introduction: with using multiple linear regression (mlr), can simultaneously analyses several different variables, but to get the desirable results from the mlr, the samples must be much and accurate. therefore, this method has high sensitivity and may cause errors in results. in addition, to use this method, the variable must have normal distribution and modification follow from a linear rela...

An modification of the Approximate Internal Modelbased Neural Control (AIMNC), using Multi Layer Perceptron (MLP) neural networks is proposed. A necessary condition that the system provides zero steady-state error for a constant reference and constant disturbances is derived. In the proposed control strategy only one neural network, which is the neural model of the plant, needs to be trained of...

Several neural network architectures have been developed over the past several years. One of the most popular and most powerful architectures is the multilayer perceptron. This architecture will be described in detail and recent advances in training of the multilayer perceptron will be presented. Multilayer perceptrons are trained using various techniques. For years the most used training metho...

Air pollution emerges as an imminent issue in metropolitan cities like Hong Kong, and attracts much attention in recent years. Prediction of pollutant levels and their tendency is an important topic in environmental science today. To achieve such prediction tasks, the use of neural network (NN), in particular, the multi-layer perceptron, is regarded as a cost-e7ective technique superior to trad...

In regression neural networks for pattern recognition of preprocessed guided waves signals in beams, a trained network produced large errors when identifying a test pattern not found in the training set. To improve the accuracy of results, a new neural network procedure was introduced where progressive training was performed in a series combined network with the integration of a weight-range se...

This paper describes a study of the use of four different neural network techniques for automatic speech recognition (ASR) using two common, real-world application databases. The neural network techniques investigated were the Multi-Layer Perceptron (MLP), the Multi-Output-Layer Perceptron (MOLP), which is an improved version of the MLP , the Time-Delay Neural Network (TDNN) and the Kohohnen Se...

In this paper we evaluate the classiication accuracy of four statistical and three neural network classiiers for two image based pattern classiication problems. These are ngerprint classiication and optical character recognition (OCR) for isolated handprinted digits. The evaluation results reported here should be useful for designers of practical systems for these two important commercial appli...

Commodity trading is one of the most popular resources owning to its eminent predictable return on investment to earn money through trading. The trading includes all kinds of commodities like agricultural goods such as wheat, coffee, cocoa etc., and hard products like gold, rubber, crude oils etc.,. The investment decision can be made very easily with the help of the proposed model. The propose...

In this work, a hybrid neural model (HNM) able to characterize accurately the dispersion behavior of the fundamental TE10 mode of a single layer SIW waveguide, is developed. The HNM combines the analytical expression that models the dispersion characteristics of this guiding structure, with a Multi Layer Perceptron Neural Network (MLPNN) which operates as an estimator of the cutoff angular freq...

To judge about the performance of designed support system for tunnels, structural forces i.e. peak values of axial and shear forces and moments are critical parameters. So in this study, at first a complete database using finite element method was prepared. Then, a model of artificial neural network (ANN) using multi-layer perceptron was developed to estimate lining structural forces. Sensitivi...