نتایج جستجو برای: fuzzy interference system anfis models were paralleled to configure a multi adaptive neuro
تعداد نتایج: 16079480 فیلتر نتایج به سال:
This article presents a comparison between two types of intelligent models: Artificial Neural Networks ANN and Adaptative Neuro-Fuzzy Interference System ANFIS, for forecasting flows in a section of Bogotá (Colombia) river, looking for the most efficient. The simulation was performed in the Matlab computer software, with data collected by hydrological stations of the Corporación Autónoma Region...
The quantification and prediction of inter-agent dependency requirements is one of the main concerns in Agent Oriented Requirements Engineering. To evaluate exertion load of an agent within resource constraints, this work provides a comparative analysis of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN). ANN is widely known due to its capability of learning the...
Multi-walled carbon nanotubes (CNTs) are synthesized with the assistance of water vapor in a horizontal reactor using methane over Co-Mo/MgO catalyst through chemical vapor deposition method. The application of Adaptive Neuro-Fuzzy Inference System (ANFIS) technique for modeling the effect of important parameters (i.e. temperature, reaction time and amount of H2O vapor) on the qualit...
This article presents an ultramodern modelling algorithm for predicting the remnant cellulose life cycle oil-submerged power transformers based on adaptive neuro-fuzzy interference system (ANFIS). The polymer characteristics, degree of polymerization (DP), and 2-furaldehyde (2FAL) 100 were measured collated, which apportioned into 70 training databanks 30 as testing datasets. transformer was pr...
In this paper we apply an Adaptive Network-Based Fuzzy Inference System (ANFIS) with one input, the dependent variable with one lag, for the forecasting of four macroeconomic variables of US economy, the Gross Domestic Product, the inflation rate, six monthly treasury bills interest rates and unemployment rate. We compare the forecasting performance of ANFIS with those of the widely used linear...
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...
the main problem associated with the traditional approach to image classification for the mapping of hydrothermal alteration is that materials not associated with hydrothermal alteration may be erroneously classified as hydrothermally altered due to the similar spectral properties of altered and unaltered minerals. the major objective of this paper is to investigate the potential of a neuro-fuz...
The aim of this study was to demonstrate the effectiveness of an adaptive neuro-fuzzy inference system (ANFIS) for the prediction of diesel spray penetration length in the cylinder of a diesel internal combustion engine. The technique involved extraction of necessary representative features from a collection of raw image data. A comparative evaluation of two fuzzy-derived techniques for modelli...
The paper proposed the adaptive noise suppression technique for suppression of noise in voice communication. There are different techniques earlier used for adaptive filteration like least mean square, kalman’s filter etc.In the paper we used “fuzzy logic” technique for adaptive filteration. We know about the theory of adptive filteration of noise and application of fuzzy logic. We are using th...
In this paper, an adaptive neuro fuzzy sliding mode based genetic algorithm (ANFSGA) controlsystem is proposed for a pH neutralization system. In pH reactors, determination and control of pH isa common problem concerning chemical-based industrial processes due to the non-linearity observedin the titration curve. An ANFSGA control system is designed to overcome the complexity of precisecontrol o...
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