correlation analysis-based abnormal sign miner discrimination method combining EN with MPA-SVM

The invention relates to a correlation analysis-based abnormal sign miner discrimination method combining EN with MPA-SVM. The method comprises the following steps: (1) collecting miner occupational health examination data, and constructing a miner sign parameter data set; (2) randomly dividing the miner sign data into a training set and a prediction set; (3) carrying out normalization processing on data of the training set and the prediction set; (4) adopting a Pearson's correlation coefficient to analyze and delete the physical sign data with high correlation; (5) removing redundant sign information by using EN; and (6) establishing an MPA-SVM miner abnormal sign discrimination model, wherein an evaluation index of prediction set data is used for analysis and evaluation of model performance. according to the method, the correlation analysis EN is combined with the MPA-SVM to be used for recognizing the miners with abnormal signs, the purpose of early-stage accurate screening is achieved for detection of occ