17 Best Books on Decision Modelling

We have compiled a list of the Best Reference Books on Decision Modelling, which are used by students of top universities, and colleges. This will help you choose the right book depending on if you are a beginner or an expert. Here is the complete list of Decision Modelling Books with their authors, publishers, and an unbiased review of them as well as links to the Amazon website to directly purchase them. If permissible, you can also download the free PDF books on Decision Modelling below.

1. Advance Decision Modelling

 
1."Advances in Decision Analysis (Mathematical Modelling: Theory and Applications)" by M R Roubens and Nadine Meskens
“Advances in Decision Analysis: 4 (Mathematical Modelling: Theory and Applications)” Book Review: This book has its origins in the 1997 International Conference on Methods and Applications of Multiple Criteria Decision Making, where a selection of papers were chosen through a refereeing process and authors were asked to include their latest results in their final version. Raynaud’s paper addresses long-term issues in Multiple Criteria Decision Making through a Delphi process that was conducted before and during the conference. In the second part of the book, the authors discuss methodological aspects of decision theory, with Bouyssou and Pirlot proposing the reformulation of traditional conjoint estimation models to consider non-transitive, non-complete, and non-additive decomposable conjoint models. They define properties that describe such models.

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2."New Advances in Intelligent Decision Technologies: Results of the First KES International Symposium IDT'09 (Studies in Computational Intelligence)" by Gloria Phillips-Wren
“New Advances in Intelligent Decision Technologies: Results of the First KES International Symposium IDT’09 (Studies in Computational Intelligence (199))” Book Review: The book presents the results of the First KES International Symposium IDT’09. The book covers a wide range of topics related to intelligent decision technologies, including intelligent agents, fuzzy logic, multi-agent systems, artificial neural networks, genetic algorithms, and expert systems. The book showcases the latest research and developments in these areas and demonstrates how these technologies can be applied in different domains such as finance, healthcare, and military applications. This book is a valuable resource for researchers, practitioners, and students interested in intelligent decision technologies

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3."Intelligent Spatial Decision Support Systems (Advances in Spatial Science)" by Y Leung and N T Shatin
“Intelligent Spatial Decision Support Systems (Advances in Spatial Science)” Book Review: The aim of this book is to present a comprehensive framework for intelligent spatial decision-making support systems from various perspectives, including rationality, hypothetical scenarios, advancement of the framework, and its practical applications. The author deviates from traditional approaches that solely focus on the integration of model and data, and instead prioritizes an artificial intelligence approach to spatial decision support. The book argues that systems capable of performing logical reasoning are essential to spatial decision support, in addition to models. The book delves into the fundamental concepts of information representation and inference in spatial decision support systems, exploring both representative and distributed approaches. It also discusses the use of genetic algorithms for automated data acquisition.

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4."Advances in Dynamical Systems and Control (Studies in Systems, Decision and Control)" by Victor A Sadovnichiy and Mikhail Z Zgurovsky
“Advances in Dynamical” Book Review: This book focuses on recent advancements and covers both theoretical foundations and various applications. It introduces modern mathematical modeling approaches for the qualitative and quantitative analysis of solutions to complex engineering problems in disciplines such as physics, mechanics, biochemistry, geophysics, chemistry, and climatology. Contributions from an international team of esteemed authors bridge the gap between abstract mathematical methods such as applied techniques for current analysis, algebra, integral and computational mechanics, nonautonomous and stochastic dynamical systems on the one hand, and practical applications in nonlinear mechanics, optimization, dynamic theory, and control theory on the other. Therefore, this book is of interest to mathematicians and engineers working at the interface of these fields.

