The experimental data reorganization and information synthesis: Take radiation refrigeration experiment for example

Experimental data mining is very important in the information discovery. Lots of data analysis is conducted in order to build the relative expression or correlation. However, the implicit parameters or implicit procedure parameters are usually ignored because a number of clear functions about the data exist. In fact, some new knowledge desired for the specific physical process and properties can be gotten by rebuilding the relationship among the experiment data. This paper presents a new data mining method to analysis the data completely and precisely, data reorganization and information synthesis, and its effect is proved through an actual experiment, radiation refrigeration experiment.