1 edition of **Mathematical Models for Decision Support** found in the catalog.

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Published
**1988**
by Springer Berlin Heidelberg in Berlin, Heidelberg
.

Written in English

This volume is based on the lectures presented by well-known experts at the NATO Advanced Study Institute on Mathematical Models for Decision Support held in Val d"Isère, France, July 26 - August 6, 1987. At the beginning the abstracts appear in a section of their own. This is followed by an extensive review paper which provides an overview of the major modeling issues in decision making. Thus, by first reading these two sections the readers may gain a fair glimpse of the contents of the remaining six sections of the volume. Researchers and practitioners interested in current Decision Support Systems issues and the directions in progress are the intended audience of this book. There is a particular emphasis on the adaptation of Artificial Intelligence techniques for use in decision making. Readers of this volume will find its structure and contents valuable and germane to their own field of study and research.

**Edition Notes**

Other titles | Proceedings of the NATO Advanced Study Institute on Mathematical Models for Decision Support held in Val d"Isere France, July 26 - August 6, 1987 |

Statement | edited by Gautam Mitra, Harvey J. Greenberg, Freerk A. Lootsma, Marcel J. Rijkaert, Hans J. Zimmermann |

Series | NATO ASI Series, Series F: Computer and Systems Sciences -- 48, NATO ASI series -- 48. |

Contributions | Greenberg, Harvey J., Lootsma, Freerk A., Rijkaert, Marcel J., Zimmermann, Hans J. |

The Physical Object | |
---|---|

Format | [electronic resource] / |

Pagination | 1 online resource (IX, 765 pages 150 illustrations). |

Number of Pages | 765 |

ID Numbers | |

Open Library | OL27073268M |

ISBN 10 | 3642835554 |

ISBN 10 | 9783642835551 |

OCLC/WorldCa | 840301355 |

4. title and subtitle developing integrated decision support systems from mathematical models 6. author(s) downs, michael s. 5. funding numbers 7. performing organization name(s) and addressees) naval postgraduate school monterey ca performing organization report number 9. sponsoring/monitoring agency name(s) and address(es) Bringing together the disciplines of agriculture, animal science, plant science and ecology, this book explores how mathematics can be used to understand and explain agricultural processes. It starts by providing a review of the mathematical models currently available to agriculturalists, and the philosophy behind, and objectives of, modeling. The book then applies these techniques to real.

Mathematical Programming: An Overview 1 Management science is characterized by a scientiﬁc approach to managerial decision making. It attempts to apply mathematical methods and the capabilities of modern computers to the difﬁcult and unstructured problems confronting modern managers. It is a young and novel discipline. Although its roots can beFile Size: KB. Mathematical Modelling on Decision-making: Probabilistic Model Key Stage: 4 Decision-making processes occur in all aspects of life and natural sciences. For example, the migration patterns of some species of animals could be analysed as the mathematical models so as to refine the models to better fit the real-life scenarios 3. File Size: KB.

The new edition of Mathematical Modeling, the survey text of choice for mathematical modeling courses, adds ample instructor support and online delivery for solutions manuals and software ancillaries.. From genetic engineering to hurricane prediction, mathematical models guide much of the decision making in our society. If the assumptions and methods underlying the modeling are flawed, the. Shareable Link. Use the link below to share a full-text version of this article with your friends and colleagues. Learn more.

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Use of Optimisation Models as Decision Support Tools. Role of Information Systems in Decision Making: Database and Model Management Issues. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems.

Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. Mathematical Basis for Constructing Models and Model Validation. Keywords artificial intelligence control decision problem decision support expert system intelligence knowledge base knowledge-based systems modeling natural language operations research optimization uncertainty.

Mathematical models for decision support. Applied computing. Operations research. Decision analysis. Computing methodologies. Artificial intelligence.

Control methods. Knowledge representation and reasoning. Search methodologies. Modeling and simulation. Model development and analysis. Because the USGS has been historically active in the development of mathematical models for ground water flow and transport, and because similar activity for surface water quality models has been (at least in recent years) limited to the integration of existing models in decision support systems, the following discussion of predictive models.

Hsu-Shih Shih, An interactive approach for integrated multilevel systems in a fuzzy environment, Mathematical and Computer Modelling: An International Journal, v n, p, September, Patrick Valente, Gautam Mitra, The evolution of web-based optimisation: From ASP to e-Services, Decision Support Systems, v n.4, p Cited by: 6.

NATO Advanced Study Institute on Mathematical Models for Decision Support ( Val d'Isère, France). Mathematical models for decision support. Berlin ; New York: Springer-Verlag, © (OCoLC) Material Type: Conference publication, Internet resource: Document Type: Book, Internet Resource: All Authors / Contributors.

For a book solely focused on building polyhedral models, I'd recommend the reprinted "Shapes, Space, and Symmetry" by Alan Holden; I've had it for years and have used it to build several beautiful models.

But Cundy's book offers the possibility of enjoying a broader range of mathematical ideas in the same concrete way as building polyhedra/5(6).

Get this from a library. Mathematical Models for Decision Support. [Gautam Mitra; Harvey J Greenberg; Freerk A Lootsma; Marcel J Rijkaert; Hans J Zimmermann] -- This volume is based on the lectures presented by well-known experts at the NATO Advanced Study Institute on Mathematical Models for Decision Support held in Val d'Isère, France, July 26 - August 6.

The book explores a range of approaches including optimization models, dynamic models and probability models. Show less The new edition of Mathematical Modeling, the survey text of choice for mathematical modeling courses, adds ample instructor support and online delivery for.

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Decision support systems (DSSs) are a sub-set of information systems that support human decision-making through computerized systems that provide contextual information.

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The complexity of issues requiring rational decision making grows and thus such decisions are becoming more and more difficult, despite advances in methodology and tools for decision support and in other areas of research. Globalization, interlinks between environmental, industrial, social and political issues, and rapid speed of change all contribute to the increase of this complexity.

(source: Nielsen Book Data) Choice theory forms the basis for many scientific fields, such as decision making, mathematical models of micro-economics, voting theory, theory of control in socio-economic systems, and some branches of psychology. This volume is a first monograph summing up major scientific results obtained during two decades.

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From genetic engineering to hurricane prediction, mathematical models guide much of the decision making in our society. If the assumptions and methods underlying the modeling are flawed. One division between models is based on the type of outcome they predict. Deterministic models ignore random variation, and so always predict the same outcome from a given starting point.

On the other hand, the model may be more statistical in nature and so may predict the distribution of possible outcomes. Such models are said to be stochastic. 1File Size: 1MB.Mathematical Models of Life Support Systems; Mathematical Models; Research personnel and Policy analysts, managers, and decision makers and NGOs.

He has co-authored (with K. Vrieze) a research level text book Competitive Markov Decision Processes (Springer, ). He also authored or co-authored approximately 70 refereed research papers.

The book stresses those fundamental concepts that the authors believe are most important for the practical analysis of management decisions. It focuses on modeling and evaluating uncertainty explicitly, understanding the dynamic nature of decision making, using historical data and limited information effectively, simulating complex systems, and Pages: