Shi ChunLin
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Featured researches published by Shi ChunLin.
artificial intelligence and computational intelligence | 2010
Shi ChunLin; Jin Zhiqing; Feng Huihui
On the basis of spatial aggregation, the up scaling technique was one of methods for the regional application of crop growth model. In this paper, the aggregation technique of regional soils, varieties and cultivar measures was discussed for regional application of rice growth model in county level, and the difference of rice development and yield among the county stations of Suzhou and Lianyungang, Jiangsu, was explored with experiment data from national agrometeological stations at Kunshan and Ganyu, Jiangsu and RCSODS. The results showed although the development stages were similar among counties, the yield difference was significant, After aggregation of model inputs, the RMSEs between statistical and simulated yields were 742kg/ha and 975kg/ha for Suzhou and Lianyungang respectively, and the NRMSEs were 8.7% and 12.4%, which indicated the spatial aggregation approach for model inputs was suited to regional application of rice growth model.
international symposium on information processing | 2010
Shi ChunLin; Jin Zhiqing; Feng Huihui
Dynamic forecast of crop productivity is critical for food security and decision-making of agriculture manager. Based on the Rice Cultivational Simulation-Optimization and Decision-making System (RCSODS) and aggregation methods on the model inputs, and combined normal year meteorological data and spatial interpolation technique of weather data, the dynamic forecast technique of regional rice productivity was discussed in this study. The model and the aggregation methods were validated with the experimental data from eight National agro meteorological stations located in Jiangsu province and statistical yields. Rice productivity of Jiangsu was forecasted dynamically with observed meteorological data and normal year weather data generated from the monthly meteorological data. The results showed the RMSEs of development stages and yields between simulated and observed values were 5.0 d and 1344kg/ha and the NRMSEs were 1.6% and 16.7% respectively, which indicated RCSODS could simulate the rice development process better and yield well. The RMSE and NRMSE between simulated and statistical county yields were 1081kg/ha and 13.2%, which showed the aggregation method on the meteorological data, soil attributes, variety and cultural method in county level was suitable to the regional application of rice model. The forecast yield would generally be equal to simulated yield with the delay of forecast time.
Scientia Agricultura Sinica | 2009
Liu Yan; Lu JianFei; Cao Hongxin; Shi ChunLin; Liu YongXia; Zhu DaWei; Sun JinYing; Yue YanBin; Wei XiuFang; Tian Pingping; Bao TaiLin
Jiangsu Journal of Agricultural Sciences | 2000
Gao LiangZhi; Jin ZhinQing; Zhang GengSheng; Shi ChunLin; Ge Daokuo
Chinese Journal of Rice Science | 2010
Shi ChunLin; Feng Huihui; Jin Zhiqing; Wang Hua
Jiangsu Journal of Agricultural Sciences | 2000
Gao LiangZhi; Jin Zhiqing; Zheng GuoQing; Feng LiPing; Zhang LiZhong; Shi ChunLin; Ge Daokuo
Archive | 2017
Liu Yang; Feng Yanfang; Shi ChunLin; Liu Xiaoyu; Xuan Shouli
IEEE Conference Proceedings | 2016
Xuan Shouli; Shi ChunLin; Liu Yang; Zhang Wenyu; Cao Hongxin; Xue Changying
Jiangsu Journal of Agricultural Sciences | 2010
Zhu DaWei; Jin Zhiqing; Shi ChunLin
Jiangsu Journal of Agricultural Sciences | 2010
Shi ChunLin; Jin Zhiqing; Tang RiSheng; Zheng Jianchu