In this study, artificial neural networks (ANNs) and adaptive neuro-fuzzy inference system (ANFIS) were used to estimate shear stress distribution in streams. The methods were applied to the 145 field data gauged from four different sites on the Sarimsakli and Sosun streams in Turkey. The accuracy of the applied models was compared with the multiple-linear regression (MLR). The results showed t...

Transformer fault diagnosis is an interesting subject for plant operators due to its criticality in power systems. There are several international standards available to interpret power transformer faults based on dissolved gas analysis. In certain cases these standards are not able to provide correct diagnosis. There are several soft computing techniques available for modelling transformer fau...

In a great diversity of knowledge areas, the variables that are involved in the behavior of a complex system, perform normally, a non-linear system. The search of a function that express those behavior, requires techniques as mathematics optimization techniques or others. The new paradigms introduced in the soft computing, as fuzzy logic, neuronal networks, genetics algorithms and the fusion of...

The adaptive inverse control is a novel method in control system. It makes set signal, parameter disturbance and external disturbance separately controlled and makes them reach the optimal control without compromiseThe traditional adaptive inverse control system often used FIR filters. It madde the system costing long training time and slow convergence. So, it is unable to adapt the requirement...

This study investigates the prediction model of compressive strength of self–compacting concrete (SCC) by utilizing soft computing techniques. The techniques consist of adaptive neuro–based fuzzy inference system (ANFIS), artificial neural network (ANN) and the hybrid of particle swarm optimization with passive congregation (PSOPC) and ANFIS called PSOPC–ANFIS. Their perf...

The prediction of groundwater quality is very important for the management of water resources and environmental activities. The present study has integrated a number of methods such as Geographic Information Systems (GIS) and Artificial Intelligence (AI) methodologies to predict groundwater quality in Kerman plain (including HCO3-, concentrations and Electrical Conductivity (EC) of groundwater)...

In this paper, two CI techniques, namely, single multiplicative neuron (SMN) model and adaptive neuro-fuzzy inference system (ANFIS), have been proposed for time series prediction. A variation of particle swarm optimization (PSO) with co-operative sub-swarms, called COPSO, has been used for estimation of SMN model parameters leading to COPSO-SMN. The prediction effectiveness of COPSOSMN and ANF...

The problem of fault detection of the π-model induction motor with magnetic saturation is considered in this paper. In this paper we use a new technique which is the Adaptive Neuro Fuzzy Inference Systems (ANFIS) technique for online identification of the different motor fault conditions. A simulation study is illustrated using MATLAB simulink depending on stator currents measurement only for o...

This paper presents a novel adaptive neuro-fuzzy based speed controller for vector controlled induction motor drive. The proposed neuro-fuzzy controller incorporates fuzzy logic algorithm with a five-layer artificial neural network (ANN) structure. The conventional PI controller is replaced by Adaptive Neuro-Fuzzy Inference System (ANFIS), which tunes the fuzzy inference system with hybrid lear...

This paper presents a three-phase hybrid power filter based on artificial intelligence control approach. It consists of C-type passive filter in parallel with a shunt active filter that is controlled by an adaptive Neuro-Fuzzy inference system (ANFIS) controller. The active filter is based on a three-phase voltage inverter with six control switches. The AC side of the filter is connected in par...