Difference Between Deterministic And Probabilistic
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Cognitive Processes in Choice and Decision Behavior
Author: Thomas S. Wallsten
language: en
Publisher: Taylor & Francis
Release Date: 2024-05-01
Decision theory is a uniquely interdisciplinary field of study with contributions from economics, statistics, mathematics, philosophy, operations research, and psychology. The 1970s had seen important changes in research on behavioral decision theory in terms of a shift from a reliance on economic and statistical models to an emphasis on concepts drawn from cognitive psychology. Originally published in 1980, Cognitive Processes in Choice and Decision Behavior contains papers that explore the reasons why these changes had come about and discuss the future directions to which they pointed. It was clear at the time that research in behavioral decision theory was changing dramatically. The chapters in this book represent a good assessment of the reasons the changes were coming about and some of the merits and problems of the directions in which it was moving. Today it can be read in its historical context.
Probabilistic Reliability Analysis of Power Systems
This textbook provides an introduction to probabilistic reliability analysis of power systems. It discusses a range of probabilistic methods used in reliability modelling of power system components, small systems and large systems. It also presents the benefits of probabilistic methods for modelling renewable energy sources. The textbook describes real-life studies, discussing practical examples and providing interesting problems, teaching students the methods in a thorough and hands-on way. The textbook has chapters dedicated to reliability models for components (reliability functions, component life cycle, two-state Markov model, stress-strength model), small systems (reliability networks, Markov models, fault/event tree analysis) and large systems (generation adequacy, state enumeration, Monte-Carlo simulation). Moreover, it contains chapters about probabilistic optimal power flow, the reliability of underground cables and cyber-physical power systems. After reading this book, engineering students will be able to apply various methods to model the reliability of power system components, smaller and larger systems. The textbook will be accessible to power engineering students, as well as students from mathematics, computer science, physics, mechanical engineering, policy & management, and will allow them to apply reliability analysis methods to their own areas of expertise.
Introduction to Quantum Algorithms
Author: Johannes A. Buchmann
language: en
Publisher: American Mathematical Society
Release Date: 2024-03-18
Quantum algorithms are among the most important, interesting, and promising innovations in information and communication technology. They pose a major threat to today's cybersecurity and at the same time promise great benefits by potentially solving previously intractable computational problems with reasonable effort. The theory of quantum algorithms is based on advanced concepts from computer science, mathematics, and physics. Introduction to Quantum Algorithms offers a mathematically precise exploration of these concepts, accessible to those with a basic mathematical university education, while also catering to more experienced readers. This comprehensive book is suitable for self-study or as a textbook for one- or two-semester introductory courses on quantum computing algorithms. Instructors can tailor their approach to emphasize theoretical understanding and proofs or practical applications of quantum algorithms, depending on the course's goals and timeframe.