The Q-Credit Assignment (QCA) is a method, based on Q-learning, for allocating credit to rules in Classiier Systems with internal state. It is more powerful than other proposed methods, because it correctly evaluates shared rules, but it has a large computational cost, due to the Multi-Layer Perceptron (MLP) that stores the evaluation function. We present a method for reducing this cost by redu...

nowadays, groundwater resources play a vital role as a source of drinking water in arid and semiarid regions and forecasting of pollutants content in these resources is very important. therefore, this study aimed to compare two soft computing methods for modeling cd, pb and zn concentration in groundwater resources of asadabad plain, western iran. the relative accuracy of several soft computing...

In the paper a new structure of Multi-Layer Perceptron, able to deal with quaternion-valued signal, is proposed. A learning algorithm for the proposed Quaternion MLP (QMLP) is also derived. Such a neural network allows to interpolate functions of quaternion variable with a smaller number of connections with respect to the corresponding real valued MLP. INTRODUCTION In the last few years, neural...

The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...

This paper proposes the application to the liver fibrosis stadialization of a novel training technique of feed-forward neural networks based on the Bayesian paradigm. Using the Pearson’s r correlation coefficient instead of the standard backpropagation algorithm to update the synaptic weights of a multi-layer perceptron, the proposed model is compared with traditional machine learning algorithm...

The present study provided the first-time comprehensive evaluation of 12 advanced statistical and machine learning (ML) algorithms for Soil Moisture (SM) estimation from dual polarimetric Sentinel-1 radar backscatter. ML namely support vector (SVM) with linear, polynomial, radial sigmoid kernel, random forest (RF), multi-layer perceptron (MLP), basis function (RBF), Wang Mendel’s (WM), subtract...

In this paper, we propose a new method of phoneme segmentation using MLP(multi-layer perceptron). The structure of the proposed segmenter consists of three parts: preprocessor, MLP-based phoneme segmenter, and postprocessor. The preprocessor utilizes a sequence of 44 order feature parameters for each frame of speech, based on the acoustic-phonetic knowledge. The MLP has one hidden layer and an ...

In this study, Gaussian white noise and color noise of speech signal are reduced by using adaptive filter and soft computing algorithms. Since the main target is noise reduction of speech signal in a car, ambient noise recorded in a BMW750i is used as color noise in the applications. Signal Noise Ratios (SNR) are selected as +5, 0 and -5 dB for white and color noise. Normalized Least Mean Squar...

Software piracy represents a major damage to the moral fabric associated with the respect of intellectual property. The rate of software piracy appears to be increasing globally, suggesting that additional research that uses new approaches is necessary to evaluate the problem. The study remedies previous econometric and methodological shortcomings by applying Bayesian, robust and evolutionary c...