Data Analysis And Optimization For Engineering And Computing Problems
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Data Analysis And Optimization For Engineering And Computing Problems
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Author : Pandian Vasant
language : en
Publisher: Springer Nature
Release Date : 2020-09-08
Data Analysis And Optimization For Engineering And Computing Problems written by Pandian Vasant and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-08 with Technology & Engineering categories.
This book presents the proceedings of The EAI International Conference on Computer Science: Applications in Engineering and Health Services (COMPSE 2019). The conference highlighted the latest research innovations and applications of algorithms designed for optimization applications within the fields of Science, Computer Science, Engineering, Information Technology, Management, Finance and Economics and Health Systems. Focusing on a variety of methods and systems as well as practical examples, this conference is a significant resource for post graduate-level students, decision makers, and researchers in both public and private sectors who are seeking research-based methods for modelling uncertain and unpredictable real-world problems.
Open Problems In Optimization And Data Analysis
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Author : Panos M. Pardalos
language : en
Publisher: Springer
Release Date : 2018-12-04
Open Problems In Optimization And Data Analysis written by Panos M. Pardalos and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-12-04 with Mathematics categories.
Computational and theoretical open problems in optimization, computational geometry, data science, logistics, statistics, supply chain modeling, and data analysis are examined in this book. Each contribution provides the fundamentals needed to fully comprehend the impact of individual problems. Current theoretical, algorithmic, and practical methods used to circumvent each problem are provided to stimulate a new effort towards innovative and efficient solutions. Aimed towards graduate students and researchers in mathematics, optimization, operations research, quantitative logistics, data analysis, and statistics, this book provides a broad comprehensive approach to understanding the significance of specific challenging or open problems within each discipline. The contributions contained in this book are based on lectures focused on “Challenges and Open Problems in Optimization and Data Science” presented at the Deucalion Summer Institute for Advanced Studies in Optimization, Mathematics, and Data Science in August 2016.
Foundations Of Data Science For Engineering Problem Solving
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Author : Parikshit Narendra Mahalle
language : en
Publisher: Springer Nature
Release Date : 2021-08-21
Foundations Of Data Science For Engineering Problem Solving written by Parikshit Narendra Mahalle and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-08-21 with Technology & Engineering categories.
This book is one-stop shop which offers essential information one must know and can implement in real-time business expansions to solve engineering problems in various disciplines. It will also help us to make future predictions and decisions using AI algorithms for engineering problems. Machine learning and optimizing techniques provide strong insights into novice users. In the era of big data, there is a need to deal with data science problems in multidisciplinary perspective. In the real world, data comes from various use cases, and there is a need of source specific data science models. Information is drawn from various platforms, channels, and sectors including web-based media, online business locales, medical services studies, and Internet. To understand the trends in the market, data science can take us through various scenarios. It takes help of artificial intelligence and machine learning techniques to design and optimize the algorithms. Big data modelling and visualization techniques of collected data play a vital role in the field of data science. This book targets the researchers from areas of artificial intelligence, machine learning, data science and big data analytics to look for new techniques in business analytics and applications of artificial intelligence in recent businesses.
Optimization For Data Analysis
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Author : Stephen J. Wright
language : en
Publisher: Cambridge University Press
Release Date : 2022-04-21
Optimization For Data Analysis written by Stephen J. Wright 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 2022-04-21 with Computers categories.
A concise text that presents and analyzes the fundamental techniques and methods in optimization that are useful in data science.
Introduction To Scientific Computing And Data Analysis
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Author : Mark H. Holmes
language : en
Publisher:
Release Date : 2023
Introduction To Scientific Computing And Data Analysis written by Mark H. Holmes and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023 with categories.
This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra.
Engineering Analytics
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Author : Luis Rabelo
language : en
Publisher: CRC Press
Release Date : 2021-09-27
Engineering Analytics written by Luis Rabelo and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-27 with Technology & Engineering categories.
Engineering analytics is becoming a necessary skill for every engineer. Areas such as Operations Research, Simulation, and Machine Learning can be totally transformed through massive volumes of data. This book is intended to be an introduction to Engineering Analytics that can be used to improve performance tracking, customer segmentation for resource optimization, patterns and classification strategies, and logistics control towers. Basic methods in the areas of visual, descriptive, predictive, and prescriptive analytics and Big Data are introduced. Industrial case studies and example problem demonstrations are used throughout the book to reinforce the concepts and applications. The book goes on to cover visual analytics and its relationships, simulation from the respective dimensions and Machine Learning and Artificial Intelligence from different paradigms viewpoints. The book is intended for professionals wanting to work on analytical problems, for Engineering students, Researchers, Chief-Technology Officers, and Directors that work within the areas and fields of Industrial Engineering, Computer Science, Statistics, Electrical Engineering Operations Research, and Big Data.
