SPSS在进口铁矿产地品牌识别中的应用

Application of SPSS in Brand Recognition of Imported Iron Ore Origin

文章介绍了建立进口铁矿产地品牌识别模型的方法。利用X射线荧光光谱法、红外吸收法、发射光谱法等常规方法测定所收集的进口铁矿样品中的主次元素含量,选择其中Al_(2)O_(3)、SiO_(2)、Fe、K_(2)O、Cr、CaO、MgO、V_(2)O5、TiO_(2)、MnO、Na_(2)O、P、As、S、Ni、Zn、Pb共17种元素进行含量分析。在大量检测数据的基础上,分别采用SPSS软件中4种算法对元素和产地品牌的关联程度进行计算,建立不同进口铁矿产地品牌识别模型,并利用测试样本评估不同模型的准确性和可靠性。测试结果显示,判别分析和多层感知器神经网络能实现对铁矿石产地与品牌的识别。所建立的模型可应用于常见进口铁矿的产地品牌识别,对于维护贸易公平、保障矿石质量安全将起到积极的作用。

This paper introduces the method of establishing the brand recognition model of imported iron ore origin.The contents of primary and secondary elements in the collected imported iron ore samples were determined by conventional methods such as X-ray fluorescence spectrometry,infrared absorption spectrometry and emission spectrometry.A total of 17 elements including Al_(2)O_(3),SiO_(2),Fe,K_(2)O,Cr,CaO,MgO,V_(2)O_(5),TiO_(2),MnO,Na_(2)O,P,As,S,Ni,Zn,Pb were selected for content analysis.Based on a large number of test data,four algorithms in SPSS software are used to calculate the correlation degree between elements and origin brand,establish brand recognition models of different imported iron ore origin,and use test samples to evaluate the accuracy and reliability of different models.The test results show that discriminant analysis and multilayer perceptron neural network can recognize the origin and brand of iron ore.The established model can be applied to the origin brand identification of common imported iron ore,and will play a positive role in maintaining trade equity and ensuring ore quality and safety.