Academic Journal of Computing & Information Science, 2023, 6(1); doi: 10.25236/AJCIS.2023.060106.
Kaimin Li, Guang Li, Yuanyuan Zhang
Baoshan University, Baoshan, Yunnan, 678000, China
Taking the monthly rainfall data of 16 prefectures and cities in Yunnan Province from 2012 to 2020 as the research object, an ARIMA time series model is established based on big data calculation. First, we use the cluster analysis method to divide all regions into three categories according to the distribution characteristics of rainfall and select a representative city from each category to study the rainfall distribution. Then, according to the results of the ADF test, the method using phase and seasonal differences is used to eliminate the non-stationary and seasonal trends of the series. Finally, the ARIMA prediction model of rainfall distribution in Kunming, Dali, and Pu'er is obtained by combining the sequence autocorrelation and partial autocorrelation analysis diagram to determine the values of various parameters in the ARIMA model. The prediction accuracy of the model is high, and the residual sequence is a white noise sequence, which has a good fitting effect. It effectively predicts the fluctuation law of rainfall and provides an early warning mechanism for drought, flood, debris flow, and other disasters.
rainfall, cluster analysis, ADF test, ARIMA model by big data computation
Kaimin Li, Guang Li, Yuanyuan Zhang. Study on Rainfall Distribution in Yunnan Province Based on ARIMA Model by Big Data Computation. Academic Journal of Computing & Information Science (2023), Vol. 6, Issue 1: 32-41. https://doi.org/10.25236/AJCIS.2023.060106.
[1] Dong Xuyan, Lu Ying. Study on Spatial-temporal Variation of Rainfall and its Impact on Distribution Pattern of Water Resources in Yunnan Province [J]. China population • resources and environment, 2017,27 (S2): 140-144. (In Chinese)
[2] Dawoud I, Kaciranlar S . An Optimal k of kth MA-ARIMA Models Under a Class of ARIMA model[J]. Communications in Statistics, 2016, 46(12):5754-5765.
[3] Ma Lihua. Research on Time Series Modeling of Long-term Meteorological Data [D]. Kunming University of technology, 2019. (In Chinese)
[4] Xi Liping, Cai Wenqing, Wu Haiying. Research on Precipitation Prediction Model of Wuwei County Based on Time Series Analysis [J]. Journal of Anhui Vocational and Technical College of water resources and hydropower, 2018,18 (01): 50-53. (In Chinese)
[5] Wang Xihua, Lu Wenxi, Chu Haibo, Chen Sheming. Application of ARMA-GARCH Model Based on Wavelet Analysis in Precipitation Forecast [J]. Water saving irrigation, 2011 (05): 52-56. (In Chinese)
[6] Hartigan, J. A. and M.A.Wong. A K-Means Clustering Algorithm[J]. Applied Statistics, 1979, 28: 100-108.
[7] EA Robinson, Silvia M T. The Box-Jenkins Approach[J]. Nature Reviews Genetics, 1979, 3(11): 883-889.
[8] Yao Dengkui, Duan gonghao. Rainfall trend analysis and prediction of Wuhan mayor sequence based on seasonal SARIMA model [J]. Groundwater, 2022,44 (02): 166-168. (In Chinese)
[9] Chen Jiawei. Prediction and research of landslide displacement based on ARIMA model and PSO-BP neural network algorithm [D]. Three Gorges University, 2020. (In Chinese)
[10] Chen Shan. Research on water quality time series data cleaning and early warning in Qiantang River Basin [D]. Hangzhou University of Electronic Science and technology, 2022. (In Chinese)