Last edited by Moogusida
Thursday, July 16, 2020 | History

1 edition of Applied Decision Support with Soft Computing found in the catalog.

Applied Decision Support with Soft Computing

by Xinghuo Yu

  • 42 Want to read
  • 16 Currently reading

Published by Springer Berlin Heidelberg in Berlin, Heidelberg .
Written in English

    Subjects:
  • Engineering,
  • Economics,
  • Engineering mathematics,
  • Engineering economy

  • About the Edition

    Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation mechanisms for addressing modern decision making issues. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications. Different from other existing books, this volume predominately focuses on applied decision support with soft computing. Areas covered include planning, management finance and administration in both the private and public sectors.

    Edition Notes

    Statementedited by Xinghuo Yu, Janusz Kacprzyk
    SeriesStudies in Fuzziness and Soft Computing -- 124, Studies in fuzziness and soft computing -- 124.
    ContributionsKacprzyk, Janusz
    Classifications
    LC ClassificationsTA177.4-185
    The Physical Object
    Format[electronic resource] /
    Pagination1 online resource (x, 418 p.)
    Number of Pages418
    ID Numbers
    Open LibraryOL27017580M
    ISBN 103642535348, 3540370080
    ISBN 109783642535345, 9783540370086
    OCLC/WorldCa851785853

    BibTeX @INPROCEEDINGS{Makowski03modelingknowledge: author = {Marek Makowski and Andrzej P. Wierzbicki}, title = {Modeling knowledge: Model-based decision support and soft computations,” in Applied Decision Support with Soft Computing}, booktitle = {of Series: Studies in Fuzziness and Soft Computing}, year = {}, pages = {}, publisher = . Applied Computational Intelligence and Soft Computing provides a forum for research that connects the disciplines of computer science, engineering, and mathematics using the technologies of computational intelligence and soft computing.

    soft computing model intends to explore or retrieve the effective patterns from the stock market with easy-to-understand decision rules for supporting the value stock selection problem. Applied Soft Computing, Vol. 26 Minimization of the Total Traveling Distance and Maximum Distance by Using a Transformed-Based Encoding EDA to Solve the Multiple Traveling Salesmen Problem Mathematical Problems in Engineering, Vol.

    Fuzzy Implications (FIs) generalize the classical implication and play a similar important role in Fuzzy Logic (FL), both in FL_n and FL_w in the sense of Zadeh. Their importance in applications of FL, viz., Approximate Reasoning (AR), Decision Support Systems, Fuzzy Control (FC), etc., is hard to exaggerate. It will provide a leading forum for disseminating the latest results in eSystem Development, Robotics, Data Science and Big Data Research, Idustry , IoT Development and Applications, Smart City, Smart Health, Smart Living and Smart Home, Health networking, Learning Analytics, Business Intelligence, Cloud Computing.


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Applied Decision Support with Soft Computing by Xinghuo Yu Download PDF EPUB FB2

This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications.

Different from other existing books, this volume predominately focuses on applied decision support with soft : Hardcover. This book provides a comprehensive coverage of up-to-date conceptual frameworks in broadly perceived decision support systems and successful applications.

Different from other existing books, this volume predominately focuses on applied decision support with soft computing.

Applied Decision Support with Soft Computing by Xinghuo Yu,available at Book Depository with free delivery : Xinghuo Yu.

Get this from a Applied Decision Support with Soft Computing book. Applied Decision Support with Soft Computing. [Xinghuo Yu; Janusz Kacprzyk] -- Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems.

Fast advances in soft computing technologies, such as fuzzy logic and systems. Soft computing has provided sophisticated methodologies for the development of intelligent decision support systems. Fast advances in soft computing technologies, such as fuzzy logic and systems, artificial neural networks and evolutionary computation, have made available powerful problem representation and modelling paradigms, and learning and optimisation.

Soft Computing Paradigms and Regression Trees in Decision Support Systems: /ch Decision-making is a process of choosing among alternative courses of action for solving complicated problems where multi-criteria objectives are involved. Intelligent decision support systems based on soft computing are of great importance to deal with complex decision environments, and involve the design of mathematical models for modeling decision problems, the use of different information technologies (such as the Web and social networks) and artificial intelligence tools (such as.

