Model Management and Analytics for Large Scale Systems

Produk Detail:
  • Author : Bedir Tekinerdogan
  • Publisher : Academic Press
  • Pages : 344 pages
  • ISBN : 0128166509
  • Rating : /5 from reviews
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Download or Read online Model Management and Analytics for Large Scale Systems full in PDF, ePub and kindle. this book written by Bedir Tekinerdogan and published by Academic Press which was released on 14 September 2019 with total page 344 pages. We cannot guarantee that Model Management and Analytics for Large Scale Systems book is available in the library, click Get Book button and read full online book in your kindle, tablet, IPAD, PC or mobile whenever and wherever You Like. Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the field of data science will gain novel insights on the topic of model analytics that go beyond both model-based development and data analytics. This book is aimed at both researchers and practitioners who are interested in model-based development and the analytics of large-scale models, ranging from big data management and analytics, to enterprise domains. The book could also be used in graduate courses on model development, data analytics and data management. Identifies key problems and offers solution approaches and tools that have been developed or are necessary for model management and analytics Explores basic theory and background, current research topics, related challenges and the research directions for model management and analytics Provides a complete overview of model management and analytics frameworks, the different types of analytics (descriptive, diagnostics, predictive and prescriptive), the required modelling and method steps, and important future directions

Model Management and Analytics for Large Scale Systems

Model Management and Analytics for Large Scale Systems
  • Author : Bedir Tekinerdogan,├ľnder Babur,Loek Cleophas,Mark van den Brand,Mehmet Aksit
  • Publisher : Academic Press
  • Release : 14 September 2019
GET THIS BOOK Model Management and Analytics for Large Scale Systems

Model Management and Analytics for Large Scale Systems covers the use of models and related artefacts (such as metamodels and model transformations) as central elements for tackling the complexity of building systems and managing data. With their increased use across diverse settings, the complexity, size, multiplicity and variety of those artefacts has increased. Originally developed for software engineering, these approaches can now be used to simplify the analytics of large-scale models and automate complex data analysis processes. Those in the

Business Modeling and Software Design

Business Modeling and Software Design
  • Author : Boris Shishkov
  • Publisher : Springer Nature
  • Release : 22 June 2021
GET THIS BOOK Business Modeling and Software Design

This book constitutes the refereed proceedings of the 10th International Symposium on Business Modeling and Software Design, BMSD 2020, which took place in Berlin, Germany, in July 2020. BMSD is a leading international forum that brings together researchers and practitioners interested in business modeling and its relation to software design. Particular areas of interest are: Business Processes and Enterprise Engineering; Business Models and Requirements; Business Models and Services; Business Models and Software; Information Systems Architectures and Paradigms; Data Aspects in Business Modeling

Manufacturing Modeling Management and Control MIM 2000

Manufacturing  Modeling  Management and Control  MIM 2000
  • Author : Peter P. Groumpos,A. P. Tzes
  • Publisher : Pergamon
  • Release : 22 June 2021
GET THIS BOOK Manufacturing Modeling Management and Control MIM 2000

This Proceedings contains the papers presented at the IFAC Symposium on Manufacturing, Modeling, Management and Control (MIM 2000), held in Patras, Greece, on 12-14 July 2000. MIM is a long-running series of IFAC meetings featuring the best work on the development, comparison and classification of manufacturing systems. In this Proceedings, key engineering topics, such as agile manufacturing and intelligent manufacturing, are presented alongside more management-related issues as well as some of the fundamental control theory applicable to these areas. Altogether, over 90 papers

Data Management in Machine Learning Systems

Data Management in Machine Learning Systems
  • Author : Matthias Boehm,Arun Kumar,Jun Yang
  • Publisher : Morgan & Claypool Publishers
  • Release : 25 February 2019
GET THIS BOOK Data Management in Machine Learning Systems

Large-scale data analytics using machine learning (ML) underpins many modern data-driven applications. ML systems provide means of specifying and executing these ML workloads in an efficient and scalable manner. Data management is at the heart of many ML systems due to data-driven application characteristics, data-centric workload characteristics, and system architectures inspired by classical data management techniques. In this book, we follow this data-centric view of ML systems and aim to provide a comprehensive overview of data management in ML systems

Real Time Data Analytics for Large Scale Sensor Data

Real Time Data Analytics for Large Scale Sensor Data
  • Author : Himansu Das,Nilanjan Dey,Valentina Emilia Balas
  • Publisher : Academic Press
  • Release : 31 August 2019
GET THIS BOOK Real Time Data Analytics for Large Scale Sensor Data

Real-Time Data Analytics for Large-Scale Sensor Data covers the theory and applications of hardware platforms and architectures, the development of software methods, techniques and tools, applications, governance and adoption strategies for the use of massive sensor data in real-time data analytics. It presents the leading-edge research in the field and identifies future challenges in this fledging research area. The book captures the essence of real-time IoT based solutions that require a multidisciplinary approach for catering to on-the-fly processing, including methods