Описание: This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies. Related case studies, especially on energy systems in the steel industry are also addressed and analyzed. The case studies in this volume are entirely rooted in both classical data-driven prediction problems and industrial practice requirements. Detailed figures and tables demonstrate the effectiveness and generalization of the methods addressed, and the classifications of the addressed prediction problems come from practical industrial demands, rather than from academic categories. As such, readers will learn the corresponding approaches for resolving their industrial technical problems. Although the contents of this book and its case studies come from the steel industry, these techniques can be also used for other process industries. This book appeals to students, researchers, and professionals within the machine learning and data analysis and mining communities.
Описание: This book introduces data-driven remaining useful life prognosis techniques, and shows how to utilize the condition monitoring data to predict the remaining useful life of stochastic degrading systems and to schedule maintenance and logistics plans.
Описание: This book presents modeling methods and algorithms for data-driven prediction and forecasting of practical industrial process by employing machine learning and statistics methodologies.
Автор: Gressel, Simone Pauleen, David Taskin, Nazim Название: Management decision-making, big data and analytics ISBN: 1526492008 ISBN-13(EAN): 9781526492005 Издательство: Sage Publications Рейтинг: Цена: 7285.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: An exciting new textbook examining big data and business analytics to look at how they can help managers become more effective decision-makers.
Автор: Antoniou, Constantinos Название: Mobility Patterns, Big Data and Transport Analytics ISBN: 0128129700 ISBN-13(EAN): 9780128129708 Издательство: Elsevier Science Рейтинг: Цена: 16505.00 р. Наличие на складе: Поставка под заказ.
Описание:
Transportation modelers and analysts face new opportunities and challenges in the study of mobility patterns and transportation systems, thanks to the advent of paradigm-shifting big data. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications provides a guide to this new analytical framework related to big data, focusing on capturing, predicting, visualizing and controlling mobility patterns - a key aspect of transportation modeling.
Transportation systems analysis relies upon assumptions related to social, collective, personal, or disaggregate organization of desires expressed by the mobility of people or goods. Recent advances in information technology - such as available data from open sources, participation in media platforms, and sensor technologies - have created an environment of great change, and the potential for transportation structural reorganization. Mobility Patterns, Big Data and Transport Analytics: Tools and Applications features prominent international expert overview on these new analytical frameworks, applications, and concepts in mobility analysis and transportation systems.
The book covers in detail, mobility 'structural' analysis (and its dynamics), the extensive behavioral characteristics of transport, observability requirements and limitations for realistic transportation applications, and transportation systems analysis related to complex processes and phenomena. The book bridges the gap between big data, data science, and Transportation Systems Analysis with a study of big data's impact on mobility, and an introduction to the tools necessary to apply new techniques.
Guides readers through the paradigm-shifting opportunities and challenges of handling Big Data in transportation modeling and analytics
Covers current analytical innovations focused on capturing, predicting, visualizing, and controlling mobility patterns, while discussing future trends
Delivers an introduction to transportation-related information advances, providing a benchmark reference by world-leading experts in the field
Captures and manages mobility patterns, covering multiple purposes and alternative transport modes, in a multi-disciplinary approach
Companion website features videos showing the analyses performed, as well as test codes and data-sets, allowing readers to recreate the presented analyses and apply the highlighted techniques to their own data
This book addresses the impacts of various types of services such as infrastructure, platforms, software, and business processes that cloud computing and Big Data have introduced into business. Featuring chapters which discuss effective and efficient approaches in dealing with the inherent complexity and increasing demands in data science, a variety of application domains are covered. Various case studies by data management and analysis experts are presented in these chapters. Covered applications include banking, social networks, bioinformatics, healthcare, transportation and criminology. Highlighting the Importance of Big Data Management and Analysis for Various Applications will provide the reader with an understanding of how data management and analysis are adapted to these applications. This book will appeal to researchers and professionals in the field.
Описание: This business analytics (BA) text discusses the models based on fact-based data to measure past business performance to guide an organization in visualizing and predicting future business performance and outcomes.It provides a comprehensive overview of analytics in general with an emphasis on predictive analytics. Given the booming interest in analytics and data science, this book is timely and informative. It brings many terms, tools, and methods of analytics together.The first three chapters provide an introduction to BA, importance of analytics, types of BA—descriptive, predictive, and prescriptive—along with the tools and models. Business intelligence (BI) and a case on descriptive analytics are discussed. Additionally, the book discusses on the most widely used predictive models, including regression analysis, forecasting, data mining, and an introduction to recent applications of predictive analytics—machine learning, neural networks, and artificial intelligence. The concluding chapter discusses on the current state, job outlook, and certifications in analytics.
