This paper introduces the Inverted Hierarchical Neuro-Fuzzy BSP System (HNFB 1 ), a new neuro-fuzzy model that has been specifically created for record classification and rule extraction in databases. The HNFB 1 is based on the Hierarchical Neuro-Fuzzy Binary Space Partitioning Model (HNFB), which embodies a recursive partitioning of the input space, is able to automatically generate its own structure, and allows a greater number of inputs. The new HNFB 1 allows the extraction of knowledge in the form of interpretable fuzzy rules expressed by the following: If is and is , then input pattern belongs to class . For the process of rule extraction in the HNFB 1 model, two fuzzy evaluation measures were defined: 1) fuzzy accuracy and 2) fuzzy coverage. The HNFB 1 has been evaluated with different benchmark databases for the classification task: Iris Dataset, Wine Data, Pima Indians Diabetes Database, Bupa Liver Disorders, and Heart Disease. When compared with several other pattern classification models and algorithms, the HNFB 1 model has shown similar or better classification performance. Nevertheless, its performance in terms of processing time is remarkable. The HNFB 1 converged in less than one minute for all the databases described in the case study.
The dissemination of information on water quality for a non-specialist audience is essential to support political and institutional actions for the management of aquatic environments. Therefore, water quality indices have been proposed since they are able to synthesize into a single value or category information, usually described from an extensive set of water quality variables. This research proposes a new water quality index, based on fuzzy logic, aimed at lotic environments, developed through the collaboration of experts in water quality of the Rio de Janeiro Environmental Agency (Instituto Estadual do Ambiente -INEA). The proposed index was applied to water quality data from the Paraíba do Sul River, obtained by INEA, in the years 2002 to 2009. The results of IQA FAL showed that the index was able to synthesize the water quality of this stretch of the Paraíba do Sul, satisfactorily matching the assessments of the water quality assessments contained in the reports available. It was also noticed that with this methodology it was possible to avoid the attenuation of the influence of a variable in critical condition was attenuated by the influence of other variables in favorable conditions, producing an inaccurate result in the final index.
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