نتایج جستجو برای: anfis de

تعداد نتایج: 1534928  

2013
A. R. Fallahpour

Correspondence to A.R. Moghassem email: [email protected] ABSTRACT This study compares capabilities of two different modelling methodologies for predicting breaking strength of rotor spun yarns. Forty eight yarn samples were produced considering variations in three drawing frame parameters namely break draft, delivery speed, and distance between back and middle rolls. Several topologies with dif...

2005
Ali Asadian Behzad Moshiri Ali Khaki-Sedigh Caro Lucas

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, a method using a hybrid-adaptive network based fuzzy inference system (ANFIS) has been proposed which is trained during...

2016
Yaseen A. Hamaamin Amir Pouyan Nejadhashemi Zhen Zhang Subhasis Giri Sean A. Woznicki Jun Xu

Accurate and efficient estimation of streamflow in a watershed’s tributaries is prerequisite parameter for viable water resources management. This study couples process-driven and data-driven methods of streamflow forecasting as a more efficient and cost-effective approach to water resources planning and management. Two data-driven methods, Bayesian regression and adaptive neuro-fuzzy inference...

2013
Om Prakash

Conventional controller’s usually required a prior knowledge of mathematical modelling of the process. The inaccuracy of mathematical modelling degrades the performance of the process, especially for non-linear and complex control problem. The process used is Water-Bath system, which is most widely used and nonlinear to some extent. For Water-Bath system, it is necessary to attain desired tempe...

2005
Kerim Guney Nurcan Sarikaya

A new method for computing the resonant frequency of the circular microstrip antenna, based on the adaptive neuro-fuzzy inference system (ANFIS), is presented. A hybrid learning algorithm is used to identify the parameters of ANFIS. The results of the new method are in excellent agreement with the experimental results reported elsewhere.

2011
Apoorvi Sood Swati Aggarwal

The paper introduces various methods for classification like fuzzy logic, and its combination with artificial neural networks. Datasets from UCI Repository have been used for the implementation of classification models using Matlab 7.0 for Fuzzy Inference System(FIS) and Anfis and Matlab R2007b for Anfis with variable labels and different membership functions.

Journal: :Appl. Soft Comput. 2015
Ali M. Abdulshahed Andrew Longstaff Simon Fletcher

Thermal errors can have significant effects on CNC machine tool accuracy. The errors come from thermal deformations of the machine elements caused by heat sources within the machine structure or from ambient temperature change. The effect of temperature can be reduced by error avoidance or numerical compensation. The performance of a thermal error compensation system essentially depends upon th...

2016
Bingfeng Gu Yash P. Gupta Thomas Pröll M. Nazmul Karim Jinglu Hu Kotaro Hirasawa

Conventional control algorithms used in pH control systems give inefficient performance, leading to use of large mixers. To improve the neutralization control process, an ANFIS based advanced controller has been proposed. In this paper, method of design of adaptive controller based on neurofuzzy technique is presented. The method uses ANFIS methodology to 1 / 4

2007
M. Firat

The use of Artificial Intelligence methods is becoming increasingly common in the modeling and forecasting of hydrological and water resource processes. In this study, applicability of Adaptive Neuro Fuzzy Inference System (ANFIS) and Artificial Neural Network (ANN) methods, Generalized Regression Neural Networks (GRNN) and Feed 5 Forward Neural Networks (FFNN), for forecasting of daily river f...

2011
Mohammad Saber Iraji

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...

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