汽车工况构建

说明：  通过实际采集到的数据，数显通过数据预处理，进行不良数据的清洗，然后通过PCA降维，k均值聚类提取运动学片段，建立运动学片段库，通过随机策略提取运动学片段构成汽车行驶工况。(Through the actual collected data, the digital display cleans the bad data through data pretreatment, and then extracts the kinematics fragments through PCA dimensionality reduction, K-means clustering, establishes the kinematics fragments library, and extracts the kinematics fragments through random strategy to form the driving conditions of the vehicle.)

backup_V02_withAllFeature, 0 , 2019-09-23
backup_V02_withAllFeature\Motor.mat, 1448562 , 2019-09-20
backup_V02_withAllFeature\PCA_process.m, 1465 , 2019-09-21
backup_V02_withAllFeature\Position.mat, 1568456 , 2019-09-20
backup_V02_withAllFeature\Velocity.mat, 1221993 , 2019-09-20
backup_V02_withAllFeature\construct_fea_mat.m, 2226 , 2019-09-21
backup_V02_withAllFeature\construct_speed_curve.m, 1820 , 2019-09-21
backup_V02_withAllFeature\create_speed_interval.m, 1195 , 2019-09-20
backup_V02_withAllFeature\data_process.m, 869 , 2019-09-20
backup_V02_withAllFeature\discriminate_condition.m, 680 , 2019-09-21
backup_V02_withAllFeature\evaluate_func.m, 663 , 2019-09-21
backup_V02_withAllFeature\generate_kinematic_lib.m, 691 , 2019-09-20
backup_V02_withAllFeature\kinematic_split.m, 5038 , 2019-09-21
backup_V02_withAllFeature\main_test.m, 1726 , 2019-09-21
backup_V02_withAllFeature\pic_another.tif, 66555 , 2019-09-21
backup_V02_withAllFeature\pic_origin.fig, 35738 , 2019-09-21
backup_V02_withAllFeature\pic_origin.tif, 64997 , 2019-09-21