Modeling Decisions

Modeling Decisions
Title Modeling Decisions PDF eBook
Author Vicenç Torra
Publisher Springer Science & Business Media
Pages 284
Release 2007-05-11
Genre Computers
ISBN 3540687912

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This book covers the underlying science and application issues related to aggregation operators, focusing on tools used in practical applications that involve numerical information. It will thus be required reading for engineers, statisticians and computer scientists of all kinds. Starting with detailed introductions to information fusion and integration, measurement and probability theory, fuzzy sets, and functional equations, the authors then cover numerous topics in detail, including the synthesis of judgements, fuzzy measures, weighted means and fuzzy integrals.

Real-World Decision Modeling with DMN

Real-World Decision Modeling with DMN
Title Real-World Decision Modeling with DMN PDF eBook
Author James Taylor
Publisher Jtonedm
Pages 0
Release 2023-07-24
Genre
ISBN

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Organizations make thousands of automated, operational decisions every week. How well they make these decisions drives profitability, reputation and customer satisfaction. Decision modeling helps them understand, automate and improve them

Decision Modelling for Health Economic Evaluation

Decision Modelling for Health Economic Evaluation
Title Decision Modelling for Health Economic Evaluation PDF eBook
Author Andrew Briggs
Publisher OUP Oxford
Pages 269
Release 2006-08-17
Genre Medical
ISBN 0191004952

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In financially constrained health systems across the world, increasing emphasis is being placed on the ability to demonstrate that health care interventions are not only effective, but also cost-effective. This book deals with decision modelling techniques that can be used to estimate the value for money of various interventions including medical devices, surgical procedures, diagnostic technologies, and pharmaceuticals. Particular emphasis is placed on the importance of the appropriate representation of uncertainty in the evaluative process and the implication this uncertainty has for decision making and the need for future research. This highly practical guide takes the reader through the key principles and approaches of modelling techniques. It begins with the basics of constructing different forms of the model, the population of the model with input parameter estimates, analysis of the results, and progression to the holistic view of models as a valuable tool for informing future research exercises. Case studies and exercises are supported with online templates and solutions. This book will help analysts understand the contribution of decision-analytic modelling to the evaluation of health care programmes. ABOUT THE SERIES: Economic evaluation of health interventions is a growing specialist field, and this series of practical handbooks will tackle, in-depth, topics superficially addressed in more general health economics books. Each volume will include illustrative material, case histories and worked examples to encourage the reader to apply the methods discussed, with supporting material provided online. This series is aimed at health economists in academia, the pharmaceutical industry and the health sector, those on advanced health economics courses, and health researchers in associated fields.

Probability Models for Economic Decisions, second edition

Probability Models for Economic Decisions, second edition
Title Probability Models for Economic Decisions, second edition PDF eBook
Author Roger B. Myerson
Publisher MIT Press
Pages 569
Release 2019-12-17
Genre Business & Economics
ISBN 0262355604

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An introduction to the use of probability models for analyzing risk and economic decisions, using spreadsheets to represent and simulate uncertainty. This textbook offers an introduction to the use of probability models for analyzing risks and economic decisions. It takes a learn-by-doing approach, teaching the student to use spreadsheets to represent and simulate uncertainty and to analyze the effect of such uncertainty on an economic decision. Students in applied business and economics can more easily grasp difficult analytical methods with Excel spreadsheets. The book covers the basic ideas of probability, how to simulate random variables, and how to compute conditional probabilities via Monte Carlo simulation. The first four chapters use a large collection of probability distributions to simulate a range of problems involving worker efficiency, market entry, oil exploration, repeated investment, and subjective belief elicitation. The book then covers correlation and multivariate normal random variables; conditional expectation; optimization of decision variables, with discussions of the strategic value of information, decision trees, game theory, and adverse selection; risk sharing and finance; dynamic models of growth; dynamic models of arrivals; and model risk. New material in this second edition includes two new chapters on additional dynamic models and model risk; new sections in every chapter; many new end-of-chapter exercises; and coverage of such topics as simulation model workflow, models of probabilistic electoral forecasting, and real options. The book comes equipped with Simtools, an open-source, free software used througout the book, which allows students to conduct Monte Carlo simulations seamlessly in Excel.

Modeling Decisions for Artificial Intelligence

Modeling Decisions for Artificial Intelligence
Title Modeling Decisions for Artificial Intelligence PDF eBook
Author Vicenc Torra
Publisher Springer Science & Business Media
Pages 340
Release 2004-07-22
Genre Computers
ISBN 3540225552

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This book constitutes the refereed proceedings of the First International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2004, held in Barcelona, Spain in August 2004. The 26 revised full papers presented together with 4 invited papers were carefully reviewed and selected from 53 submissions. The papers are devoted to topics like models for information fusion, aggregation operators, model selection, fuzzy integrals, fuzzy sets, fuzzy multisets, neural learning, rule-based classification systems, fuzzy association rules, algorithmic learning, diagnosis, text categorization, unsupervised aggregation, the Choquet integral, group decision making, preference relations, vague knowledge processing, etc.

Data, Models, and Decisions

Data, Models, and Decisions
Title Data, Models, and Decisions PDF eBook
Author Dimitris Bertsimas
Publisher Ingram
Pages 530
Release 2004
Genre Business & Economics
ISBN 9780975914601

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Combines topics from two traditionally distinct quantitative subjects, probability/statistics and management science/optimization, in a unified treatment of quantitative methods and models for management. Stresses those fundamental concepts that are most important for the practical analysis of management decisions: modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision-making, using historical data and limited information effectively, simulating complex systems, and allocating scarce resources optimally.

Modeling Decisions for Artificial Intelligence

Modeling Decisions for Artificial Intelligence
Title Modeling Decisions for Artificial Intelligence PDF eBook
Author Vincenc Torra
Publisher Springer Science & Business Media
Pages 384
Release 2006-03-20
Genre Computers
ISBN 3540327800

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This book constitutes the refereed proceedings of the Third International Conference on Modeling Decisions for Artificial Intelligence, MDAI 2006, held in Tarragona, Spain, in April 2006. The 31 revised full papers presented together with 4 invited lectures were thoroughly reviewed and selected from 97 submissions. The papers are devoted to theory and tools for modeling decisions, as well as applications that encompass decision making processes and information fusion techniques.