信息与控制2025，Vol.54Issue(6)：906-916,928,12.DOI:10.13976/j.cnki.xk.2024.4042
基于加权监督和双重映射的随机配置网络炉温预测模型
Stochastic Configuration Network Furnace Temperature Prediction Model Based on Weighted Supervision and Double Mapping
摘要
Abstract
To improve the robustness and accuracy of a data-driven prediction model for furnace tempera-ture in municipal solid waste incineration(MSWI),we propose a modeling method leveraging weighted supervision and double mapping to enhance the stochastic configuration network(WS-DM-SCN)and construct the furnace temperature prediction model.First,we design a weighting matrix based on the kernel risk-sensitive mean p-power error function,which is embedded into the supervision mechanism of SCN to constrain the connection weight configuration and bias parameters in the presence of noise.Second,we linearly integrate the Softplus and Sigmoid functions as the activation function of the SCN hidden layer to realize the double mapping transformation of the hid-den layer features during the training.Thus,we confirm the convergence of the SCN model with the two improved strategies.The results of the comparative experiments reveal that the error ob-tained with WS-DM-SCN decreased under the effects of different outlier proportions,thereby verif-ying the effectiveness of the proposed method.关键词
城市固废焚烧/随机配置网络/加权监督/双重映射Key words
municipal solid waste incineration/stochastic configuration network/weighted supervision/double mapping分类
信息技术与安全科学引用本文复制引用
严爱军,臧欣妍..基于加权监督和双重映射的随机配置网络炉温预测模型[J].信息与控制,2025,54(6):906-916,928,12.基金项目
国家自然科学基金项目(62373017,62073006) （62373017,62073006）
北京市自然科学基金项目(4212032) （4212032）
