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Data Driven Systems And Intelligent Applications
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Book Synopsis Data-Driven Systems and Intelligent Applications by : Mangesh M Ghonge
Download or read book Data-Driven Systems and Intelligent Applications written by Mangesh M Ghonge and published by . This book was released on 2024-10-02 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively discusses basic data-driven intelligent systems, the methods for processing the data, and cloud computing with artificial intelligence. It presents fundamental and advanced techniques used for handling large user data, and for the data stored in the cloud. It further covers data-driven decision-making for smart logistics and manufacturing systems, network security, and privacy issues in cloud computing. This book: Discusses intelligent systems and cloud computing with the help of artificial intelligence and machine learning. Showcases the importance of machine learning and deep learning in data-driven and cloud-based applications to improve their capabilities and intelligence. Presents the latest developments in data-driven and cloud applications with respect to their design and architecture. Covers artificial intelligence methods along with their experimental result analysis through data processing tools. Presents the advent of machine learning, deep learning, and reinforcement technique for cloud computing to provide cost-effective and efficient services. The text will be useful for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer engineering, manufacturing engineering, and production engineering.
Book Synopsis Data Driven Smart Manufacturing Technologies and Applications by : Weidong Li
Download or read book Data Driven Smart Manufacturing Technologies and Applications written by Weidong Li and published by Springer Nature. This book was released on 2021-02-20 with total page 218 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book reports innovative deep learning and big data analytics technologies for smart manufacturing applications. In this book, theoretical foundations, as well as the state-of-the-art and practical implementations for the relevant technologies, are covered. This book details the relevant applied research conducted by the authors in some important manufacturing applications, including intelligent prognosis on manufacturing processes, sustainable manufacturing and human-robot cooperation. Industrial case studies included in this book illustrate the design details of the algorithms and methodologies for the applications, in a bid to provide useful references to readers. Smart manufacturing aims to take advantage of advanced information and artificial intelligent technologies to enable flexibility in physical manufacturing processes to address increasingly dynamic markets. In recent years, the development of innovative deep learning and big data analytics algorithms is dramatic. Meanwhile, the algorithms and technologies have been widely applied to facilitate various manufacturing applications. It is essential to make a timely update on this subject considering its importance and rapid progress. This book offers a valuable resource for researchers in the smart manufacturing communities, as well as practicing engineers and decision makers in industry and all those interested in smart manufacturing and Industry 4.0.
Book Synopsis Handbook of Dynamic Data Driven Applications Systems by : Frederica Darema
Download or read book Handbook of Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2023-10-16 with total page 937 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).
Book Synopsis Advances in Applications of Data-Driven Computing by : Jagdish Chand Bansal
Download or read book Advances in Applications of Data-Driven Computing written by Jagdish Chand Bansal and published by Springer Nature. This book was released on 2021-04-16 with total page 187 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book aims to foster machine and deep learning approaches to data-driven applications, in which data governs the behaviour of applications. Applications of Artificial intelligence (AI)-based systems play a significant role in today’s software industry. The sensors data from hardware-based systems making a mammoth database, increasing day by day. Recent advances in big data generation and management have created an avenue for decision-makers to utilize these huge volumes of data for different purposes and analyses. AI-based application developers have long utilized conventional machine learning techniques to design better user interfaces and vulnerability predictions. However, with the advancement of deep learning-based and neural-based networks and algorithms, researchers are able to explore and learn more about data and their exposed relationships or hidden features. This new trend of developing data-driven application systems seeks the adaptation of computational neural network algorithms and techniques in many application domains, including software systems, cyber security, human activity recognition, and behavioural modelling. As such, computational neural networks algorithms can be refined to address problems in data-driven applications. Original research and review works with model and build data-driven applications using computational algorithm are included as chapters in this book.
Book Synopsis Data-Driven Science and Engineering by : Steven L. Brunton
Download or read book Data-Driven Science and Engineering written by Steven L. Brunton and published by Cambridge University Press. This book was released on 2022-05-05 with total page 615 pages. Available in PDF, EPUB and Kindle. Book excerpt: A textbook covering data-science and machine learning methods for modelling and control in engineering and science, with Python and MATLAB®.
