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Back-propagation artificial neural network was developed to study the relationship between the aging rates of capacity in Ni/H battery and alloying elements of cathode materials. Leave-one out method was used to train the ANN model. Test results showed that the prediction performance of the ANN model is satisfactory: the scatter dots distribute along the 0__45??diagonal line in the scatter diagram,...
DNA sequences of several bacteria were classified using artificial neural network model. The ??dinucleotides compositions?? method was used to characterize the DNA sequences which transform every DNA sequence to a 16-dimension vector. Back-propagation artificial neural network was developed and trained using ??leave-one-out?? method. Results showed that the accuracy of classification was 84.3%, which...
Radial-basis-function (RBF) artificial neural network was developed to recognize the coronary heart disease patients basing on the contents of microelements in human blood. Leave-one out method was used to train the model. After training, the RBF model was used to recognize the coronary heart disease patients. Results showed that the RBF model recognized the three samples correctly, and the accuracy...
Back-propagation neural network model was developed to predict the coal and gas outburst. After trained, the artificial neural network model was used to predict the coal and gas outburst of several samples. Moreover, ANN model was also used to analyse the quantitative effects of influencing factors on the coal and gas outburst. The prediction performance of ANN model is satisfactory. The prediction...
Back-propagation artificial neural network was developed to predict the dielectric constants of (Zr0.7Sn0.3)TiO4 ceramics. Leave-one out method was used to train the ANN model. Test results showed that the prediction performance of the ANN model is satisfactory: the scatter dots distribute along the 0__45??diagonal line in the scatter diagram, the values of statistical criteria are 0.7489(MSE), 2...
Back-propagation artificial neural network was developed to predict the corrosion rates of steels in sea water. Leave-one out method was used to train the ANN model. Test results showed that the prediction performance of the ANN model is satisfactory: the scatter dots distribute along the 0__45deg diagonal line in the scatter diagram, the values of statistical criteria are 1.3498 muAldrcm-2 (MSE),...
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