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In order to improve forecasting model accuracy of BP neural network, an improved prediction method of optimized BP neural network based on modified particle swarm optimization algorithm (PSO) was proposed. In this modified PSO algorithm, an adaptive mutation operator was proposed in PSO to change positions of the particles plunged in the local optimization. The modified PSO was used to optimize the...
In semiconductor manufacturing, it is important to produce multiple products on the same equipment to enhance the overall equipment effectiveness so as to improve the productivity. However, the “high-mix” production is difficult to control due to the time-varying model. To address this problem, an adaptive exponentially weighted moving average (EWMA) control method of which the core content is online...
This paper presents a data-driven adaptive soft sensor approach to investigate the performance and optimal operation of cooling tower for energy conservation. To achieve this aim, first, the cooling tower process is characterized by an adaptive soft sensor with nonnegative garrote (NNG) variable selection procedure. Then, based on the statistics result of NNG variable selection, the effect of environment...
The modeling for fermentation process has important significance in achieving control and optimal control of the fermentation process. Generalization capability of the model based on global learning support vector machine was not strong, so according to local learning theory the method of establishing the fermentation process dynamic model was proposed in this paper. The dynamic of the fermentation...
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