2篇
您的检索式：作者名="Hongshi Han"
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| 1 | Rapid Prediction Model for Urban Floods Based on a Light Gradient Boosting Machine Approach and Hydrological–Hydraulic Model显示文摘Global climate change and sea level rise have led to increased losses from flooding.Accurate prediction of floods is essential to mitigating flood losses in coastal cities.Physically based models cannot satisfy the demand for real-time prediction for urban flooding due to their computational complexity.In this study,we proposed a hybrid modeling approach for rapid prediction of urban floods,coupling the physically based model with the light gradient boosting machine(LightGBM)model.A hydrological–hydraulic model was used to provide sufficient data for the LightGBM model based on the personal computer storm water management model(PCSWMM).The variables related to rainfall,tide level,and the location of flood points were used as the input for the LightGBM model.To improve the prediction accuracy,the hyperparameters of the LightGBM model are optimized by grid search algorithm and K-fold cross-validation.Taking Haidian Island,Hainan Province,China as a case study,the optimum values of the learning rate,number of estimators,and number of leaves of the LightGBM model are 0.11,450,and 12,respectively.The Nash-Sutcliffe efficiency coefficient(NSE)of the LightGBM model on the test set is 0.9896,indicating that the LightGBM model has reliable predictions and outperforms random forest(RF),extreme gradient boosting(XGBoost),and k-nearest neighbor(KNN).From the LightGBM model,the variables related to tide level were analyzed as the dominant variables for predicting the inundation depth based on the Gini index in the study area.The proposed LightGBM model provides a scientific reference for flood control in coastal cities considering its superior performance and computational efficiency. | Kui Xu Zhentao Han Hongshi Xu Lingling Bin | 2023 | International Journal of Disaster Risk Science2023，14，1： | 0 |
| 2 | Genome-wide association study exposed the pleiotropic genes for yield-related and oil quality traits in Brassica napus L.显示文摘Oilseed rape(Brassica napus L.) is an allotetraploid(AACC,2n=38) crop,valued for its edible oil and protein content.seed yield and nutritional composition of rapeseed are influenced by its yield and oil quality traits.However,the genetic basis of yield-related and oil-quality traits remain ambiguous.A panel of 266 diversified oilseed rape accessions was genotyped using 223 simple sequence repeat(SSR) markers covering all 19 chromosomes to identify significant markers associated with yield and quality traits.Twelve yield-related and six quality traits were investigated in two consecutive years(2014 and 2015),with three replications in two environments(Changshun,CS;and Qinghe,QH).Using the model GLM with population structure and kinship(Q+K),a total of 25 significant SSR markers(P <0.001) were detected to be associated with these twelve yield-related and six quality traits,explaining 4.56%-19.17% of the phenotypic variation for each trait.Based on these markers,BnaA03g23490D, BnaC09g46370D,BnaA07g37150D,BnaA01g32590D, and BnaC09g37280D were identified as pleiotropic genes controlling multiple traits.These candidate genes illustrated the potential for the genetic understanding of yield and oil quality traits.Most importantly,these significant markers can be used for marker-assisted breeding of oilseed rape in different environments. | Yang Xiang M.M.U.Helal Longbing Liang Minqin Zhang Hongshi Han Xianglai Dai Jixian Zhao Dalun Chen Xianping Wang Min Li Chuanji Zhao | 2023 | Oil Crop Science2023，8，3： | 0 |
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