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Based on the analysis of the affecting factors of the photovoltaic (PV) power generation, this paper presents a prediction model of PV power generation based on BP neural network optimized by the mind evolutionary algorithm (MEA). The model uses the MEA to optimize the weights and thresholds within the BP neural network, which overcomes the shortcomings of conventional learning algorithm which is...
This paper reports on a new Mamdani data-driven fuzzy modelling approach, which makes use of interval type-2 fuzzy sets and employs a multi-objective evolutionary algorithm to optimise the structure and parameters of interval type-2 fuzzy models with respect to the predictive accuracy and the complexity of fuzzy models. In order to reduce the computational burden of the interval type-2 fuzzy modelling,...
This paper reports on an efficient algorithm for locating the `optimal' solutions for multi-objective optimization problems by combining a state-of-the-art optimizer with a fitness model-estimate. This hybrid framework is introduced to illustrate how to make sufficient use of an approximate model, which includes a `controlled' process and an `uncontrolled' process during the search. With the inclusion...
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