This book presents a systematic review of multidimensional normalization methods and addresses problems frequently encountered when using various methods and ways to eliminate them.
The invariant properties of the linear normalization methods presented here can be used to eliminate simple problems and avoid obvious errors when choosing a normalization method. The book introduces valuable, novel techniques for the multistep normalization of multidimensional data. One of these methods involves inverting the normalized values of cost attributes into profit attributes based on...
This book presents a systematic review of multidimensional normalization methods and addresses problems frequently encountered when using various m...
With a focus on cargo transportation, this book addresses the development of approaches intended to secure an infrastructure of smart services to support the adaptive implementation of online multi-modal freight transport management processes. It discusses the development of multi-criteria decision-making components and their integration into the multi-layered computer-based information management of intelligent systems.
Through detailed descriptions of various components of intelligent transport management systems, the book demonstrates how to develop the services needed in...
With a focus on cargo transportation, this book addresses the development of approaches intended to secure an infrastructure of smart services to s...
This book introduces readers to advanced data science techniques for signal mining in connection with agriculture. It shows how to apply heuristic modeling to improve farm-level efficiency, and how to use sensors and data intelligence to provide closed-loop feedback, while also providing recommendation techniques that yield actionable insights.
The book also proposes certain macroeconomic pricing models, which data-mine macroeconomic signals and the influence of global economic trends on small-farm sustainability to provide actionable insights to farmers, helping them avoid...
This book introduces readers to advanced data science techniques for signal mining in connection with agriculture. It shows how to apply heuristic ...
This book covers central issues in mitigating supply chain risks from various perspectives. Today’s supply chains are vulnerable to disruptions that can have a significant impact on firms, business and performance. The aim of supply chain risk management is to identify the potential sources of risks and implement appropriate actions in order to mitigate supply chain disruptions. In this regard, the book presents a wealth of methods, strategies and analyses that are essential for mitigating supply chain risks.
As a comprehensive collection of the latest research and cutting-edge...
This book covers central issues in mitigating supply chain risks from various perspectives. Today’s supply chains are vulnerable to disruptions t...
This book analyzes cyberdefense from a novel and interdisciplinary perspective, offering solutions for problems that have long impeded a more efficient defense. It explains why cyberdefense organized and performed by humans is too slow, too cumbersome, and too ineffective.
Combining the analytical capabilities of experts in operations research and management, international security studies, economics, risk analysis, and defense management, the volume addresses these problems of current cyberdefense. The authors present suggestions for the next generation of...
This book analyzes cyberdefense from a novel and interdisciplinary perspective, offering solutions for problems that have long impeded a more efficien...
This second edition systematically presents the underlying theory, model development, and applications of network Data Envelopment Analysis (DEA). It discusses the models used to measure the efficiency of systems in specific network structures and introduces readers to the latest applications. It demonstrates how the “network DEA” approach helps identify and manage the specific components that cause inefficiencies in the overall system. The existing models for measuring the efficiency of systems in specific network structures are also discussed, and the relationships between system...
This second edition systematically presents the underlying theory, model development, and applications of network Data Envelopment Analysis (DEA). ...
This edited volume presents state-of-the-art research that can leverage large-scale sensory data collected in grocery/retail stores where a single customer visit may generate nearly 10,000 data points. For decades, retail shelf space optimization has been confined to the analysis of product allocation decisions over a limited number of shelves, often taken in isolation. Such models incorporated interesting concepts relating to space and cross-space elasticity in the design of planograms. Although useful, these models have not addressed the bigger picture of planning store shelf space in a...
This edited volume presents state-of-the-art research that can leverage large-scale sensory data collected in grocery/retail stores where a single cus...
This book explains and illustrates recent developments and advances in decision-making and risk analysis. It demonstrates how artificial intelligence (AI) and machine learning (ML) have not only benefitted from classical decision analysis concepts such as expected utility maximization but have also contributed to making normative decision theory more useful by forcing it to confront realistic complexities. These include skill acquisition, uncertain and time-consuming implementation of intended actions, open-world uncertainties about what might happen next and what consequences actions can...
This book explains and illustrates recent developments and advances in decision-making and risk analysis. It demonstrates how artificial intelligen...
This book highlights research on the behavioral biases affecting judgmental accuracy in judgmental forecasting and showcases the state-of-the-art in judgment-based predictive analytics. In recent years, technological advancements have made it possible to use predictive analytics to exploit highly complex (big) data resources. Consequently, modern forecasting methodologies are based on sophisticated algorithms from the domain of machine learning and deep learning. However, research shows that in the majority of industry contexts, human judgment remains an indispensable component of the...
This book highlights research on the behavioral biases affecting judgmental accuracy in judgmental forecasting and showcases the state-of-the-art i...
This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are essential in today’s world. Healthcare management faces a number of challenges, e.g. reducing patient growth through disease prevention, stopping or slowing disease progression, and reducing healthcare costs while improving quality of care. The book provides an overview of current healthcare management problems and highlights how analytics and knowledge management have been used to better cope with them. It then demonstrates how to use descriptive...
This book presents data mining methods in the field of healthcare management in a practical way. Healthcare quality and disease prevention are esse...
