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The Application of Fuzzy Logic for Managerial Decision Making Processes, Andreas Meier; Edy Portmann; Kilian Stoffel; Luis


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Автор: Andreas Meier; Edy Portmann; Kilian Stoffel; Luis
Название:  The Application of Fuzzy Logic for Managerial Decision Making Processes
ISBN: 9783319853048
Издательство: Springer
Классификация:




ISBN-10: 331985304X
Обложка/Формат: Soft cover
Страницы: 103
Вес: 1.88 кг.
Дата издания: 2017
Серия: Fuzzy Management Methods
Язык: English
Издание: Softcover reprint of
Иллюстрации: 35 illustrations, black and white; xii, 103 p. 35 illus.
Размер: 23.39 x 15.60 x 0.61 cm
Читательская аудитория: General (us: trade)
Основная тема: Business and Management
Подзаголовок: Latest Research and Case Studies
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book addresses the latest research and applications of fuzzy management methods for business decisions. how fuzzy management methods support the inclusion of human thinking and human behavior in decision making processes; how to generate better results with fuzzy management methods in cases of imprecise information;


Hands-On Simulation Modeling with Python: Develop simulation models to get accurate results and enhance decision-making processes

Автор: Ciaburro Giuseppe
Название: Hands-On Simulation Modeling with Python: Develop simulation models to get accurate results and enhance decision-making processes
ISBN: 1838985093 ISBN-13(EAN): 9781838985097
Издательство: Неизвестно
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Цена: 14194.00 р.
Наличие на складе: Есть у поставщика Поставка под заказ.

Описание:

Enhance your simulation modeling skills by creating and analyzing digital prototypes of a physical model using Python programming with this comprehensive guide

Key Features

  • Learn to create a digital prototype of a real model using hands-on examples
  • Evaluate the performance and output of your prototype using simulation modeling techniques
  • Understand various statistical and physical simulations to improve systems using Python

Book Description

Simulation modeling helps you to create digital prototypes of physical models to analyze how they work and predict their performance in the real world. With this comprehensive guide, you'll understand various computational statistical simulations using Python.

Starting with the fundamentals of simulation modeling, you'll understand concepts such as randomness and explore data generating processes, resampling methods, and bootstrapping techniques. You'll then cover key algorithms such as Monte Carlo simulations and Markov decision processes, which are used to develop numerical simulation models, and discover how they can be used to solve real-world problems. As you advance, you'll develop simulation models to help you get accurate results and enhance decision-making processes. Using optimization techniques, you'll learn to modify the performance of a model to improve results and make optimal use of resources. The book will guide you in creating a digital prototype using practical use cases for financial engineering, prototyping project management to improve planning, and simulating physical phenomena using neural networks.

By the end of this book, you'll have learned how to construct and deploy simulation models of your own to overcome real-world challenges.

What you will learn

  • Gain an overview of the different types of simulation models
  • Get to grips with the concepts of randomness and data generation process
  • Understand how to work with discrete and continuous distributions
  • Work with Monte Carlo simulations to calculate a definite integral
  • Find out how to simulate random walks using Markov chains
  • Obtain robust estimates of confidence intervals and standard errors of population parameters
  • Discover how to use optimization methods in real-life applications
  • Run efficient simulations to analyze real-world systems

Who this book is for

Hands-On Simulation Modeling with Python is for simulation developers and engineers, model designers, and anyone already familiar with the basic computational methods that are used to study the behavior of systems. This book will help you explore advanced simulation techniques such as Monte Carlo methods, statistical simulations, and much more using Python. Working knowledge of Python programming language is required.

Group Decision and Negotiation: Theory, Empirical Evidence, and Application

Автор: Deepinder Bajwa; Sabine T. Koeszegi; Rudolf Vetsch
Название: Group Decision and Negotiation: Theory, Empirical Evidence, and Application
ISBN: 3319526235 ISBN-13(EAN): 9783319526232
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This book constitutes revised selected papers from the 16th International Conference on Group Decision and Negotiation, GDN 2016, held in Bellingham, WA, USA, in June 2016.

