement, image segmentation, machine learning, and image processing, the book is an essential and comprehensive reference work for engineers, academicians, researchers, and students.