this paper aims to evaluate the impact of several indices of market structure including entry to barrier, economies of scale and concentration degree on 140 active industries using the digit. accordingly, we apply three methods including cost disadvantages ratio ( ), herfindahl–hirschman concentration index ( ) and comanor and willson criterion in order to assess the economies of scale and usin...

Two main objectives have been considered in this paper: providing a good model to predict the critical temperature and pressure of binary hydrocarbon mixtures, and comparing the efficiency of the artificial neural network algorithms and the support vector regression as two commonly used soft computing methods. In order to have a fair comparison and to achieve the highest efficiency, a comprehen...

TThe uncertainty estimation and compensation are challenging problems for the robust control of robot manipulators which are complex systems. This paper presents a novel decentralized model-free robust controller for electrically driven robot manipulators. As a novelty, the proposed controller employs a simple Gaussian Radial-Basis-Function Network as an uncertainty estimator. The proposed netw...

This paper investigates a framework for Secure Retrieval and Dissemination of Information (text and image) in Distributed and Wireless Environments (SECRET_DIDWE). Our research focuses on the evaluation and integration of Information Retrieval techniques. Text Retrieval and Content Based Image Retrieval techniques are mainly studied for use in medical environment. The framework is based on a wi...

The defects of BP neural network, such as low convergence speed, falling into local minimum easily, bad generalization ability, can depress the calculation accuracy of BP neural network and damage its practical effect. So the research of improving BP neural network has great theoretical and practical significance. The paper advances a new fuzzy neural network algorithm to overcome the defects o...

In order to overcome some unavoidable factors, like shift of the part, that influence the crisp neural networks’ recognition, the present study is dedicated in developing a novel fuzzy neural network (FNN), which integrates both the fuzzy set theory and adaptive resonance theory 2 (ART2) neural network for grouping the parts into several families based on the image captured from the vision sens...

Medical applications usually used Radial Basis Function Networks just as Artificial Neural Networks. However, RBFNs are Knowledge-Based Networks that can be interpreted in several way: Artificial Neural Networks, Regularization Networks, Support Vector Machines, Wavelet Networks, Fuzzy Controllers, Kernel Estimators, Instanced-Based Learners. A survey of their interpretations and of their corre...

Stator Winding Fault can be detected by monitoring any abnormality of the Park’s spectrum. In this paper, a fault-detection performance comparison is presented between the Support Vector Machine (SVM) and backpropagation algorithm (BP) using experimental data for a healthy and faulty case. Support Vector Machine and Back propagation Algorithm provide environments to develop fault-detection sche...