Decision Support Systems: Theory and Application

Автор: Clyde W. Holsapple; Andrew B. Whinston
Название: Decision Support Systems: Theory and Application
ISBN: 3642830900 ISBN-13(EAN): 9783642830907
Издательство: Springer
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Цена: 14673.00 р.
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Описание: Proceedings of the NATO Advanced Study Institute on Decision Support Systems: Theory and Application Held at Acquafredda di Maratea, Italy, June 3-14, 1985

Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making

Автор: Sangaiah Arun Kumar, Gao Xiao-Zhi, Abraham Ajith
Название: Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making
ISBN: 1522510087 ISBN-13(EAN): 9781522510086
Издательство: Mare Nostrum (Eurospan)
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Цена: 40055.00 р.
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Описание: Soft computing techniques are innovative tools that use nature-inspired algorithms to run predictive analysis of industries from business to software measurement. These tools have gained momentum in recent years for their practicality and flexibility.The Handbook of Research on Fuzzy and Rough Set Theory in Organizational Decision Making collects both empirical and applied research in the field of fuzzy set theory, and bridges the gap between the application of soft computational approaches and the organizational decision making process. This publication is a pivotal reference for business professionals, IT specialists, software engineers, and advanced students of business and information technology.

Markov chains and decision processes for engineers and managers

Автор: Sheskin, Theodore J. (cleveland State University, Ohio, Usa)
Название: Markov chains and decision processes for engineers and managers
ISBN: 1420051113 ISBN-13(EAN): 9781420051117
Издательство: Taylor&Francis
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Цена: 22202.00 р.
Наличие на складе: Поставка под заказ.

Описание: Presents an introduction to finite Markov chains and Markov decision processes, with applications in engineering and management. This book introduces discrete-time, finite-state Markov chains, and Markov decision processes. It describes both algorithms and applications, enabling students to understand the logical basis for the algorithms.

Bending the Law of Unintended Consequences: A Test-Drive Method for Critical Decision-Making in Organizations

Автор: Adler Richard M.
Название: Bending the Law of Unintended Consequences: A Test-Drive Method for Critical Decision-Making in Organizations
ISBN: 3030327132 ISBN-13(EAN): 9783030327132
Издательство: Springer
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Цена: 6986.00 р.
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Описание: This title provides managers, executives and other professionals with an innovative method for critical decision-making. It also provides four sample test drives of realistic critical decisions as well as two instructional videos to illustrate this new method.

Fuzzy Logic for Planning and Decision Making

Автор: Freerk A. Lootsma
Название: Fuzzy Logic for Planning and Decision Making
ISBN: 1441947795 ISBN-13(EAN): 9781441947796
Издательство: Springer
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Цена: 23757.00 р.
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Описание: Thisvolume starts with the basicconceptsof FuzzyLogic: the membership function, the intersection and the union of fuzzy sets, fuzzy numbers, and the extension principle underlying the algorithmic operations. Several chapters are devoted to applications of FuzzyLogic in various branches of Operations Research: PERT planning with uncertain activity durations, SMART and the AHP for Multi-Criteria Decision Analysis (MCDA) with vague preferential statements, ELECTRE usingthe ideasof the AHP and SMART, and Multi-Objective Optimization (MOO) with weighted degrees of satisfaction. Finally, earlierstudiesof colour perception illustrate the attemptsto find a physiological basisfor the set-theoretical and the algorithmic operations in Fuzzy Logic. The last chapter also discusses somekey issues in linguistic categorization and the prospectsof FuzzyLogicas a multi-disciplinary research activity. I am greatly indebted to the Department of Mechanical Engineering and Applied Mechanics, College of Engineering, University of Michigan, Ann Arbor, for the splendid opportunity to start the actual work on this book during my sabbatical leavefrom Delft (1993 - 1994); to LAMSADE, Universite de Paris-Dauphine, where many ideas emerged duringtwo winter visits (1989, 1990); to the International Institute for Applied Systems Analysis, Laxenburg, Austria, whereI got further inspiration duringa number of summer visits (1992, 1995, and 1996); and to the NISSAN Foundation in The Netherlands who enabled me to visit several Japanese universities (June 1996). Moreover, I gratefully acknowledge the stimulating supportgiven by many colleagues inthe International Society on Multi-Criteria Decision Making and in the European Working Group "Aide Multicritere Ii la Decision".

