Predictive Analytics for Energy Efficiency and Energy Retailing
Author: Konstantin Hopf
Publisher: University of Bamberg Press
Published: 2019-07-15
Total Pages: 283
ISBN-13: 3863096681
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Smart Meter Data Analytics
Author: Yi Wang
Publisher: Springer Nature
Published: 2020-02-24
Total Pages: 306
ISBN-13: 9811526249
DOWNLOAD EBOOKThis book aims to make the best use of fine-grained smart meter data to process and translate them into actual information and incorporated into consumer behavior modeling and distribution system operations. It begins with an overview of recent developments in smart meter data analytics. Since data management is the basis of further smart meter data analytics and its applications, three issues on data management, i.e., data compression, anomaly detection, and data generation, are subsequently studied. The following works try to model complex consumer behavior. Specific works include load profiling, pattern recognition, personalized price design, socio-demographic information identification, and household behavior coding. On this basis, the book extends consumer behavior in spatial and temporal scale. Works such as consumer aggregation, individual load forecasting, and aggregated load forecasting are introduced. We hope this book can inspire readers to define new problems, apply novel methods, and obtain interesting results with massive smart meter data or even other monitoring data in the power systems.
Retail Sales Exam Review
Author: Cybellium
Publisher: Cybellium
Published:
Total Pages: 269
ISBN-13: 1836794037
DOWNLOAD EBOOKWelcome to the forefront of knowledge with Cybellium, your trusted partner in mastering the cuttign-edge fields of IT, Artificial Intelligence, Cyber Security, Business, Economics and Science. Designed for professionals, students, and enthusiasts alike, our comprehensive books empower you to stay ahead in a rapidly evolving digital world. * Expert Insights: Our books provide deep, actionable insights that bridge the gap between theory and practical application. * Up-to-Date Content: Stay current with the latest advancements, trends, and best practices in IT, Al, Cybersecurity, Business, Economics and Science. Each guide is regularly updated to reflect the newest developments and challenges. * Comprehensive Coverage: Whether you're a beginner or an advanced learner, Cybellium books cover a wide range of topics, from foundational principles to specialized knowledge, tailored to your level of expertise. Become part of a global network of learners and professionals who trust Cybellium to guide their educational journey. www.cybellium.com
Data Analytics for Smart Grids Applications—A Key to Smart City Development
Author: Devendra Kumar Sharma
Publisher: Springer Nature
Published: 2024-01-03
Total Pages: 466
ISBN-13: 3031460928
DOWNLOAD EBOOKThis book introduces big data analytics and corresponding applications in smart grids. The characterizations of big data, smart grids as well as a huge amount of data collection are first discussed as a prelude to illustrating the motivation and potential advantages of implementing advanced data analytics in smart grids. Basic concepts and the procedures of typical data analytics for general problems are also discussed. The advanced applications of different data analytics in smart grids are addressed as the main part of this book. By dealing with a huge amount of data from electricity networks, meteorological information system, geographical information system, etc., many benefits can be brought to the existing power system and improve customer service as well as social welfare in the era of big data. However, to advance the applications of big data analytics in real smart grids, many issues such as techniques, awareness, and synergies have to be overcome. This book provides deployment of semantic technologies in data analysis along with the latest applications across the field such as smart grids.
Machine Learning Approach for Cloud Data Analytics in IoT
Author: Sachi Nandan Mohanty
Publisher: John Wiley & Sons
Published: 2021-07-14
Total Pages: 528
ISBN-13: 1119785855
DOWNLOAD EBOOKMachine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.
Cloud Computing Impact on the World
Author: Vijay Kumar Yadav
Publisher: Vijay Kumar Yadav
Published:
Total Pages: 130
ISBN-13:
DOWNLOAD EBOOK**Cloud Computing Impact on the World** is an essential guide to understanding how cloud computing has become a transformative force in today's digital age. This book offers a deep dive into the origins and evolution of cloud computing, examining the key innovations and technologies that have driven its rapid adoption. Readers will explore the major players in the industry, such as AWS, Google Cloud, and Microsoft Azure, and learn how cloud computing went from a niche concept to a global powerhouse. The book highlights cloud computing's role in driving business transformation across various industries, including retail, healthcare, finance, and manufacturing. It also delves into its economic impact, illustrating how it has enabled globalization, fostered innovation in startups, and contributed to the growth of developing economies. Beyond business and economics, the book explores the broader societal implications, from reshaping education and employment to promoting social good and sustainability. With an emphasis on security, artificial intelligence, and big data, the book provides a comprehensive overview of how cloud computing is shaping the future. **Cloud Computing Impact on the World** offers a forward-looking perspective on emerging technologies like edge computing and quantum computing, making it a must-read for anyone interested in the ongoing evolution of cloud services and their global impact.
