A double inverted pendulum system is a very complex and nonlinear system. In this paper, a new design method using adaptive networks based fuzzy inference system (ANFIS) is proposed to cope with this system. This is a single input multi outputs system which states are all nonlinear and the second state maybe need infinity control force in the steady state. So the transient states control is mor...

Inertial navigation is a crucial part of vehicle systems in complex and covert surroundings. To address the low accuracy inertial multifaced surroundings, this study, we proposed an error estimation based on adaptive neuro fuzzy inference system (ANFIS) which can quickly accurately output position end-to-end. The new was tested using both single-sequence multi-sequence data collected from by KI...

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. ...

This study presents a new method for modeling an adaptive neuro-fuzzy inference system (ANFIS) based on vibration for predicting surface roughness in the CNC turning process. The input parameters of the model are insert nose radius, cutting speed, feed rate, depth of cut and vibration amplitude, which determine the output parameter of the surface roughness. A Gauss type membership function was ...

This paper presents the architecture and learning procedure underlying ANFIS (Adaptive-Network-based Fuzzy Inference System), a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data ...

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...

The aim of this paper is to propose an exploratory study on simple, accurate and 19 computationally efficient movement classification technique for prosthetic hand application. The 20 surface myoelectric signals were acquired from 2 muscles – Flexor Carpi Ulnaris and Extensor Carpi 21 Radialis of 4 normal-limb subjects. These signals were segmented and the features extracted using a 22 new comb...

The Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference System (FIS) has attracted a growing interest of researchers in various scientific and engineering areas due to the growing need for adaptive intelligent systems to solve real world problems. ANN learns by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of fuzzy set theory...

The Adaptive Network-Based Fuzzy Inference System (ANFIS) has been proven to be efficient for forecasting. To address this concern, this research develops a nonlinear combined forecasting system by ANFIS for predicting the demand of telecommu-nication technology. We investigate the weights assigned to the combined forecast using two linear methods (the Least squares analysis and the Logistic mo...