期刊文献+
共找到2篇文章
< 1 >
每页显示 20 50 100
基于BP神经网络的表层悬浮物浓度预测模型
1
作者 胡田 李贤哲 于徐华 《上海船舶运输科学研究所学报》 2016年第2期72-76,共5页
悬浮物浓度是海洋沉积动力学领域中的重要参数,对其进行准确预测及定量研究绿潮爆发期间悬浮物所带来的影响具有重要意义。将BP(Back Propagation)神经网络应用于表层悬浮物浓度的预测中:将流速、水深、波高、温度、盐度及风速等影响悬... 悬浮物浓度是海洋沉积动力学领域中的重要参数,对其进行准确预测及定量研究绿潮爆发期间悬浮物所带来的影响具有重要意义。将BP(Back Propagation)神经网络应用于表层悬浮物浓度的预测中:将流速、水深、波高、温度、盐度及风速等影响悬浮物浓度的因素作为BP神经网络的输入单元,通过对苏北近岸海域进行调查,获取用于训练和预测的数据,建立表层悬浮物浓度的BP神经网络预测模型。将预测结果与多因子逐步回归拟合结果进行比较,得到逐步回归预测结果的平均相对误差为24.13%,BP神经网络预测结果的平均相对误差仅为13.02%。由此可见,BP神经网络预测结果具有更高的精度,可为苏北近岸海域表层悬浮物浓度的准确预测提供更可靠的途径。 展开更多
关键词 BP神经网络 悬浮物浓度 苏北近岸海域 预测
下载PDF
Impact of climatic change on sea surface temperature variation in Subei coastal waters,East China 被引量:2
2
作者 王然 于非 《Chinese Journal of Oceanology and Limnology》 SCIE CAS CSCD 2014年第6期1406-1413,共8页
Sea surface temperature (SST) variation in the Subei coastal waters, East China, which is important for the ecological environment of the Yellow Sea where Enteromorphaprolifera blooms frequently, is affected by the ... Sea surface temperature (SST) variation in the Subei coastal waters, East China, which is important for the ecological environment of the Yellow Sea where Enteromorphaprolifera blooms frequently, is affected by the East Asian winter monsoon (EAWM), El Nifio-Southem Oscillation (ENSO), and Pacific Decadal Oscillation (PDO). In this study, correlations between climatic events and SST anomalies (SSTA) around the Subei (North Jiangsu Province, East China) Coast from 1981-2012 are analyzed, using empirical orthogonal function (EOF) and correlation analyses. First, a key region was determined by EOF analysis to represent the Subei coastal waters. Then, coherency analyses were performed on this key region. According to the correlation analysis, the EAWM index has a positive correlation with the spring and summer SSTA of the key region. Furthermore, the Nifio3.4 index is negatively correlated with the spring and summer SSTA of the key region 1 year ahead, and the PDO has significant negative coherency with spring SSTA and negative coherency with summer SSTA in the key region 1 year ahead. Overall, PDO exhibits the most significant impact on SSTA of the key region. In the key region, all these factors are correlated more significantly with SSTA in spring than in summer. This suggests that outbreaks ofEnteromorpha prolifera in the Yellow Sea are affected by global climatic changes, especially the PDO. 展开更多
关键词 sea surface temperature (SST) Pacific Decadal Oscillation (PDO) El Nifio-Southem Oscillation(ENSO) East Asian winter monsoon (EAWM) Subei coastal waters
下载PDF
上一页 1 下一页 到第
使用帮助 返回顶部