Since 2002, an artificial water and sediment regulation(AWSR) has been carried out, which largely reduced water and sediment discharged from the Yellow River into the Bohai Sea. Although the sediment transport in the ...Since 2002, an artificial water and sediment regulation(AWSR) has been carried out, which largely reduced water and sediment discharged from the Yellow River into the Bohai Sea. Although the sediment transport in the Yellow River Mouth(YRM) has been observed and modeled intensively since AWSR, but preferentially for the non-storm conditions. In this study, a three-dimensional current-wave-sediment coupled model, DHI-MIKE numerical model, was used to examine the seasonal suspended-sediment transport in the YRM after the AWSR. Results show that the seasonal distribution of suspended-sediments in the YRM is dominated by wind and wave rather than river input. The major transport pathway of suspended-sediments is from the western Laizhou Bay to the Bohai Strait during the winter monsoon, especially in storm events. In addition, about 66% of the river sediments deposit within 30 km of the YRM, which is smaller than previous estimations. It suggests that the YRM has been eroded in recent decades.展开更多
In agriculture,insect pests must be identified at the initial stage of infestation to avoid their spread in the field.Leaf folders(cnaphalocrocis medinalis)and yellow stemborers(scirpophaga incertulas)are destructive ...In agriculture,insect pests must be identified at the initial stage of infestation to avoid their spread in the field.Leaf folders(cnaphalocrocis medinalis)and yellow stemborers(scirpophaga incertulas)are destructive pests of paddy crops,which are causing severe yield loss.Manual identification of insect pests in the crop is time-consuming,tedious,and ineffective.This paper focuses on a light trap based four-layer deep neural network with search and rescue optimization(DNN-SAR)method to identify leaf folders and yellow stemborers.Light traps are designed to lure the insects in the paddy field and the images of trapped insects are analyzed using the proposed detection method.In the DNN-SAR,images are contrastenhanced using deer hunting algorithm,impulse noise is removed with fast average group filter,and segmented using social ski-driver optimization.The search and rescue optimization algorithm is used for the selection of optimal weights in the deep neural network,which has improved the convergence rate,lowered the complexity of learning,and improved the accuracy of detection.The proposed method outperformed the existing methods and achieved 98.29%pest detection accuracy.展开更多
基金supported by the National Natural Science Foundation of China (Nos. 41476030, U1706215, and 41406081)the Project of Taishan Scholar
文摘Since 2002, an artificial water and sediment regulation(AWSR) has been carried out, which largely reduced water and sediment discharged from the Yellow River into the Bohai Sea. Although the sediment transport in the Yellow River Mouth(YRM) has been observed and modeled intensively since AWSR, but preferentially for the non-storm conditions. In this study, a three-dimensional current-wave-sediment coupled model, DHI-MIKE numerical model, was used to examine the seasonal suspended-sediment transport in the YRM after the AWSR. Results show that the seasonal distribution of suspended-sediments in the YRM is dominated by wind and wave rather than river input. The major transport pathway of suspended-sediments is from the western Laizhou Bay to the Bohai Strait during the winter monsoon, especially in storm events. In addition, about 66% of the river sediments deposit within 30 km of the YRM, which is smaller than previous estimations. It suggests that the YRM has been eroded in recent decades.
文摘In agriculture,insect pests must be identified at the initial stage of infestation to avoid their spread in the field.Leaf folders(cnaphalocrocis medinalis)and yellow stemborers(scirpophaga incertulas)are destructive pests of paddy crops,which are causing severe yield loss.Manual identification of insect pests in the crop is time-consuming,tedious,and ineffective.This paper focuses on a light trap based four-layer deep neural network with search and rescue optimization(DNN-SAR)method to identify leaf folders and yellow stemborers.Light traps are designed to lure the insects in the paddy field and the images of trapped insects are analyzed using the proposed detection method.In the DNN-SAR,images are contrastenhanced using deer hunting algorithm,impulse noise is removed with fast average group filter,and segmented using social ski-driver optimization.The search and rescue optimization algorithm is used for the selection of optimal weights in the deep neural network,which has improved the convergence rate,lowered the complexity of learning,and improved the accuracy of detection.The proposed method outperformed the existing methods and achieved 98.29%pest detection accuracy.
