Trimming the inputs of RBF networks
نویسندگان
چکیده
منابع مشابه
Determination of Lateral load Capacity of Steel Shear Walls Based on Artificial Neural Network Models
In this paper, load-carrying capacity in steel shear wall (SSW) was estimated using artificial neural networks (ANNs). The SSW parameters including load-carrying capacity (as ANN’s target), plate thickness, thickness of stiffener, diagonal stiffener distance, horizontal stiffener distance and gravity load (as ANN’s inputs) are used in this paper to train the ANNs. 144 samples data of each of th...
متن کاملPREDICTION OF NONLINEAR TIME HISTORY DEFLECTION OF SCALLOP DOMES BY NEURAL NETWORKS
This study deals with predicting nonlinear time history deflection of scallop domes subject to earthquake loading employing neural network technique. Scallop domes have alternate ridged and grooves that radiate from the centre. There are two main types of scallop domes, lattice and continuous, which the latticed type of scallop domes is considered in the present paper. Due to the large number o...
متن کاملتشخیص بهتر سلامت رانندگان با بهره گیری از شبکه عصبی مصنوعی
Introduction: Uncontrolled health status of drivers, can lead to the death of healthy individuals who are living in their best periods of life in terms of performance and wellness and also it can impose huge financial costs on a country. The purpose of this study was to design an intelligent system using Multilayer perceptron (MLP) and radial basis function (RBF) neural networks in order to dia...
متن کاملAdaptive RBF network control for robot manipulators
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...
متن کاملThe Modeling and Comparison of GMDH and RBF Artificial Neural Networks in Forecasting Consumption of Petroleum Products in the Agricultural Sector
Energy plays a significant role in today's developing societies. The role of energy demands to make decisions and policy with regard to its production, distribution, and supply. The vital importance of energy, especially fossil fuels, is a factor affecting agricultural production. This factor has a great influence on the production of agricultural products in Iran. The forecast of the con...
متن کامل