Internet of Things and Big Data Analytics-Based Manufacturing
Author: Arun Kumar Rana
Publisher: CRC Press
Published: 2024-10-17
Total Pages: 288
ISBN-13: 1040127517
DOWNLOAD EBOOKBy enabling the conversion of traditional manufacturing systems into contemporary digitalized ones, Internet of Things (IoT) adoption in manufacturing creates huge economic prospects through reshaping industries. Modern businesses can more readily implement new data-driven strategies and deal with the pressure of international competition thanks to Industrial IoT. But as the use of IoT grows, the amount of created data rises, turning industrial data into Industrial Big Data. Internet of Things and Big Data Analytics-Based Manufacturing shows how Industrial Big Data can be produced as a result of IoT usage in manufacturing, considering sensing systems and mobile devices. Different IoT applications that have been developed are demonstrated and it is shown how genuine industrial data can be produced, leading to Industrial Big Data. This book is organized into four sections discussing IoT and technology, the future of Big Data, algorithms, and case studies demonstrating the use of IoT and Big Data in a variety of industries, including automation, industrial manufacturing, and healthcare. This reference title brings all related technologies into a single source so that researchers, undergraduate and postgraduate students, academicians, and those in the industry can easily understand the topic and further their knowledge.
A Handbook to Business Analytics
Author: Sahil Kohli
Publisher: Beyond Leer Publishing, an Imprint of Kohli Media LLP
Published: 2023-02-14
Total Pages: 171
ISBN-13: 8195956211
DOWNLOAD EBOOKBusiness Analytics has become a crucial aspect of decision-making in the modern business world. With the availability of vast amounts of Data and the increasing use of technology, organizations are now relying more than ever on data-driven insights to drive growth and gain a competitive advantage. In "A Handbook to Business Analytics," authors Sahil Kohli and Deepanshi Wadhwa present a comprehensive guide to understanding the principles and practices of Business Analytics. The book covers a wide range of topics, from the basics of Data Collection and Analysis to Visualisation and Decision Analysis. With clear explanations and practical examples, this handbook is designed to be accessible to readers with little or no prior experience in the field. Whether you are a student, professional, or entrepreneur, this book will provide you with the knowledge and skills you need to make informed decisions based on data. By the end of this handbook, you will have a deep understanding of the role of Analytics in Business, the various tools and techniques available for Data Analysis, and how to apply these techniques to real-world business problems. Whether you are looking to build a career in Business Analytics or simply want to gain a competitive advantage in your current role, this book is an essential resource for anyone interested in using Data to drive Business success.
Green Computing and Predictive Analytics for Healthcare
Author: Sourav Banerjee
Publisher: CRC Press
Published: 2020-12-10
Total Pages: 205
ISBN-13: 1000223949
DOWNLOAD EBOOKGreen Computing and Predictive Analytics for Healthcare excavates the rudimentary concepts of Green Computing, Big Data and the Internet of Things along with the latest research development in the domain of healthcare. It also covers various applications and case studies in the field of computer science with state-of-the-art tools and technologies. The rapid growth of the population is a challenging issue in maintaining and monitoring various experiences of quality of service in healthcare. The coherent usage of these limited resources in connection with optimum energy consumption has been becoming more important. The major healthcare nodes are gradually becoming Internet of Things-enabled, and sensors, work data and the involvement of networking are creating smart campuses and smart houses. The book includes chapters on the Internet of Things and Big Data technologies. Features: Biomedical data monitoring under the Internet of Things Environment data sensing and analyzing Big data analytics and clustering Machine learning techniques for sudden cardiac death prediction Robust brain tissue segmentation Energy-efficient and green Internet of Things for healthcare applications Blockchain technology for the healthcare Internet of Things Advanced healthcare for domestic medical tourism system Edge computing for data analytics This book on Green Computing and Predictive Analytics for Healthcare aims to promote and facilitate the exchange of research knowledge and findings across different disciplines on the design and investigation of healthcare data analytics. It can also be used as a textbook for a master’s course in biomedical engineering. This book will also present new methods for medical data evaluation and the diagnosis of different diseases to improve quality-of-life in general and for better integration of Internet of Things into society. Dr. Sourav Banerjee is an Assistant Professor at the Department of Computer Science and Engineering of Kalyani Government Engineering College, Kalyani, West Bengal, India. His research interests include Big Data, Cloud Computing, Distributed Computing and Mobile Communications. Dr. Chinmay Chakraborty is an Assistant Professor at the Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, India. His main research interests include the Internet of Medical Things, WBAN, Wireless Networks, Telemedicine, m-Health/e-Health and Medical Imaging. Dr. Kousik Dasgupta is an Assistant Professor at the Department of Computer Science and Engineering, Kalyani Government Engineering College, India. His research interests include Computer Vision, AI/ML, Cloud Computing, Big Data and Security.
Data Analytics, Computational Statistics, and Operations Research for Engineers
Author: Debabrata Samanta
Publisher: CRC Press
Published: 2022-03-24
Total Pages: 275
ISBN-13: 1000550427
DOWNLOAD EBOOKWith the rapidly advancing fields of Data Analytics and Computational Statistics, it’s important to keep up with current trends, methodologies, and applications. This book investigates the role of data mining in computational statistics for machine learning. It offers applications that can be used in various domains and examines the role of transformation functions in optimizing problem statements. Data Analytics, Computational Statistics, and Operations Research for Engineers: Methodologies and Applications presents applications of computationally intensive methods, inference techniques, and survival analysis models. It discusses how data mining extracts information and how machine learning improves the computational model based on the new information. Those interested in this reference work will include students, professionals, and researchers working in the areas of data mining, computational statistics, operations research, and machine learning.
