Applied the GM(1,1) for groundwater level supplement in Jiao-Xi hot spring area, Taiwan

The administration of hot spring in Taiwan has collected and checked the data of hot spring level these years. Unique temperature and quality of the hot spring usually caused the device recorded and missing data. The data analysis used the gray theory in order to supplement the data of hot spring level. This study based on observation data of hot spring level, tested and predicted the best model with gray prediction. The best model helped the fragmented part of data fixed, which arranged to produce the complete set of data. In the data of hot spring level in Jiao-Xi, the Hot Spring Park, Guo-Xiao and TaiTzu stations fixed the four batches of the fragmented data using the best model estimation. This study used the best model in each administrations of hot spring. The action made the fragmented data of hot spring level, which included Shin Xiao Shen Station, Shin Xiao Chien Station, Tourist Center Station, Fu Chong Station and Da Zhong Rd. Station during 2011~2014 fixed. The result of the supplementation brought down the gap between the actual hot spring levels in Jiao-Xi.