Book Synopsis Building Intelligent .NET Applications by : Sara Morgan
Download or read book Building Intelligent .NET Applications written by Sara Morgan and published by Addison-Wesley Professional. This book was released on 2005 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: Demonstrating how to enhance both new and existing .NET applications with powerful new artificial intelligence technologies, this text uses real-world examples which readers can use as the basis for their own applications.
Book Synopsis Data-Driven Mining, Learning and Analytics for Secured Smart Cities by : Chinmay Chakraborty
Download or read book Data-Driven Mining, Learning and Analytics for Secured Smart Cities written by Chinmay Chakraborty and published by Springer Nature. This book was released on 2021-04-28 with total page 383 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides information on data-driven infrastructure design, analytical approaches, and technological solutions with case studies for smart cities. This book aims to attract works on multidisciplinary research spanning across the computer science and engineering, environmental studies, services, urban planning and development, social sciences and industrial engineering on technologies, case studies, novel approaches, and visionary ideas related to data-driven innovative solutions and big data-powered applications to cope with the real world challenges for building smart cities.
Book Synopsis Data-Driven Innovation for Intelligent Technology by : Hiram Ponce
Download or read book Data-Driven Innovation for Intelligent Technology written by Hiram Ponce and published by Springer. This book was released on 2024-04-28 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book focuses on new perspectives and applications of data-driven innovation technologies, applied artificial intelligence, applied machine learning and deep learning, data science, and topics related to transforming data into value. It includes theory and use cases to help readers understand the basics of data-driven innovation and to highlight the applicability of the technologies. It emphasizes how the data lifecycle is applied in current technologies in different business domains and industries, such as advanced materials, healthcare and medicine, resource optimization, control and automation, among others. This book is useful for anyone interested in data-driven innovation for smart technologies, as well as those curious in implementing cutting-edge technologies to solve impactful artificial intelligence, data science, and related information technology and communication problems.
Book Synopsis Data-Driven Innovation for Intelligent Technology by : Hiram Ponce
Download or read book Data-Driven Innovation for Intelligent Technology written by Hiram Ponce and published by Springer Nature. This book was released on with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Data Science by : Pallavi Vijay Chavan
Download or read book Data Science written by Pallavi Vijay Chavan and published by CRC Press. This book was released on 2022-08-15 with total page 322 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers the topic of data science in a comprehensive manner and synthesizes both fundamental and advanced topics of a research area that has now reached its maturity. The book starts with the basic concepts of data science. It highlights the types of data and their use and importance, followed by a discussion on a wide range of applications of data science and widely used techniques in data science. Key Features • Provides an internationally respected collection of scientific research methods, technologies and applications in the area of data science. • Presents predictive outcomes by applying data science techniques to real-life applications. • Provides readers with the tools, techniques and cases required to excel with modern artificial intelligence methods. • Gives the reader a variety of intelligent applications that can be designed using data science and its allied fields. The book is aimed primarily at advanced undergraduates and graduates studying machine learning and data science. Researchers and professionals will also find this book useful.
Book Synopsis Dynamic Data Driven Applications Systems by : Frederica Darema
Download or read book Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2020-11-02 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Third International Conference on Dynamic Data Driven Application Systems, DDDAS 2020, held in Boston, MA, USA, in October 2020. The 21 full papers and 14 short papers presented in this volume were carefully reviewed and selected from 40 submissions. They cover topics such as: digital twins; environment cognizant adaptive-planning systems; energy systems; materials systems; physics-based systems analysis; imaging methods and systems; and learning systems.
Book Synopsis Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications by : B Rajanarayan Prusty
Download or read book Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications written by B Rajanarayan Prusty and published by CRC Press. This book was released on 2024-05-09 with total page 253 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include: an exclusive section on essential preprocessing approaches for the data-driven model a detailed overview of data-driven model applications to power system planning and operational activities specific focus on developing forecasting models for renewable generations such as solar PV and wind power, and showcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworks This book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.
