A Time Series Short-Term Prediction Method Based on Multi-Granularity Event Matching and Alignment

Accurate forecasting of time series is crucial across various domains.Many prediction tasks rely on effectively segmenting,matching,and time series data alignment.For instance,regardless of time series with the same granularity,segmenting them into different granularity events can effectively mitigate the impact of varying time scales on prediction accuracy.However,these events of varying granularity frequently intersect with each other,which may possess unequal durations.Even minor differences can result in significant errors when matching time series with future trends.Besides,directly using matched events but unaligned events as state vectors in machine learning-based prediction models can lead to insufficient prediction accuracy.Therefore,this paper proposes a short-term forecasting method for time series based on a multi-granularity event,MGE-SP(multi-granularity event-based short-termprediction).First,amethodological framework for MGE-SP established guides the implementation steps.The framework consists of three key steps,including multi-granularity event matching based on the LTF(latest time first)strategy,multi-granularity event alignment using a piecewise aggregate approximation based on the compression ratio,and a short-term prediction model based on XGBoost.The data from a nationwide online car-hailing service in China ensures the method’s reliability.The average RMSE(root mean square error)and MAE(mean absolute error)of the proposed method are 3.204 and 2.360,lower than the respective values of 4.056 and 3.101 obtained using theARIMA(autoregressive integratedmoving average)method,as well as the values of 4.278 and 2.994 obtained using k-means-SVR(support vector regression)method.The other experiment is conducted on stock data froma public data set.The proposed method achieved an average RMSE and MAE of 0.836 and 0.696,lower than the respective values of 1.019 and 0.844 obtained using the ARIMA method,as well as the values of 1.350 and 1.172 obtained using the k-means-SVR method.

Analysis of Climatic Conditions for the Growth of Longhui Lilium brownii var.viridulum

Based on temperature,precipitation and sunshine data at Longhui National Station during 1981-2021,temperature at 22 regional stations during 2011-2021,and lily planting information of Longya Lily Base,the feasibility of meteorological conditions for the growth of Lilium brownii var.viridulum was analyzed.The results showed that in general,the climatic conditions in Longhui were suitable for planting L.brownii var.viridulum.Among them,the south hilly area was the most suitable climate area,and the north mountain area was the suitable climate area,and the northwest mountain area was the more suitable climate area.It should sufficiently use the climatic conditions of Longhui,do a good job in meteorological service of L.brownii var.viridulum,and provide favorable meteorological guarantee for farmers,to reduce the impact of adverse meteorological conditions on L.brownii var.viridulum,and improve the economic benefits of lily production.

Study on Risk Assessment of Summer Rainstorm Disaster and Countermeasures for Disaster Prevention and Mitigation in Shaoyang City

Using summer(June-August)precipitation observation data in 10 representative stations of Shaoyang City during 1971-2021 and disaster data caused by summer rainstorm in nine counties(cities)and four districts of Shaoyang during 1981-2021,statistical analysis on summer rainstorm and its caused disaster in Shaoyang was conducted,and spatial and temporal characteristics of summer rainstorm and spatial distribution rule of disaster were found out.The results showed that(1)the rainstorm disaster in Shaoyang City occurs almost every year and is highly seasonal.(2)Rainstorm disaster loss is the first of other meteorological disasters.(3)The summer rainstorm disaster has the characteristics of sudden and destructive.On this basis,the relative grades of rainstorm disaster risk degree and disaster loss degree were divided,and the risk assessment of rainstorm and flood disaster in Shaoyang City was made,and the disaster prevention and mitigation measures and countermeasures were put forward.The research could provide scientific decision basis for party and government departments guiding flood fighting and disaster relief.