This paper proposes a new classification method for Farsi handwritten word recognition using gradient and gradient based features. The extracted feature vectors were classified using two Multi Layer Perceptron networks as basic experts, and one Radial Basis Function was applied to choose the best expert. The experiments were performed using the Iranshahr dataset. This dataset consists of 780 sa...

In information retrieval, data fusion has been investigated by many researchers. Previous investigation and experimentation demonstrate that the linear combination method is an effective data fusion method for combining multiple information retrieval results. One advantage is its flexibility since different weights can be assigned to different component systems so as to obtain better fusion res...

Recently system combination has been shown to be an effective way to improve translation quality over single machine translation systems. In this paper, we present a simple and effective method to systematically derive an ensemble of SMT systems from one baseline linear SMT model for use in system combination. Each system in the resulting ensemble is based on a feature set derived from the feat...

Feature combination is a popular method for improving object classification performances. In this paper we present a simple and effective weighting scheme for feature combination based on the dominant-set notion of a cluster. Specifically, we use dominant sets clustering to evaluate how accurate a kernel matrix is expected to be for a SVM classifier. This expected kernel accuracy reflects the d...

This paper presents the Bayesian Combined Predictor (BCP), a probabilistically motivated predictor for Short Term Load Forecasting (STLF) based on the combination of an artificial neural network (ANN) predictor and two linear regression (LR) predictors. The method is applied to STLF for the Greek Public Power Corporation dispatching center of the island of Crete, using 1994 data, and daily load...

The electrocardiogram signal which represents the electrical activity of the heart provides interference in the recording of the electromyogram signal, when the electromyogram signal is recorded from muscles close to the heart. Therefore, due to impurities, electromyogram signals recorded from this area cannot be used. In this paper, a new method was developed using a combination of artificial ...

-. Port throughput forecast plays a great role in the development of port logistics economy. This paper works over that significant subject based on a new kind of nonlinear combination method, which is composed of linear exponential smoothing model, simple moving average method and Elman network. The forecasted values through the first two methods are taken as the inputs of Elman network, which...

In this paper we present the Bayesian Combined Predictor (BCP), a probabilistically motivated predictor for time series prediction. BCP utilizes local predictors of several types (e.g. linear predictors, artificial neural network predictors, polynomial predictors etc.) and produces a final prediction which is a weighted combination of the local predictions; the weights can be interpreted as Bay...

Researchers and practitioners in many scientific disciplines and industrial fields are often faced with complex problems when dealing with comparisons between two or more groups using classical parametric methods. The data arising from real problems rarely are in agreement with stringent parametric assumptions. The NonParametric Combination (NPC) methodology frees the researcher from stringent ...

In llatllral language processing, many methods have been proposed to solve the ambiguity l)roblems. In this paper, we propose a lechnique to COlnbille a method of interactive disamlfiguation and automatic one tbr anlbiguous words. The characteristic of our method is that the accuracy of the interactive dis-alnbiguation is considered. The method solves the two following l)roblems when combining ...