Simulating business processes for descriptive, predictive, and prescriptive analytics

Автор: Greasley, Andrew
Название: Simulating business processes for descriptive, predictive, and prescriptive analytics
ISBN: 1547416742 ISBN-13(EAN): 9781547416745
Издательство: Walter de Gruyter
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Цена: 9668.00 р.
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Описание: This book outlines the benefits and limitations of simulation, what is involved in setting up a simulation capability in an organization, the steps involved in developing a simulation model and how to ensure that model results are implemented. In addition, detailed example applications are provided to show where the tool is useful and what it can offer the decision maker. In Simulating Business Processes for Descriptive, Predictive, and Prescriptive Analytics , Andrew Greasley provides an in-depth discussion of Business process simulation and how it can enable business analytics How business process simulation can provide speed, cost, dependability, quality, and flexibility metrics Industrial case studies including improving service delivery while ensuring an efficient use of staff in public sector organizations such as the police service, testing the capacity of planned production facilities in manufacturing, and ensuring on-time delivery in logistics systems State-of-the-art developments in business process simulation regarding the generation of simulation analytics using process mining and modeling people’s behavior Managers and decision makers will learn how simulation provides a faster, cheaper and less risky way of observing the future performance of a real-world system. The book will also benefit personnel already involved in simulation development by providing a business perspective on managing the process of simulation, ensuring simulation results are implemented, and that performance is improved.

Decision Making with Uncertainty in Stormwater Pollutant Processes

Автор: Buddhi Wijesiri; An Liu; Prasanna Egodawatta; Jame
Название: Decision Making with Uncertainty in Stormwater Pollutant Processes
ISBN: 9811335060 ISBN-13(EAN): 9789811335068
Издательство: Springer
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Цена: 7685.00 р.
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Описание: This book presents new findings on intrinsic variability in pollutant build-up and wash-off processes by identifying the characteristics of underlying process mechanisms, based on the behaviour of various-sized particles. The correlation between build-up and wash-off processes is clearly defined using heavy metal pollutants as a case study. The outcome of this study is an approach developed to quantitatively assess process uncertainty, which makes it possible to mathematically incorporate the characteristics of variability in build-up and wash-off processes into stormwater quality models. In addition, the approach can be used to quantify process uncertainty as an integral aspect of stormwater quality predictions using common uncertainty analysis techniques. The information produced using enhanced modelling tools will promote more informed decision-making, and thereby help to improve urban stormwater quality.

Fuzzy Reasoning in Decision Making and Optimization

Автор: Christer Carlsson; Robert Fuller
Название: Fuzzy Reasoning in Decision Making and Optimization
ISBN: 3790824976 ISBN-13(EAN): 9783790824971
Издательство: Springer
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Цена: 29209.00 р.
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Описание: Unlike classical logic which requires a deep under- standing of a system, exact equations, and precise numeric values, fuzzy logic incorporates an alternative way of thinking, which allows modeling complex systems using a higher level of abstraction originating from our knowledge and experience.

Fuzzy Optimization and Multi-Criteria Decision Making in Digital Marketing

Автор: Anil Kumar, Manoj Kumar Dash
Название: Fuzzy Optimization and Multi-Criteria Decision Making in Digital Marketing
ISBN: 1466688084 ISBN-13(EAN): 9781466688087
Издательство: Mare Nostrum (Eurospan)
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Цена: 29106.00 р.
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Описание: Applies fuzzy theory and multi-criteria decision making principles for better practice in the digital business environment. This research-focused publication features discussions on several key concepts useful for modern business professionals including decision-making models and fuzzy theory applied to internet marketing, consumer behavior, and the optimization of strategic marketing plans.

Fuzzy and Multi-Level Decision Making: Soft Computing Approaches

Автор: Chi-Bin Cheng; Hsu-Shih Shih; E. Stanley Lee
Название: Fuzzy and Multi-Level Decision Making: Soft Computing Approaches
ISBN: 3319925245 ISBN-13(EAN): 9783319925240
Издательство: Springer
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Цена: 13974.00 р.
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Описание: This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.


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