摘要水路运输以其载重量大、成本低、投资省等技术经济特征，在综合运输系统中占据着重要地位，水路运输量的不断增长，确保航运市场始终在高位运行。在水运市场的蓬勃发展促进了水运力量的不断壮大的同时，许多水路交通险情和交通事故阻碍了水运市场的进一步发展。30539
风灾事故在湖区交通事故中是常见事故之一。船舶在大风浪中航行会遭到大风浪的砰击、拍底、淹侵和打空车等，可能造成货损、船损，甚至发生交通事故。因此，在内河海事交通管理中，迫切需要针对船舶航行安全监管的湖区（小范围）风速风力监测与预警，以保障大风等恶劣天气条件下船舶的安全管理。
课题针对某湖区风速监测数据，截用其中较平滑的近200个数据，使用神经网络法，持续法和指数滑动法，以及它们两两组合和三者综合的组合模型，综合加权预测数据，实现风速的预测与预警。同时综合考虑风速对船舶的航行影响，实现大风天气条件下船舶的安全管理。
关键词 船舶交通安全 风速预测 神经网络法 持续法
毕业论文设计说明书外文摘要
Title Research on the wind speed forecast and early warning technology based on the maritime safety supervision
Abstract
Waterway transport with its carrying capacity, low cost, and other economic characteristics of technology investment, in an integrated transport system, occupies an important position, growing waterway traffic, to ensure that the shipping market is always run high. In the booming shipping market and promote the waterway force has grown while many waterways traffic dangers and accidents hindered the further development of water transport market.
Hurricane accident is a common accident in a traffic accident in the Lake District. Ships sailing in heavy sea would have been large waves slamming, flop, flood and other inundation and hit empty, heave and yaw other adverse movement may cause damage, boat damage, or even traffic accidents. Therefore, in the inland marine traffic management, the urgent need for (small-scale) wind wind monitoring and early warning for navigation safety supervision Lakes to protect the safety management of high winds and other bad weather conditions the ship.
Subject against a lake wind speed monitoring data, which smoother cut by nearly 200 data, using a neural network method, continuous method and index sliding method, and the combination of model combinations of two and three are comprehensive, integrated weighted prediction data to achieve wind forecasting and warning. At the same time considering the wind speed of the ship's voyage, secure management of ships under windy weather conditions.
Keywords Ship Traffic Safety Wind Speed Forecasting Neural Network Persistence Method
目 次
第一章 绪论 1
1.1 湖区风速预测方法与预警研究的背景 1
1.2目的和意义 1
1.3现状 1
第二章 湖区风速预测方法 5
2.1风速的概念与规律 5
2.2使用BP神经网络法进行风速预测 6
2.3使用持续法进行风速预测 12
2.4使用指数平滑法预测风速 13
2.4 三种方法比较 16
2.5 组合预测 16
第三章 湖区船舶交通安全预警 20
3.1 船舶交通 20
3.2 船舶交通安全 20
3.3风速对船舶交通安全的影响 21
3.4改进措施 24
结论与展望 25
致谢 26
参考文献 27 基于海事安全监管的湖区风速预测预警技术研究:http://www.751com.cn/zidonghua/lunwen_26291.html