首页|Intelligent color matching model for wood dyeing using Genetic Algorithm and Extreme learning machine
Intelligent color matching model for wood dyeing using Genetic Algorithm and Extreme learning machine
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NSTL
Ios Press
Wood dyeing technology is of great significance to improve the utilization rate of inferior wood resources. The challenge to imitating precious wood species by inferior wood is to quickly and accurately obtain the dyeing formula of precious wood species. This study uses Genetic Algorithm (GA) to optimize Extreme learning machine (ELM), and then a predictive model based on GA-ELM is proposed for predicting the dyeing formula of precious wood species. The sum of the relative deviations of the three dyes between the predicted formula and the actual formula, that is, the relative deviation of the formula, is calculated to evaluate the model's prediction accuracy. The simulation results show that the average relative deviations of the formula predicted by Back Propagation (BP) neural network, Radial Basis Function (RBF) neural network, ELM, and GA-ELM are 0.808, 0.717, 0.708, and 0.262. The prediction deviation of the GA-ELM is much smaller than that of other traditional neural networks, which can achieve good results in wood production.
Extreme learning machinegenetic algorithmcomputer color matchingwood veneer
NSTL
Ios Press
