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Software effort estimation is very crucial and there is always a need to improve its accuracy as much as possible. Several estimation techniques have been developed in this regard and it is difficult to determine which model gives more accurate estimation on which dataset. Among all proposed methods, the Radial Basis Function Neural (RBFN) networks models have presented promising results in software...
Software effort estimation is very crucial and there is always a need to improve its accuracy as much as possible. Several estimation techniques have been developed in this regard and it is difficult to determine which model gives more accurate estimation on which dataset. Among all proposed methods, the Radial Basis Function Neural (RBFN) networks models have presented promising results in software...
Load forecasting is important necessity to provide economic, reliable, high grade energy. In this study, short term hourly load forecasting systems were developed for nine load distribution regions of Turkey using artificial neural networks (ANN) approach. ANN is the most commonly preferred approach for load forecasting. The mean average percent error (MAPE) of total hourly load forecast for Turkey...
On basis of management risks evaluation system for expressway projects, a risk evaluation model, which was based on the improved BP neural network and fuzzy synthetic evaluation, was established, trained and simulated in this study. The numerical value of various risky factors was confirmed using fuzzy synthetic evaluation method. Furthermore, the neural network model was designed and its BP algorithm...
Text classification has been mostly performed through implicit semantic correlation techniques, such as latent semantic analysis. This approach however, has proved insufficient for situations where there are short texts to be classified into one or more from many classes. That is the case of the classification of statements of purpose of Brazilian companies, according to the around one thousand and...
Usually, intrusion detection systems (IDS) work using two methods of identification of attacks: by signatures that are specific defined elements of the network traffic possible to identification and by anomalies being some deviations form of the network behavior assumed as normal. In the both cases one must pre-defined the form of the signature (in the first case) and the networkpsilas normal behavior...
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