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In this paper, a new approach for designing the KB of an FLC (using a GA) is proposed and its effectiveness is compared to a previous approach based on GA-fuzzy combination for making predictions of power requirement and surface finish in grinding (a machining process to obtain smooth surface on the work).
Three types of uncertainties affecting the predictions of power distribution in the core of a nuclear reactor are discussed: the uncertainties of basic nuclear data, the uncertainties resulting from the use of different simulation tools and those due to approximations in reflector modelling.
The accuracy of the predictions of power calculations has been demonstrated here to be excellent, perhaps surprisingly so given the number of assumptions involved in power calculations.
Predictions of power, sample size and minimum observable effect size (difference in group means) are available across a range of common study designs.
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Our methodology will be used for design optimization, performance evaluation, and prediction of power consumption of DBD for industrial applications.
Recent research on wind farms tends to focus on wind flow modelling to enable accurate prediction of power generation.
However, having a good prediction of power consumption is still an important request to the computer science community.
Successful integration of renewable energy sources like wind power into smart grids largely depends on accurate prediction of power from these intermittent sources.
The disturbed voltage trajectory is also reported as a well-performing attribute for machine learning based transient stability prediction of power systems [25].
An accurate computation of added resistance, therefore, is getting more important for the prediction of power increase in random ocean waves.
The precise prediction of power generation, heat transfer and flow distribution within a reactor core is of great importance to asses the safety features of any reactor design.
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