The modeling of mineral processing plant based the combination of exploratory data analysis spss and neural network in this article improve quality of modeling and enrich content of neural network ; at the same time it make mathematic model of mineral processing plant not only be used to forecast effect but also forecast condition of controlling 本文采用spss统计分析软件与神经网络相结合进行选矿厂数学建模,提高了选矿厂数学建模的质量,丰富了神经网络的内容;同时使选矿厂数学模型不再只是用于预测选矿效益,还可以尝试用于预测选矿控制条件。
In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics in easy-to-understand form, often with visual graphs, without using a statistical model or having formulated a hypothesis. Exploratory data analysis was promoted by John Tukey to encourage statisticians visually to examine their data sets, to formulate hypotheses that could be tested on new data-sets.