Linguistic fuzzy logic in R
| Autor: | Michal Burda |
|---|---|
| Rok vydání: | 2015 |
| Předmět: |
Deductive reasoning
Fuzzy classification Neuro-fuzzy Association rule learning Computer science Fuzzy Control Language Fuzzy set Inference Type-2 fuzzy sets and systems Defuzzification Fuzzy logic Fuzzy number Fuzzy associative matrix computer.programming_language Adaptive neuro fuzzy inference system Fuzzy rule business.industry Fuzzy control system Fuzzy cognitive map Linguistics Fuzzy mathematics Fuzzy set operations Artificial intelligence Combs method T-norm fuzzy logics business computer Membership function |
| Zdroj: | FUZZ-IEEE |
| DOI: | 10.1109/fuzz-ieee.2015.7337826 |
| Popis: | The aim of this paper is to present a new package for the R statistical environment that enables the use of linguistic fuzzy logic in data processing applications. The lfl package provides tools for transformation of data into fuzzy sets representing linguistic expressions, for mining of linguistic fuzzy association rules, and for perfoming an inference on fuzzy rule bases using the Perception-based Logical Deduction (PbLD). The package also contains a Fuzzy Rule-based Ensemble, a tool for time series forecasting based on an ensemble of forecasts from several individual methods that is driven by a linguistic rule base created automatically from a large set of training time series. |
| Databáze: | OpenAIRE |
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