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Author: Tao-Sheng Wang Publisher: Springer Nature ISBN: 9811535884 Category : Technology & Engineering Languages : en Pages : 758
Book Description
This book discusses an emerging field of decision science that focuses on business processes and systems used to extract knowledge from large volumes of data to provide significant insights for crucial decisions in critical situations. It presents studies employing computing techniques like machine learning, which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets, leadership, and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the 2nd International Conference on Decision Science and Management (ICDSM 2019), held at Hunan International Economics University, China, on 20–21 September 2019.
Author: Tao-Sheng Wang Publisher: Springer Nature ISBN: 9811535884 Category : Technology & Engineering Languages : en Pages : 758
Book Description
This book discusses an emerging field of decision science that focuses on business processes and systems used to extract knowledge from large volumes of data to provide significant insights for crucial decisions in critical situations. It presents studies employing computing techniques like machine learning, which explore decision-making for cross-platforms that contain heterogeneous data associated with complex assets, leadership, and team coordination. It also reveals the advantages of using decision sciences with management-oriented problems. The book includes a selection of the best papers presented at the 2nd International Conference on Decision Science and Management (ICDSM 2019), held at Hunan International Economics University, China, on 20–21 September 2019.
Author: Faisal Saeed Publisher: Springer ISBN: 3319990071 Category : Technology & Engineering Languages : en Pages : 1133
Book Description
This book presents the proceedings of the 3rd International Conference of Reliable Information and Communication Technology 2018 (IRICT 2018), which was held in Kuala Lumpur, Malaysia, on July 23–24, 2018. The main theme of the conference was “Data Science, AI and IoT Trends for the Fourth Industrial Revolution.” A total of 158 papers were submitted to the conference, of which 103 were accepted and considered for publication in this book. Several hot research topics are covered, including Advances in Data Science and Big Data Analytics, Artificial Intelligence and Soft Computing, Business Intelligence, Internet of Things (IoT) Technologies and Applications, Intelligent Communication Systems, Advances in Computer Vision, Health Informatics, Reliable Cloud Computing Environments, Recent Trends in Knowledge Management, Security Issues in the Cyber World, and Advances in Information Systems Research, Theories and Methods.
Author: Zdzislaw Polkowski Publisher: CRC Press ISBN: 1000520846 Category : Technology & Engineering Languages : en Pages : 159
Book Description
This book brings insight into data science and offers applications and implementation strategies. It includes current developments and future directions and covers the concept of data science along with its origins. It focuses on the mechanisms of extracting data along with classifications, architectural concepts, and business intelligence with predictive analysis. Data Science in Engineering and Management: Applications, New Developments, and Future Trends introduces the concept of data science, its use, and its origins, as well as presenting recent trends, highlighting future developments; discussing problems and offering solutions. It provides an overview of applications on data linked to engineering and management perspectives and also covers how data scientists, analysts, and program managers who are interested in productivity and improving their business can do so by incorporating a data science workflow effectively. This book is useful to researchers involved in data science and can be a reference for future research. It is also suitable as supporting material for undergraduate and graduate-level courses in related engineering disciplines.
Author: Taser, Pelin Yildirim Publisher: IGI Global ISBN: 1799841871 Category : Computers Languages : en Pages : 334
Book Description
The internet of things (IoT) has emerged to address the need for connectivity and seamless integration with other devices as well as big data platforms for analytics. However, there are challenges that IoT-based applications face including design and implementation issues; connectivity problems; data gathering, storing, and analyzing in cloud-based environments; and IoT security and privacy issues. Emerging Trends in IoT and Integration with Data Science, Cloud Computing, and Big Data Analytics is a critical reference source that provides theoretical frameworks and research findings on IoT and big data integration. Highlighting topics that include wearable sensors, machine learning, machine intelligence, and mobile computing, this book serves professionals who want to improve their understanding of the strategic role of trust at different levels of the information and knowledge society. It is therefore of most value to data scientists, computer scientists, data analysts, IT specialists, academicians, professionals, researchers, and students working in the field of information and knowledge management in various disciplines that include but are not limited to information and communication sciences, administrative sciences and management, education, sociology, computer science, etc. Moreover, the book provides insights and supports executives concerned with the management of expertise, knowledge, information, and organizational development in different types of work communities and environments.