Journals & Books; Help Download PDF Download. Share. Export. Advanced. Applied Soft Computing. Vol JanuaryPages Decision rules for ambulance scheduling decision support systems. Author links open overlay panel Lu Zhen Shaopu Sheng Zhenhua Xie Kai Wang.

Show more. This book is dedicated to applied computational intelligence and soft computing techniques with special reference to decision support in Cyber Physical Systems (CPS), where the physical as well as the communication segment of the networked entities interact with each other.

All the papers will be peer-reviewed following Applied Soft Computing reviewing procedures. Guest editors will make an initial assessment of the suitability and scope of all submissions. Papers will be evaluated based on their originality, presentation, relevance and contributions, as well as their suitability to the special issue.

Soft Computing is dedicated to system solutions based on soft computing techniques. It provides rapid dissemination of important results in soft computing technologies, a fusion of research in evolutionary algorithms and genetic programming, neural science and neural net systems, fuzzy set theory and fuzzy systems, and chaos theory and chaotic systems.

We have developed a decision support system for Istanbul Strait to assist system warns Vessel Traffic Service (VTS) center and personnel of vessels for possible s which have collision possibility, have been estimated with neural ion is basically defined as 2 vessels being too close to each collision of 2 vessels is determined by.

Read the latest articles of Applied Soft Computing atElsevier’s leading platform of peer-reviewed scholarly literature. Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.

Soft computing is a collection of methodologies, which aim to exploit tolerance for imprecision, uncertainty and partial truth to achieve tractability, robustness and low solution cost.

Soft Computing vs Hard Computing. The biological processes fascinated scientists to solve real world problems by simulating the processes to robust algorithms and solve problems like a human mind in uncertain environment with limited information whereas the conventional algorithms (hard computing) fail to solve due to the strict principles.

Applied Soft Computing is an part of international magazine that promotes the integrated approach of soft computing to fix current life troubles.

A compilation of Soft Computing functionality aimed at exploiting impurity, uncertainty and tolerance for partial truths to achieve tractability, robustness and reduced solution costs. The primary aim of the Applied Soft Computing. ” Decision Support Systems, ” Applied Soft Computing, Vol.

11, No. 2, pp. – Tsay, R. (): Multivariate Time Series Analysis: With R and Financial Applications. 1st ed. Wiley. Book summary views reflect the number of visits to the book and chapter landing pages. Home Browse by Title Periodicals Applied Soft Computing Vol. 11, No. 4 On the extraction of decision support rules from fuzzy predictive models article On the extraction of decision support rules from fuzzy predictive models.

• Application of soft computing to decision-support systems • Neurofuzzy systems • Fuzzy logic control 11 Future of Soft Computing (adapted from L.A. Zadeh) • Soft computing is likely to play an especially important role in science and engineering, but applied neural network technique. RBFs are gaining in popularity.

Applied Computational Intelligence and Soft Computing-Special Issue; Volume - Article ID - Research Article; Development of Decision Support Model for Selecting a Maintenance Plan Using a Fuzzy MCDM Approach: A Theoretical Framework. This book gives an introduction to Soft Computing, which aims to exploit tolerance for imprecision, uncertainty, approximate reasoning, and partial truth in order to achieve close resemblance with human like decision making.

Soft Computing is a new multidisciplinary field, to construct new generation of Artificial Intelligence, known as.Book Description Soft computing is a branch of computer science that deals with a family of methods that imitate human intelligence.

This is done with the goal of creating tools that will contain some human-like capabilities (such as learning, reasoning and decision-making).Professor Hong’s articles have been published in Applied Mathematics and Computation, Applied Mathematical Modelling, Applied Soft Computing, Control and Cybernetics, Decision Support Systems, Electric Power Systems Research, Energy, Energies, Energy Conversion and Management, Energy Policy, European Journal of Operational Research, IEEE.