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The aim of the paper is to present a Bayesian Network (BN) for predicting reputation of members of Virtual Learning Communities using direct interactions between them considering the theory of the rewards of behavioral Psychology. Reputation is a key factor of a trust model. A prototype of the proposed BN was implemented in the Moodle Learning Management System.
This paper presents the implementation of a controller based on Adaptive Task Allocation Algorithm (ATAA) for a traffic network with signalized intersections, where it is required to decrease waiting times of vehicles at every intersection. The main contributions of this work are the implementation of ATAA controller under a Model Predictive Control (MPC) scheme and the use of an estimator which does...
This paper propose that the combination of smoothing approach taking into account the entropic information provided by Renyi' method, has an acceptable performance in term of forecasting errors. The methodology of the proposed scheme is examined through benchmark chaotic time series, such as Mackay Glass, Lorenz, Henon maps, the Lynx and rainfall from Santa Francisca series, with addition of white...
Accurate load forecasts are required in most tasks of energy planning. In this paper we present a hybrid method for short-term load forecasting. We combined Exponential Smoothing, a classical method for time series forecasting, with Gradient Boosting, a powerful machine learning algorithm. The proposed model was tested with real data and the results showed a considerable improvement in forecasting...
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