Evolving fuzzy systems (EFSs) are widely known as a powerful tool for streaming data prediction. In this article, novel zero-order EFS with unique belief structure is proposed stream classification. Thanks to new structure, the model can handle interclass overlaps in natural way and better capture underlying multimodel of streams form prototypes. Utilizing data-driven soft thresholds, self-orga...

The volume of landfills that are increasingly piled up and not handled properly will have a negative impact, such as decrease in public health. Therefore, predicting the with high degree accuracy is needed reference for government agencies community making future policies. This study aims to analyze Adaptive Neuro-Fuzzy Inference System (ANFIS) method. prediction results' level measured by valu...

In this paper an adaptive neuro fuzzy inference system based on interval Gaussian type-2 fuzzy sets in the antecedent part and Gaussian type-1 fuzzy sets as coefficients of linear combination of input variables in the consequent part is presented. The capability of the proposed method (we named ANFIS2) to function approximation and dynamical system identification is shown. The ANFIS2 structure ...

the main goal of research is designing an adaptive nuero-fuzzy inference system for evaluating the implementation of business intelligence systems in software industry. iranian software development organizations have been facing a lot of problems in case of implementing business intelligence systems. this system would be helpful in recognizing the conditions and prerequisites of success or fail...

System modelling based on conventional mathematical tools like differential equations is not well suited for dealing with ill-defined and uncertain systems. By contrast, a fuzzy inference system, employing fuzzy if–then rules can model the qualitative aspects of human knowledge and reasoning processes without employing precise quantitative analyses. This fuzzy modeling or fuzzy identification e...