Автор: Agrawal Rashmi, Paprzycki Marcin, Gupta Neha Название: Big Data, IoT, and Machine Learning: Tools and Applications ISBN: 0367531216 ISBN-13(EAN): 9780367531218 Издательство: Taylor&Francis Рейтинг: Цена: 8114.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание:
The idea behind this book is to simplify the journey of aspiring readers and researchers to understand Big Data, IoT and Machine Learning. It also includes various real-time/offline applications and case studies in the fields of engineering, computer science, information security and cloud computing using modern tools.
This book consists of two sections: Section I contains the topics related to Applications of Machine Learning, and Section II addresses issues about Big Data, the Cloud and the Internet of Things. This brings all the related technologies into a single source so that undergraduate and postgraduate students, researchers, academicians and people in industry can easily understand them.
Features
Addresses the complete data science technologies workflow
Explores basic and high-level concepts and services as a manual for those in the industry and at the same time can help beginners to understand both basic and advanced aspects of machine learning
Covers data processing and security solutions in IoT and Big Data applications
Offers adaptive, robust, scalable and reliable applications to develop solutions for day-to-day problems
Presents security issues and data migration techniques of NoSQL databases
Описание: This book focuses on optimal control and systems engineering in the big data era. Part I offers reviews on optimization and control theories, and Part II examines the optimization and control applications.
Автор: Ukkusuri Название: Transportation Analytics in the Era of Big Data ISBN: 3319758616 ISBN-13(EAN): 9783319758619 Издательство: Springer Рейтинг: Цена: 13974.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: Preface.- Chapter 1. Beyond Geotagged Tweets: Exploring the Geolocalisation of Tweets for Transportation Applications.- Chapter 2. Social Media in Transportation Research and Promising Applications.- Chapter 3. Ground transportation big data analytics and third party validation - solutions for a new era of regulation and private sector innovation.- Chapter 4. A privacy-preserving urban traffic estimation system. - Chapter 5. Data, Methods, and Applications of Traffic Source Prediction. - Chapter 6. Analyzing the spatial and temporal characteristics of subway passenger flow based on smart card data.- Chapter 7. An Initial Evaluation of the Impact of Location Obfuscation Mechanisms on Geospatial Analysis.- Chapter 8. PETRA: The Personal Transport Advisor Platform and Services.- Chapter 9. Mobility Pattern Identification Based on Mobile Phone Data.
Автор: Boris Deliba?i?; Jorge E. Hern?ndez; Jason Papatha Название: Decision Support Systems V – Big Data Analytics for Decision Making ISBN: 3319185322 ISBN-13(EAN): 9783319185323 Издательство: Springer Рейтинг: Цена: 5590.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: 'Big Data' Decision Making Use Cases.- The Roles of Big Data in the Decision-Support Process: An Empirical Investigation.- Cloud Enabled Big Data Business Platform for Logistics Services: A Research and Development Agenda.- Making Sense of Governmental Activities Over Social Media: A Data-Driven Approach.- Data-Mining and Expert Models for Predicting Injury Risk in Ski Resorts.- The Effects of Performance Ratios in Predicting Corporate Bankruptcy: The Italian Case.- A Tangible Collaborative Decision Support System for Various Variants of the Vehicle Routing Problem.- Decision Support Model for Participatory Management of Water Resource.- Modeling Interactions Among Criteria in MCDM Methods: A Review.
Автор: Zhu Joe, Charles Vincent Название: Data-Enabled Analytics: Dea for Big Data ISBN: 3030751619 ISBN-13(EAN): 9783030751616 Издательство: Springer Рейтинг: Цена: 20962.00 р. Наличие на складе: Есть у поставщика Поставка под заказ.
Описание: This book explores the novel uses and potentials of Data Envelopment Analysis (DEA) under big data. Considering the vast literature on DEA, one could say that DEA has been and continues to be, a widely used technique both in performance and productivity measurement, having covered a plethora of challenges and debates within the modelling framework.
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