Introduction To Scientific Computing And Data Analysis
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Author : Mark H. Holmes
language : en
Publisher: Springer Nature
Release Date : 2023-07-11
Introduction To Scientific Computing And Data Analysis written by Mark H. Holmes and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-07-11 with Computers categories.
This textbook provides an introduction to numerical computing and its applications in science and engineering. The topics covered include those usually found in an introductory course, as well as those that arise in data analysis. This includes optimization and regression-based methods using a singular value decomposition. The emphasis is on problem solving, and there are numerous exercises throughout the text concerning applications in engineering and science. The essential role of the mathematical theory underlying the methods is also considered, both for understanding how the method works, as well as how the error in the computation depends on the method being used. The codes used for most of the computational examples in the text are available on GitHub. This new edition includes material necessary for an upper division course in computational linear algebra.
Deep Learning Techniques And Optimization Strategies In Big Data Analytics
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Author : Thomas, J. Joshua
language : en
Publisher: IGI Global
Release Date : 2019-11-29
Deep Learning Techniques And Optimization Strategies In Big Data Analytics written by Thomas, J. Joshua and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-11-29 with Computers categories.
Many approaches have sprouted from artificial intelligence (AI) and produced major breakthroughs in the computer science and engineering industries. Deep learning is a method that is transforming the world of data and analytics. Optimization of this new approach is still unclear, however, and there’s a need for research on the various applications and techniques of deep learning in the field of computing. Deep Learning Techniques and Optimization Strategies in Big Data Analytics is a collection of innovative research on the methods and applications of deep learning strategies in the fields of computer science and information systems. While highlighting topics including data integration, computational modeling, and scheduling systems, this book is ideally designed for engineers, IT specialists, data analysts, data scientists, engineers, researchers, academicians, and students seeking current research on deep learning methods and its application in the digital industry.
Optimization Problems In Graph Theory
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Author : Boris Goldengorin
language : en
Publisher: Springer
Release Date : 2018-09-27
Optimization Problems In Graph Theory written by Boris Goldengorin and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-09-27 with Mathematics categories.
This book presents open optimization problems in graph theory and networks. Each chapter reflects developments in theory and applications based on Gregory Gutin’s fundamental contributions to advanced methods and techniques in combinatorial optimization. Researchers, students, and engineers in computer science, big data, applied mathematics, operations research, algorithm design, artificial intelligence, software engineering, data analysis, industrial and systems engineering will benefit from the state-of-the-art results presented in modern graph theory and its applications to the design of efficient algorithms for optimization problems. Topics covered in this work include: · Algorithmic aspects of problems with disjoint cycles in graphs · Graphs where maximal cliques and stable sets intersect · The maximum independent set problem with special classes · A general technique for heuristic algorithms for optimization problems · The network design problem with cut constraints · Algorithms for computing the frustration index of a signed graph · A heuristic approach for studying the patrol problem on a graph · Minimum possible sum and product of the proper connection number · Structural and algorithmic results on branchings in digraphs · Improved upper bounds for Korkel--Ghosh benchmark SPLP instances
Modeling Simulation And Optimization
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Author : Pandian Vasant
language : en
Publisher: Springer
Release Date : 2018-05-23
Modeling Simulation And Optimization written by Pandian Vasant and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-05-23 with Technology & Engineering categories.
This book features selected contributions in the areas of modeling, simulation, and optimization. The contributors discusses requirements in problem solving for modeling, simulation, and optimization. Modeling, simulation, and optimization have increased in demand in exponential ways and how potential solutions might be reached. They describe how new technologies in computing and engineering have reduced the dimension of data coverage worldwide, and how recent inventions in information and communication technology (ICT) have inched towards reducing the gaps and coverage of domains globally. The chapters cover how the digging of information in a large data and soft-computing techniques have contributed to a strength in prediction and analysis, for decision making in computer science, technology, management, social computing, green computing, and telecom. The book provides an insightful reference to the researchers in the fields of engineering and computer science. Researchers, academics, and professionals will benefit from this volume. Features selected expanded papers in modeling, simulation, and optimization from COMPSE 2016; Includes research into soft computing and its application in engineering and technology; Presents contributions from global experts in academia and industry in modeling, simulation, and optimization.