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5."Decision Modelling for Health Economic Evaluation (Handbooks in Health Economic Evaluation)" by Mark Sculpher and Karl Claxton
“Decision Modelling for Health Economic Evaluation (Handbooks in Health Economic Evaluation)” Book Review: This book describes decision modeling techniques for healthcare interventions to determine their cost-effectiveness. The book emphasizes the importance of properly representing uncertainty in the evaluation process and its implications for decision-making and future research. The book provides practical guidance on modeling methods, starting with the basics of developing various types of models and input parameter estimates, analyzing the results, and advancing to a comprehensive view of models as an essential tool for informing future research. The book includes case studies and exercises, supported by online templates and solutions. It is intended for health economists in academia, the pharmaceutical industry, and the healthcare sector, as well as for those in advanced health economics courses and related fields.

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6."Spreadsheet Modelling and Decision Analysis" by Cliff T Ragsdale
“Spreadsheet Modeling and Decision Analysis” Book Review: The fourth edition of the book includes the successful elements and theories from previous versions. It has added new topics and models that are relevant to current business dynamics. The book provides guidance on commonly used administration science methods and how to use them in Microsoft Excel for Windows. It also focuses on developing both mathematical and spreadsheet modeling skills.

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7."Fuzzy Preference Modelling and Multicriteria Decision Support (Theory and Decision Library D:)" by J C Fodor and M R Roubens
“Fuzzy Preference Modelling and Multicriteria Decision Support: 14 (Theory and Decision Library D:)” Book Review: The book discusses how combining three-sided principles from stochastic geometry and fuzzy sets has resulted in significant progress in mathematics. It investigates the use of functional equations to model fuzzy relations and preference orderings, applying these techniques to concepts such as equivalence relations. The book highlights a multivalued extension of a well-known finding that a relationship expressing weak preference can be separated into three components: strict preference, indifference, and incomparability. This has had a profound influence on further advancements in fuzzy set theory, increasing its acceptance in the mathematics community.

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8."Modelling for Financial Decisions: Proceedings of the 5th Meeting of the EURO Working Group" by Jaap Spronk and Benedetto Matarazzo
“Modelling for Financial Decisions: Proceedings of the 5th Meeting of the EURO Working Group on “Financial Modelling” held in Catania, 20–21 April, 1989 (Studies in Financial Modelling)” Book Review: This book is designed to provide financial leaders, such as financial officers, professional investors, and bank managers, with a range of tools for decision-making. It covers a broad range of applications using techniques from various fields such as econometrics, operations research, and financial science. The focus is on developing decision-making tools for financial decision-making and support systems. The role of the decision-maker is emphasized, both in the development and in the use of decision support systems. Advances in computer hardware and software have made it easier to design personalized decision support systems. Financial modeling bridges the gap between theoretical financial knowledge and practical application.

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9."Large-Scale Modelling and Interactive Decision Analysis: Proceedings of a Workshop sponsored by IIASA" by Günter Fandel and Manfred Grauer
“Large-Scale Modelling and Interactive Decision Analysis: Proceedings of a Workshop sponsored by IIASA (International Institute for Applied Systems Notes in Economics and Mathematical Systems)” Book Review: This book is a report on the outcomes of an International Workshop on Large-Scale Modeling and Interactive Decision Analysis. The workshop was organized jointly by the System and Decision Sciences Program of the International Institute for Applied Systems Analysis (IIASA) in Laxenburg, Austria, and the Institute for Informatics of the Academy of Sciences of the GDR in Berlin, GDR. Over fifty researchers from thirteen countries took part, and the workshop was held at the famous Wartburg Castle near Eisenach, where Martin Luther translated the Bible into German. The aim of the workshop was to discuss practical and methodological issues related to the modeling of large-scale systems and new approaches to decision analysis using advanced data processing systems. This workshop is part of a series of conferences organized by or in collaboration with IIASA, which have been previously announced in the Lecture Notes In Economics and Mathematical Systems (Vol. 229 and Vol. 246).

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10."Decision Making and Modelling in Cognitive Science" by Sisir Roy
“Decision Making and Modelling in Cognitive Science” Book Review: The book talks about using quantum ontology to measure cognitive processes, instead of classical probability theory, which is inadequate for modelling the human cognitive domain. It explores how cognition depends on context and neurons. The author suggests that decision-making and state of mind are similar to equanimity and neutral mind in Buddhism. The book also proposes that quantum ontology can be a useful tool for modelling in other fields of science.

