Weather forecasting is the application of science and technology to predict the state of the atmosphere for a future time at a given location. It is carried out by collecting quantitative data about the current state of the atmosphere and past and/or present experiences. In this study Adaptive Neuro-Fuzzy Inference System (ANFIS) and Multi-Layer Perceptron (MLP) Artificial Neural Network (ANN) ...

Taking an intelligent trimming device hydraulic manipulator as the research object, aiming at uncertainty, nonlinearity and complexity of its system, a trajectory tracking control scheme is studied in this paper. In light virtual work principle, coupling dynamic model system established. order to improve anti-interference adaptive abilities compound strategy combining neuro-fuzzy inference (ANF...

today, dc motors is still being used globally due to their easy speed controllability. in this article, an adaptive neuro-fuzzy inference system (anfis) controller is designed for dc motors. the main purpose of performing such task is to reduce the dc motor starting current and deleting the ripple current during starting time in considering control parameters such as: rise time, settling time, ...

The rate of penetration (ROP) is one of the vital parameters which directly affects the drilling time and costs. There are various parameters that influence the drilling rate; they include weight on bit, rotational speed, mud weight, bit type, formation type, and bit hydraulic. Several approaches, including mathematical models and artificial intelligence have been proposed to predict the rate o...

This paper describes the application of adaptive neuro-fuzzy inference system (ANFIS) model for classification of electroencephalogram (EEG) signals. Decision making was performed in two stages: feature extraction using the wavelet transform (WT) and the ANFIS trained with the backpropagation gradient descent method in combination with the least squares method. Five types of EEG signals were us...

weather process prediction is the tool for managers to planning the future political for maximum operation. the aim of this research is relation investigation of large scale synoptically patterns with seasonal rainfall of khorasan province. in this research, we have analyzed 37 years of rainfall data in khorasan province that is located the northeastern part of iran .we attempted to train adapt...

During the recent decades, neural network models have been focused upon by researchers due to their more real performance and on this basis, different types of these models have been used in forecasting. Now, there is a question that which kind of these models has more explanatory power in forecasting the future processes of the stock. In line with this, the present paper made a comparison betw...

In this paper we presented an architecture and basic learning process underlying in fuzzy inference system and adaptive neuro fuzzy inference system which is a hybrid network implemented in framework of adaptive network. In real world computing environment, soft computing techniques including neural network, fuzzy logic algorithms have been widely used to derive an actual decision using given i...

The presented control scheme utilizes Adaptive Neuro Fuzzy Inference System (ANFIS) controller to track a reference engine rotational speed and disturbance rejection during engine idling. To evaluate the performance of the controller a model of the engine is simulated and simulation results presented. ANFIS implements a first order Sugeno-style fuzzy system. It is a method for tuning an existin...

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...