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This paper analyzed the enterprise process energy consumption systematically with a lot of statistic data starting from energy efficiency, and established the energy consumption prediction model based on genetic algorithm of wavelet neural network (GA-WNN). This paper made previous optimization training with genetic algorithm, which have feature of natural evolution regularity, to the weights and...
A diagnosis method basing on neural network classifier, genetic algorithm (GA) and wavelet transform is proposed for a pulse width modulation voltage source inverter. It is used to detect and identify the transistor open-circuit fault. BP neural network (BPNN) is capable of recognition. However, it has shortcomings obviously. These are just advantages of GA, which has ability of global search. Thus...
This work presents a novel approach to the reduction of Peak-to-Average Power Ratio (PAPR) in multicarrier modulation: Partial Transmit Sequence (PTS) is optimized by opportune tailored Genetic Algorithms (GA) which allow achieving solution with pre-selected accuracy and reduced computational burden. A comparative study on both Orthogonal Frequency Division Multiplexing (OFDM) and Wavelet Packets...
The chaotic time series forecast was researched by using wavelet neural networks (WNN) in this paper. An improved training method for WNN was presented. The method combines the genetic algorithm (GA) with gradient descent BP algorithm; the BP method was embedded in the GA operation in order to resolve the GA's limitation in detail search capability. In the last step of the method the WNN searches...
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