Book Synopsis Intelligent Technologies for Web Applications by : Priti Srinivas Sajja
Download or read book Intelligent Technologies for Web Applications written by Priti Srinivas Sajja and published by CRC Press. This book was released on 2016-04-19 with total page 358 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet has become an integral part of human life, yet the web still utilizes mundane interfaces to the physical world, which makes Internet operations somewhat mechanical, tedious, and less human-oriented. Filling a large void in the literature, Intelligent Technologies for Web Applications is one of the first books to focus on providing vita
Book Synopsis Intelligent Systems and Learning Data Analytics in Online Education by : Santi Caballé
Download or read book Intelligent Systems and Learning Data Analytics in Online Education written by Santi Caballé and published by Academic Press. This book was released on 2021-06-15 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Intelligent Systems and Learning Data Analytics in Online Education provides novel artificial intelligence (AI) and analytics-based methods to improve online teaching and learning. This book addresses key problems such as attrition and lack of engagement in MOOCs and online learning in general. This book explores the state of the art of artificial intelligence, software tools and innovative learning strategies to provide better understanding and solutions to the various challenges of current e-learning in general and MOOC education. In particular, Intelligent Systems and Learning Data Analytics in Online Education shares stimulating theoretical and practical research from leading international experts. This publication provides useful references for educational institutions, industry, academic researchers, professionals, developers, and practitioners to evaluate and apply. Presents the application of innovative AI techniques to collaborative learning activities Offers strategies to provide automatic and effective tutoring to students’ activities Offers methods to collect, analyze and correctly visualize learning data in educational environments
Book Synopsis Artificial Intelligence and Internet of Things Based Augmented Trends for Data Driven Systems by : Anshu Singla
Download or read book Artificial Intelligence and Internet of Things Based Augmented Trends for Data Driven Systems written by Anshu Singla and published by . This book was released on 2024-07-31 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book comprehensively discusses the role of cloud computing in artificial intelligence-based data-driven systems, and hybrid cloud computing for large data-driven applications. It further explores new approaches, paradigms, and frameworks to meet societal challenges by providing solutions for critical insights into data. The text provides internet of things-based frameworks and advanced computing techniques to deal with online/virtual systems. This book: - Covers aspects of security, authentication, and prediction for data-driven systems in heterogeneous environments. - Provide data-driven frameworks in combination with the internet of things, artificial intelligence, and computing to provide critical insights and decision-making for real-time problems. - Showcases deep learning-based computer vision algorithms for enhanced pattern detection in different domains based on data-centric approaches. - Examines the role of the internet of things and machine learning algorithms for data-driven systems. - Highlights the applications of data-driven systems and cloud computing in enhancing network performance. This book is primarily written for senior undergraduate, graduate students, and academic researchers in diverse fields including electrical engineering, electronics and communications engineering, computer science, and engineering.
Book Synopsis Artificial Intelligence for Data-Driven Medical Diagnosis by : Deepak Gupta
Download or read book Artificial Intelligence for Data-Driven Medical Diagnosis written by Deepak Gupta and published by Walter de Gruyter GmbH & Co KG. This book was released on 2021-02-08 with total page 367 pages. Available in PDF, EPUB and Kindle. Book excerpt: THE SERIES: INTELLIGENT BIOMEDICAL DATA ANALYSIS By focusing on the methods and tools for intelligent data analysis, this series aims to narrow the increasing gap between data gathering and data comprehension. Emphasis is also given to the problems resulting from automated data collection in modern hospitals, such as analysis of computer-based patient records, data warehousing tools, intelligent alarming, effective and efficient monitoring. In medicine, overcoming this gap is crucial since medical decision making needs to be supported by arguments based on existing medical knowledge as well as information, regularities and trends extracted from big data sets.
Book Synopsis Context-Aware Machine Learning and Mobile Data Analytics by : Iqbal Sarker
Download or read book Context-Aware Machine Learning and Mobile Data Analytics written by Iqbal Sarker and published by Springer Nature. This book was released on 2022-01-01 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.
