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In this paper, wind power series prediction using BEA modified (BEAmod.) neural networks-based approach is presented. Wind power forecasting is a complex, multidimensional, and highly non-linear system. Neural network is able to learn the relationship between system inputs and outputs without mathematical conversion, and perform complex nonlinear mapping, data classification, prediction, and is also...
This article proposes that the combination of smoothing approach considering the entropic information provided by Renyi's 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 Mackey Glass, Lorenz, Henon maps, the Lynx and rainfall from Santa Francisca - Cordoba, with addition of white...
There are many Evolutionary Algorithms which main features are: population, evolutionary operations (crossover, mate, mutation and others). Most of them are based on randomness and follow a criteria using fitness like selector. The proposal uses probability density function according to best of initial population to sample new population and save better individuals iteratively. Then using centroid...
This work presents the modeling and implementation of a Hybrid Chemical Reactions Optimization that uses CRO operators to find good solutions, and heuristics to initialize the first population and mapping tasks in processors to solve the Multiprocessor task scheduling problem, taking into account the heterogeneity of the multiprocessor system.
In this work, a reservoir simulation approximation model (proxy) based on recurrent artificial neural networks is proposed. This model is intended to obtain rates of oil, gas and water production at time t+1 from the respective production rates, average pressure and water cut at t time and the well operation points to be applied in t + 1. Also, this model is able to follow the dynamics of the reservoir...
This work is focused on the modeling and development of a CBIR (Content-based image retrieval) system applied to the recovery of digital medical images of a human body, denominated M-CBIR. This model is composed on two methodologies: features extraction techniques and metric data structures. When this set of techniques is applied to the search of different human body regions, it can retrieve the most...
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