نتایج جستجو برای: adaptive neuro fuzzy inference systems anfis
تعداد نتایج: 1504896 فیلتر نتایج به سال:
Navigation and obstacle avoidance in an unknown environment is proposed in this paper using hybrid neural network with fuzzy logic controller. The overall system is termed as Adaptive Neuro Fuzzy Inference System (ANFIS). ANFIS combines the benefits of fuzzy logic and neural networks for the purpose of achieving robotic navigation task. Simulation results are presented using Khepera Simulator (...
Churn prediction is a useful tool to predict customer at churn risk. By accurate prediction of churners and non-churners, a company can use the limited marketing resource efficiently to target the churner customers in a retention marketing campaign. Accuracy is not the only important aspect in evaluating a churn prediction models. Churn prediction models should be both accurate and comprehensib...
The aim of this work is to optimise the vibration of the plate with the help of Adaptive neuro-fuzzy inference system (ANFIS) controller. The contribution of piezoelectric sensor and actuator layers on the mass and stiffness of the plate is considered. As the plate is square so we get total 64 squares. To validate the present code, frequency response has been compared with exact solution as wel...
Induction generator is the most common generator in wind energy systems because of its simplicity, ruggedness, little maintenance, price, etc. Thus, a novel design of an Adaptive Neuro-fuzzy Inference strategy(ANFIS) for analyzing some of the parameters such as frequency, voltage, current, etc. of the induction motor is presented in this paper. Induction motors are characterized by highly non-l...
Weather elements are the most important parameters in metrological and hydrological studies especially in semi-arid regions, like Jordan. The Adaptive Neuro-Fuzzy Inference System (ANFIS) is used here to predict the minimum and maximum temperature of rainfall for the next 10 years using 30 years’ time series data for the period from 1985 to 2015. Several models were used based on different memb...
This paper describes the comparison of Artificial Intelligence (AI) based rotor position estimation techniques for Switched Reluctance Motor (SRM) with respect to its execution time in Digital Signal Processor (DSP) TMS320F2812. The various networks of Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System ( ANFIS) structures are trained for mapping the nonlinear current-flux...
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 study, a new adaptive controller is proposed for position control of pneumatic systems. difficulties associated with the mathematical model of the system in addition to the instability caused by pulse width modulation (pwm) in the learning-based controllers using gradient descent, motivate the development of a new approach for pwm pneumatics. in this study, two modified feedback error l...
The UV-spectrophotometric method of analysis was proposed for simultaneous determination of fluoxetine (FLX) and sertraline (SRT). Considering the strong spectral overlap between UV-Vis spectra of these compounds, a previous separation should be carried out in order to determine them by conventional spectrophotometric techniques. Here, full-spectrum multivariate calibrations adaptive neuro-fuzz...
To accurately estimate the state of charge of a lithium-ion battery pack used in electric vehicles, a neurofuzzy system is proposed. The subtractive clustering is used to determine the structure and the initial parameters of the neuro-fuzzy system to reduce heuristic errors. The algorithm of adaptive neuro-fuzzy inference (ANFIS) is adopted to optimize the parameters of the neuro-fuzzy system. ...
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