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Aiming at the problem that the dual-frequency ultrasonic extraction of puerarin is difficult to detect effectively and efficiently with the method of manually watching and off-line detection, a method of soft sensor modeling is proposed. In the method, the genetic algorithm and the support vector machine (GA-SVM) are combined to build the soft measurement model of the puerarin extraction. By using...
The nonlinear plants with significant time delays are difficult to be controlled by classical means. In the present paper intelligent approaches are applied for the design of a nonlinear Smith predictor for compensation of the plant time delay based on a Takagi-Sugeno-Kang plant model and a fuzzy logic parallel distributed compensation (PDC). The design and the advantages of the PDC-Smith are illustrated...
Global solar radiation (GSR) data is the most important parameter for solar energy applications. But radiation data is not available in all the locations of India, due to higher cost and difficulty in measurements. Therefore it is necessary to develop methods to predict GSR using available meteorological parameters like sunshine data, relative humidity and temperature out of which temperature is the...
The increasing trend of high density computing environments have exacerbated the cooling infrastructure of the modern datacenters which contributes to mounting energy costs due to uncoordinated operation. By integrating information technology and infrastructure management through continuous monitoring, a balance between energy requirements of compute and cooling equipment can be achieved. Building...
The temperature of the burning zone in the acquisition process is not stable and has an important impact on the quality of pellet. In order to improve the burning zone temperature stability, zone of combustion temperature prediction model is proposed based on the improved BP neural network. According to the field data characteristics, using cluster analysis method for data processing in order to reduce...
Soft computing forecasting tools play an important role to forecast many complicated systems. In this paper, an effort has been made to use soft computing approaches to predict Dhaka daily temperatures for the period of 28 February 1945 to 27 August 2006. We have selected the fuzzy neuro model, the neuro genetic algorithm model as soft computing techniques. To compare results, a popular time series...
Battery fast charging is a crucial issue in both research and application to realize and promote the mass commercialization of electric vehicles, especially pure electric vehicles. However, due to the strong nonlinear properties of batteries, the charging process should take into consideration various factors such as state of charge (SoC), temperature, and charging current, so as to assure the safety,...
Near infrared (NIR) sensitive wavelengths of soluble solids content (SSC) were selected based on genetic algorithms (GAs) and interval partial least square (iPLS) in Nanfeng mandarin fruits, the better result was obtained with sensitive wavelengths of 642-787 nm, 861-1152 nm and 1225-1368 nm by iPLS. Then 30 unknown samples were used to evaluate performance of the model built with sensitive wavelengths...
Combining genetic algorithms and artificial neural networks, a hybrid genetic-neural method was proposed for modeling the nonlinear dynamic deformation system considering the effect of environmental factors. This method describes the characteristic of nonlinear evolvement of deformation using ANN (the artificial neural network) whose structure (including nodes of input layer and hide layer) is automatically...
Visible and near infrared spectroscopy (Vis/NIR) combined with chemometric methods was employed to classify rice wines with different ages. Spectra of 240 wine samples (80 for each year) were collected in the Vis/NIR region (325-1075nm) in the spectroradiometer in transmission mode. Partial least squares (PLS) analysis was applied to extract the principal components (PCs) as new eigenvectors to represent...
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