This paper deals with the prediction of chaotic time series by using the multi-stage fuzzy inference system and its application to the analysis of operating flexibility. Multi-national corporation obtained by shifting manufacturing plants located in different countries is denoted as operating flexibility. Even though the operating flexibility is optimized by the stochastic dynamic programming u...

Abstract Only the label corresponding to maximum value of fully connected layer is used as output category when a neural network performs classification tasks. When close sub-maximum value, obtained by considering only and ignoring not completely accurate. To reduce noise improve accuracy, combining principles fuzzy reasoning, this paper integrates all results with emotional tendency text based...

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...

during pre-project planning as an essential phase of a project, fundamental decisions that lead to project success or failure will make. this phase of a project is more important essentially in oil, gas and petrochemical mega projects that tremendous amount of resources should consume. uncertainty in the initial phases of the project is at the highest level and therefore major project decisions...

To enhance the evaluation of the reliability recently featured many of the approaches linking the probability and fuzzy logic, the multi agent system can provide a connection between fuzzy logic and probability. In this article represents a new application of multi-agent model for evaluating the reliability indices of generation power system. Using agents of the probability for determining capa...

introduction: kidney disease is a major public health challenge worldwide. epidemiologic data suggest a significant relationship between underlying diseases and decrease in glomerular filtration rate (gfr). clinical studies and laboratory research have shown that the mentioned parameter is effective in development and progression of the renal disease per se. in this study, we used learning-base...

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 ...

overtaking a slow lead vehicle is a complex maneuver because of the variety of overtaking conditions and driver behavior. in this study, two novel prediction models for overtaking behavior are proposed. these models are derived based on multi-input multi-output adaptive neuro-fuzzy inference system (manfis). they are validated at microscopic level and are able to simulate and predict the future...

This paper employs Adaptive Neuro-Fuzzy Inference System (ANFIS) to predict water level that leads to flood in coastal areas. ANFIS combines the verbal power of fuzzy logic and numerical power of neural network for its action. Meteorological and astronomical data of Santa Monica, a coastal area in California, U. S. A., were obtained. A portion of the data was used to train the ANFIS network, wh...

Hybrid algorithm is the hot issue in Computational Intelligence (CI) study. From in-depth discussion on Simulation Mechanism Based (SMB) classification method and composite patterns, this paper presents the Mamdani model based Adaptive Neural Fuzzy Inference System (M-ANFIS) and weight updating formula in consideration with qualitative representation of inference consequent parts in fuzzy neura...