基于污水处理厂减少监测污水装置的要求,提出了一种以相对误差最小为性能指标的污水浓度预测方法,该方法首先将低维空间的数据映射到高维空间,然后在高维空间上建立线性预测模型.最后给出了应用实例,并与传统的最小二乘法和当前热门的神经网络方法的结果进行了比较,结果表明本文方法结构简单而且有效.
A prediction approach of waste-water concentration was proposed, in order to reduce costs or decrease monitoring devices, by minimum relative error performance index. Firstly, non-linearly data on low dimensional space was mapped into high dimensional space, then established the linear prediction model on the high dimensional space, finally an application example was provided to illustrate the method, and comparisons was made with the traditional least squares method or the current popular neural network method. Simulation shows the method is simple and effective.