In the current study two methods are evaluated for predicting the compressive strength of concrete containing metakaolin. Adaptive neuro-fuzzy inference system (ANFIS) model and stepwise regression (SR) model are developed as a reliable modeling method for simulating and predicting the compressive strength of concrete containing metakaolin at the different ages. The required data in training an...

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...

A method based on adaptive neuro-fuzzy inference system (ANFIS) for computing the effective permittivity and the characteristic impedance of the micro-coplanar strip (MCS) line is presented. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems (FISs). A hybrid learning algorithm, which combines the least square method and the backpropagation alg...

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...

The main challenge in Wastewater Treatment Plants (WWTP) by activated sludge process is the reduction of the energy consumption that varies according to the pollutant load of influent. However, this energy is fundamentally used for aerators in a biological process. The modeling of energy consumption according to the decision parameters deemed necessary for good control of the active sludge ...

In this paper a pose invariant face recognition using neuro-fuzzy approach is proposed. Here adaptive neuro fuzzy interface system (ANFIS) classifier is used as neuro-fuzzy approach for pose invariant face recognition. In the proposed approach the preprocessing of image is done by using adaptive median filter. It removes the salt pepper noise from the original images. From these denoised images...

The next paper presents the development of a non-lineal dynamic system modelling using the combination of neural networks with fuzzy logic. The first approximation method used is ANFIS. With this method, the most significant rules were selected and slightly modified to obtain a significantly better result. This procedure was applied on a case study where an environmental system was modelled. Ke...

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

In this paper, an efficient and accurate method for tomatoes sorting will proposed. first we extract features from inputted tomato image and then accurate and appropriate decision on Classification tomatoes using fuzzy the mamdani inference, adaptive fuzzy neural network (anfis) methods for each of that image. In our proposed system adaptive fuzzy neural network (anfis) has less error and syste...

We present a quick and straightfoward way of input selection for neuro-fuzzy modeling using ANFIS. The method is tested on two real-world problems: the non-linear regression problem of automobile MPG (miles per gallon) prediction, and the nonlinear system identi-cation using the Box and Jenkins gas furnace data 1].