Author: Siddharth Swarup Rautaray Publisher: Springer Nature ISBN: 9813368152 Category : Computers Languages : en Pages : 341
Book Description
This book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.
Author: Louis Anthony Cox, Jr. Publisher: John Wiley & Sons ISBN: 1118217160 Category : Business & Economics Languages : en Pages : 328
Book Description
Discover recent powerful advances in the theory, methods, and applications of decision and risk analysis Focusing on modern advances and innovations in the field of decision analysis (DA), Breakthroughs in Decision Science and Risk Analysis presents theories and methods for making, improving, and learning from significant practical decisions. The book explains these new methods and important applications in an accessible and stimulating style for readers from multiple backgrounds, including psychology, economics, statistics, engineering, risk analysis, operations research, and management science. Highlighting topics not conventionally found in DA textbooks, the book illustrates genuine advances in practical decision science, including developments and trends that depart from, or break with, the standard axiomatic DA paradigm in fundamental and useful ways. The book features methods for coping with realistic decision-making challenges such as online adaptive learning algorithms, innovations in robust decision-making, and the use of a variety of models to explain available data and recommend actions. In addition, the book illustrates how these techniques can be applied to dramatically improve risk management decisions. Breakthroughs in Decision Science and Risk Analysis also includes: An emphasis on new approaches rather than only classical and traditional ideas Discussions of how decision and risk analysis can be applied to improve high-stakes policy and management decisions Coverage of the potential value and realism of decision science within applications in financial, health, safety, environmental, business, engineering, and security risk management Innovative methods for deciding what actions to take when decision problems are not completely known or described or when useful probabilities cannot be specified Recent breakthroughs in the psychology and brain science of risky decisions, mathematical foundations and techniques, and integration with learning and pattern recognition methods from computational intelligence Breakthroughs in Decision Science and Risk Analysis is an ideal reference for researchers, consultants, and practitioners in the fields of decision science, operations research, business, management science, engineering, statistics, and mathematics. The book is also an appropriate guide for managers, analysts, and decision and policy makers in the areas of finance, health and safety, environment, business, engineering, and security risk management.
Author: Salvatore Greco Publisher: Springer Science & Business Media ISBN: 1441959041 Category : Business & Economics Languages : en Pages : 421
Book Description
Multiple Criteria Decision Making (MCDM) is the study of methods and procedures by which concerns about multiple conflicting criteria can be formally incorporated into the management planning process. A key area of research in OR/MS, MCDM is now being applied in many new areas, including GIS systems, AI, and group decision making. This volume is in effect the third in a series of Springer books by these editors (all in the ISOR series), and it brings all the latest developments in MCDM into focus. Looking at developments in the applications, methodologies and foundations of MCDM, it presents research from leaders in the field on such topics as Problem Structuring Methodologies; Measurement Theory and MCDA; Recent Developments in Evolutionary Multiobjective Optimization; Habitual Domains and Dynamic MCDM in Changeable Spaces; Stochastic Multicriteria Acceptability Analysis; and many more chapters.
