Displaying similar documents to “An heuristic approach for mapping landslide hazard integrating fuzzy logic with analytic hierarchy process”

Fuzzy querying: issues and perspectives

Janusz Kacprzyk, Gabriella Pasi, Peter Vojtáš, Sławomir Zadrożny (2000)

Kybernetika

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The term query is widely used in the database as well as information retrieval communities. Basically, a query against a collection of information items (to be called later, for brevity, an information source) provides a formal description of the items of interest to the user posing this query. A source of information is meant here very generally. It may take the form of an archive of multimedia or textual documents, a database, or a knowledge base. In the three previous examples the...

On classification with missing data using rough-neuro-fuzzy systems

Robert K. Nowicki (2010)

International Journal of Applied Mathematics and Computer Science

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The paper presents a new approach to fuzzy classification in the case of missing data. Rough-fuzzy sets are incorporated into logical type neuro-fuzzy structures and a rough-neuro-fuzzy classifier is derived. Theorems which allow determining the structure of the rough-neuro-fuzzy classifier are given. Several experiments illustrating the performance of the roughneuro-fuzzy classifier working in the case of missing features are described.

A Linguistic Fuzzy Approach to the Consensus Reaching in Multiple Criteria Group Decision-making Problems

Vojtěch Sukač, Jana Talašová, Jan Stoklasa (2016)

Acta Universitatis Palackianae Olomucensis. Facultas Rerum Naturalium. Mathematica

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The paper introduces a new method of reaching a consensus in multiple criteria group decision-making under fuzziness. This model is based on the general definition of the ‘soft’ consensus introduced by Kacprzyk and Fedrizzi in 1986. The fuzzy evaluations of alternatives express degrees of fulfillment of the given goals by the respective alternatives for each expert. The selection of the best alternative is based on the fuzzy consensus by experts. For this purpose a set of alternatives...

Evolution-fuzzy rule based system with parameterized consequences

Piotr Czekalski (2006)

International Journal of Applied Mathematics and Computer Science

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While using automated learning methods, the lack of accuracy and poor knowledge generalization are both typical problems for a rule-based system obtained on a given data set. This paper introduces a new method capable of generating an accurate rule-based fuzzy inference system with parameterized consequences using an automated, off-line learning process based on multi-phase evolutionary computing and a training data covering algorithm. The presented method consists of the following steps:...