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...

An Enterprise resource Planning (ERP) system is packaged business software that integrates organizational process and functions into a unified system. Many researchers and practitioners agree that Enterprise Resource Planning (ERP) systems are the most important development in terms of corporate use of information technology (IT) in the 1990s. In this author predict a Comparative study of Anfis...

A control system for non identical dc-dc converters using Adaptive Neuro Fuzzy Inference System (ANFIS) is presented. The converters are connected in parallel and have a non identical inductance value, L1≠L2≠L3, with 10% tolerance. The objective of control system is to balance the output current of each converter. One of converters is used as reference. The current error, which is subtraction o...

A new concept regarding to the GPS/INS integration, based on artificial intelligence here is presented. Most integrated inertial navigation systems (INS) and global positioning systems (GPS) have been implemented using the Kalman filtering technique with its drawbacks related to the need for predefined INS error model and observability of at least four satellites. Most recently, an INS/GPS inte...

Sudden water inrush has been a deadly killer in underground engineering for decades. Currently, especially in developing countries, frequent water inrush accidents still kill a large number of miners every year. In this study, an approach for predicting the probability of fault-induced water inrush in underground engineering using the adaptive neuro-fuzzy inference system (ANFIS) was developed....

A new speed control approach based on the Adaptive Neuro-Fuzzy Inference System (ANFIS) to a closed-loop, variable speed induction motor (IM) drive is proposed in this paper. ANFIS provides a nonlinear modeling of motor drive system and the motor speed can accurately track the reference signal. ANFIS has the advantages of employing expert knowledge from the fuzzy inference system and the learni...

This paper describes the application of Adaptive Neuro-Fuzzy Inference System (ANFIS) model with SVD for classification of Electrocardiogram(ECG) signals into one of the few known categories, and to arrive at a diagnostic decision regarding the condition of the patient. The proposed architecture is a combination of Singular Value Decomposition (SVD) filtering method and ANFIS model. The ECG sig...

This paper addresses about an approach that suggests for stock portfolio optimization using the combination of Adaptive Neuro-Fuzzy Inference System (ANFIS) and Capital Asset Pricing Model (CAPM). Stock portfolio optimization aims to determine which of the stocks to be added to a portfolio based on the investor’s needs, changing economic and market conditions. In order to construct an efficient...

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...