in this study two intelligent systems, based on adaptive neuro-fuzzy inference systems (anfis) and artificial neural networks (anns) of forecasting municipal solid wastes (msw) generation has been proposed. anfis and anns as an intelligent tool compared with together was used to monthly prediction of msw generated in tehran. monthly amount of solid wastes (sw), total monthly precipitation, mont...

In this paper, we propose a generalized fuzzy inference system (GFIS) in noise image processing. The GFIS is a multi-layer neuro-fuzzy structure which combines both Mamdani model and TS fuzzy model to form a hybrid fuzzy system. The GFIS can not only preserve the interpretability property of the Mamdani model but also keep the robust local stability criteria of the TS model. Simulation results ...

The system dynamics technique has been demonstrated to be a proper method by which to model and simulate the development of spatial data infrastructures (SDI). An SDI is a collaborative effort to manage and share spatial data at different political and administrative levels. It is comprised of various dynamically interacting quantitative and qualitative (linguistic) variables. To incorporate li...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

Fuzzy logic is a powerful tool to model knowledge uncertainty, measurements imprecision, and vagueness. However, there is another type of vagueness that arises when data have multiple forms of expression that fuzzy logic does not address quite well. This is the case for multiple instance learning problems (MIL). In MIL, an object is represented by a collection of instances, called a bag. A bag ...

This paper presents the design of a VLSI fuzzy processor, which is capable of dealing with complex fuzzy inference systems, i.e., fuzzy inferences that include rule chaining. The architecture of the processor is based on a computational model whose main features are: the capability to cope effectively with complex fuzzy inference systems; a detection phase of the rule with a positive degree of ...

The paper presents the design of municipal creditworthiness parameters. Municipal creditworthiness modelling is realized by fuzzy logic based systems. Therefore, current designs of hierarchical structures of Mamdanitype fuzzy inference systems and their analysis are introduced. Key-Words: Municipal creditworthiness, Mamdani-type fuzzy inference systems, hierarchical structures of fuzzy inferenc...

We propose a multi-objective space search algorithm (MSSA) and introduce the identification of fuzzy inference systems based on the MSSA and information granulation (IG). The MSSA is a multi-objective optimization algorithm whose search method is associated with the analysis of the solution space. The multi-objective mechanism of MSSA is realized using a non-dominated sorting-based multi-object...