粗集理论在污水参数软测量中的应用研究

用粗糙集理论约简属性,消除冗余信息后建立了污泥体积指数的神经网络软测量模型.用某城市污水厂实际水质参数进行仿真实验.仿真结果表明,与未采用粗糙集进行预处理的模型相比,应用该模型不仅测量值的误差更小,而且输入参数从9个降至4个,大大降低了输入数据的维数,减少了神经网络的训练时间及训练步数,有利于软测量模型的实用化.

Application research of rough set theory in wastewater parameters soft measure

SVI artificial neural network soft measurement model was established using rough set theory to reduce attributes and eliminate superfluous data.A simulation was carried out using data from a wastewater treatment plant.Simulation result indicates that compared with the model that does not use rough set theory for pre-processing,the proposed model has lower measurement error and reduces the number of input parameters from 9 to 4.The dimension of the input data is reduced greatly,the training time and steps of the artificial neural network are also reduced,which is an advantage for the soft measurement model to be used in practice.