Making Models
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Decision-Making Models
Decision Making Models: A Perspective of Fuzzy Logic and Machine Learning presents the latest developments in the field of uncertain mathematics and decision science. The book aims to deliver a systematic exposure to soft computing techniques in fuzzy mathematics as well as artificial intelligence in the context of real-life problems and is designed to address recent techniques to solving uncertain problems encountered specifically in decision sciences. Researchers, professors, software engineers, and graduate students working in the fields of applied mathematics, software engineering, and artificial intelligence will find this book useful to acquire a solid foundation in fuzzy logic and fuzzy systems, optimization problems and artificial intelligence practices, as well as how to analyze IoT solutions with applications and develop decision making mechanisms realized under uncertainty. - Introduces mathematics of intelligent systems which provides the usage of mathematical rigor such as precise definitions, theorems, results, and proofs - Provides extended and new comprehensive methods which can be used efficiently in a fuzzy environment as well as optimization problems and related fields - Covers applications and elaborates on the usage of the developed methodology in various fields of industry such as software technologies, biomedicine, image processing, and communications
Selection of Decision-Making Models in Intergovernmental Organizations: A Poliheuristic Approach to Political Regime Type Influence
Author: Timothy Tamutana Tamunang
language: en
Publisher: Miraclaire Publishing
Release Date: 2021-03-15
Until recently, Political Psychology of International Relations has attracted very few scholars’ attention in explaining states behaviors and attitudes as a juridical person. In reality, international relations scholarly works, especially related to Intergovernmental organizations, have shown that rational, structural, and functional accounts have failed to fully capture the underline nature of these institutions. A poliheuristic approach doesn’t only solve these theoretical shortcomings but also allows for the close examination of states attitudes and behaviors in making choices that would serve as tools for expected interests. This gives a chance to retrospect: how were these bodies created, what were the environmental factors that led to their formations and the nature of founders. Since organizations are adepts of metamorphosis, it is interesting to watch their overall changes. This book present not only the existing views within the subject but also provides additional information which the author has proven to be relevant.
Human-Centric Decision-Making Models for Social Sciences
The volume delivers a wealth of effective methods to deal with various types of uncertainty inherently existing in human-centric decision problems. It elaborates on comprehensive decision frameworks to handle different decision scenarios, which help use effectively the explicit and tacit knowledge and intuition, model perceptions and preferences in a more human-oriented style. The book presents original approaches and delivers new results on fundamentals and applications related to human-centered decision making approaches to business, economics and social systems. Individual chapters cover multi-criteria (multiattribute) decision making, decision making with prospect theory, decision making with incomplete probabilistic information, granular models of decision making and decision making realized with the use of non-additive measures. New emerging decision theories being presented as along with a wide spectrum of ongoing research make the book valuable to all interested in the field of advanced decision-making. The volume, self-contained in its nature, offers a systematic exposure to the concepts, design methodologies, and detailed algorithms. A prudent balance between the theoretical studies and applications makes the material suitable for researchers and graduate students in information, computer sciences, psychology, cognitive science, economics, system engineering, operation research and management science, risk management, public and social policy.
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