Human Injury Risk Prediction of Large Equipment Confined Space Operations

There are two folders in total, folder 1 is named "Comprehensive Assessment of Human Joint Injury Risk" and folder 2 is named "Prediction of Human Joint Injury Risk". The folder "Comprehensive Assessment of Human Joint Injury Risk" contains two code files, "fuzzy method. py" (6KB) and "robustness check of fuzzy functions" (10KB), one table file "data. xlsx" (137KB), and one txt instruction file "readme. txt". The code data is all running on Python 3.11. The table file "data. xlsx" consists of 980 rows and 13 columns, representing 980 pieces of data.

Each piece of data is composed of 13 sub-factors, and the "fuzzy method" file can be used to obtain the comprehensive assessment results of joint risk. The robustness of the "robustness check of fuzzy functions" verifiable method is adopted. The 13 sub-factors represent the risk index of injury to various joints in the human body (calculated by the ratio of joint load to safe load values), namely right wrist injury risk index, left wrist injury risk index, right elbow injury risk index, left elbow injury risk index, right shoulder injury risk index, left shoulder injury risk index, right hip injury risk index, left hip injury risk index, right knee injury risk index, left knee injury risk index, right ankle injury risk index, left ankle injury risk index, and lower back injury risk index. The folder "Prediction of Human Joint Injury Risk" contains a code file, "prediction model. py" (3KB), two table file“data for risk prediction.xls” (310KB), “data for risk prediction_one hot coding.xls”(350KB), and a text description file "readme. txt".The code data is all running on Python 3.11. The table file "data for risk prediction. xls" consists of 980 rows and 26 columns, representing 980 pieces of data.