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11."From Product Description to Cost: A Practical Approach: Volume 1: The Parametric Approach (Decision Engineering)" by Pierre Marie Maurice Foussier
“From Product Description to Cost: A Practical Approach: Volume 1: The Parametric Approach (Decision Engineering)” Book Review: The book is structured into four parts, with the first part providing an introduction to Parametrics, including cost estimation and measurement. The second part focuses on data preparation, such as data collection and economics, cost improvement curves, and plant capacity and loads. The third part delves into General Models and how to build and utilize them. The final part explores the use of models, including specific and general models, risk analysis, and auditing Parametrics. The book is suitable for anyone involved in cost estimating and includes real-life examples to aid in understanding.

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12."Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science)" by Rand R Wilcox
“Introduction to Robust Estimation and Hypothesis Testing (Statistical Modeling and Decision Science)” Book Review: The focus of this book is on contemporary statistical methods, including a comparison between these methods and conventional approaches like ANOVA and regression. The book offers a combination of theoretical advancements, statistical models, and computational techniques, as well as practical strategies for problem-solving. Additionally, a free software tool built in S-PLUS is provided. This book is intended for those engaged in statistical modeling and decision science.

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2. Statistical Decision Modelling

 
1."Statistical Decision Theory and Related Topics V" by Shanti S Gupta and James O Berger
“Statistical Decision Theory and Related Topics V” Book Review: The target audience for this book includes students, researchers, and scientists. The book covers a range of topics such as Bayesian analysis, asymptotics, nonparametrics, probability, and probabilistic structures. Additionally, it explains sequential, adaptive, and filtering problems. Each chapter concludes with solved examples, exercises, and short questions.

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2."Data Mining and Predictive Analytics" by Daniel T Larose and Chantal D Larose
“Data Mining and Predictive Analytics” Book Review: The intended audience of this book includes computer engineering students, researchers, and scientists, and it covers topics such as association rules, clustering, neural networks, and multivariate analysis. In addition to theoretical concepts, the book also provides practical applications and data mining methods. The focus of the book is to introduce data mining, and it includes solved examples, exercises, and short questions at the end of each chapter.

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3."Meta-analysis by the Confidence Profile Method" by David M Eddy
“Meta-analysis by the Confidence Profile Method” Book Review: The target audience of this book includes agricultural engineering students, researchers, and scientists. The focus of the book is on the methods utilized in meta-analysis and the techniques used to interpret experiments in meta-analysis. The book also explores factors that impact the comparability or applicability of meta-analysis. Additionally, the book provides examples, exercises, and short questions at the end of each chapter.

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4."Statistical Inference: Theory and Practice (Theory and Decision Library B)" by Tadeusz Bromek and Elzbieta Pleszczynska
“Statistical Inference: Theory and Practice (Theory and Decision Library B)” Book Review: The book targets students, researchers, and scientists, emphasizing the proper use of statistics and how to avoid its misuse. It highlights the stages of statistical problem formalization and provides practical applications of statistical inference. Additionally, the book offers solved examples, exercises, and short questions at the end of each chapter.

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5."Decision Theory and Multi-Agent Planning (CISM International Centre for Mechanical Sciences)" by Giacomo Della Riccia and Didier Dubois
“Decision Theory and Multi-Agent Planning (CISM International Centre for Mechanical Sciences)” Book Review: This book is for students, researchers, and scientists who are interested in learning about multi-agent planning theory, mechanics, decision-support, and planning. Each chapter contains solved examples, exercises, and short questions at the end.

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We have put a lot of effort into researching the best books on Decision Modelling and came out with a recommended list and their reviews. If any more book needs to be added to this list, please email us. We are working on free pdf downloads for books on Decision Modelling and will publish the download link here. Fill out this Decision Modelling books pdf download" request form for download notification.

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