Author: Tetsukazu Yahara Publisher: Springer Nature ISBN: 9811586322 Category : Nature Languages : en Pages : 251
Book Description
This open access book provides a theoretical framework and case studies on decision science for regional sustainability by integrating the natural and social sciences. The cases discussed include solution-oriented transdisciplinary studies on the environment, disasters, health, governance and human cooperation. Based on these case studies and comprehensive reviews of relevant works, including lessons learned from past failures for predictable surprises and successes in adaptive co-management, the book provides the reader with new perspectives on how we can co-design collaborative projects with various conflicts of interest and how we can transform our society for a sustainable future. The book makes a valuable contribution to the global research initiative Future Earth, promoting transdisciplinary studies to bridge the gap between science and society in knowledge generation processes and supporting efforts to achieve the UN’s Sustainable Development Goals (SDGs). Compared to other publications on transdisciplinary studies, this book is unique in that evolutionary biology is used as an integrator for various areas related to human decision-making, and approaches social changes as processes of adaptive learning and evolution. Given its scope, the book is highly recommended to all readers seeking an integrated overview of human decision-making in the context of social transformation.
Author: Brojo Kishore Mishra Publisher: Bentham Science Publishers ISBN: 9815079018 Category : Computers Languages : en Pages : 260
Book Description
Data Science and Interdisciplinary Research: Recent Trends and Applications is a compelling edited volume that offers a comprehensive exploration of the latest advancements in data science and interdisciplinary research. Through a collection of 10 insightful chapters, this book showcases diverse models of machine learning, communications, signal processing, and data analysis, illustrating their relevance in various fields. Key Themes: Advanced Rainfall Prediction: Presents a machine learning model designed to tackle the challenging task of predicting rainfall across multiple countries, showcasing its potential to enhance weather forecasting. Efficient Cloud Data Clustering: Explains a novel computational approach for clustering large-scale cloud data, addressing the scalability of cloud computing and data analysis. Secure In-Vehicle Communication: Explores the critical topic of secure communication in in-vehicle networks, emphasizing message authentication and data integrity. Smart Irrigation 4.0: Details a decision model designed for smart irrigation, integrating agricultural sensor data reliability analysis to optimize water usage in precision agriculture. Smart Electricity Monitoring: Highlights machine learning-based smart electricity monitoring and fault detection systems, contributing to the development of smart cities. Enhanced Learning Environments: Investigates the effectiveness of mobile learning in higher education, shedding light on the role of technology in shaping modern learning environments. Coastal Socio-Economy Study: Presents a case study on the socio-economic conditions of coastal fishing communities, offering insights into the livelihoods and challenges they face. Signal Noise Removal: Shows filtering techniques for removing noise from ECG signals, enhancing the accuracy of medical data analysis and diagnosis. Deep Learning in Biomedical Research: Explores deep learning techniques for biomedical research, particularly in the realm of gene identification using Next Generation Sequencing (NGS) data. Medical Diagnosis through Machine Learning: Concludes with a chapter on breast cancer detection using machine learning concepts, demonstrating the potential of AI-driven diagnostics.
Author: Decision Sciences Institute. Annual Meeting Publisher: Pearson Education ISBN: 0133925374 Category : Business & Economics Languages : en Pages : 400
Book Description
Decision science offers powerful insights and techniques that help people make better decisions to improve business and society. This new volume brings together the peer-reviewed papers that have been chosen as the "best of the best" by the field's leading organization, the Decision Sciences Institute. These papers, authored by respected decision science researchers and academics from around the world, will be presented at DSI's 45th Annual Meeting in Tampa, Florida in November 2014. The first book of papers ever assembled by DSI, this volume describes recent methods and approaches in the decision sciences, with a special focus on how accelerating technological innovation is driving change in the ways organizations and individuals make decisions. These papers offer actionable insights for decision-makers of all kinds, in business, public policy, non-profit organizations, and beyond. They also point to new research directions for academic researchers in decision science worldwide.
Author: Tao-Sheng Wang
Author: Tao-Sheng Wang
Author: Faisal Saeed
Author: Zdzislaw Polkowski
Author: Taser, Pelin Yildirim
Author: Siddharth Swarup Rautaray
Author: Louis Anthony Cox, Jr.
Author: Salvatore Greco
Author: Tetsukazu Yahara
Author: Brojo Kishore Mishra
Author: Decision Sciences Institute. Annual Meeting