全球变暖使得北极冰层厚度和冰层覆盖面积逐年减少，北极航道通航有望成为现实，而船舶冰困风险预警是实现北极航行安全的重点内容和难点问题。本项目首先面向通航环境信息资源的数字化，研究北极航道要素的灰信息特征及信息融合技术；其次分别从时间特征、空间位置特征、时空特征三个维度，考虑环境风险因素的时滞性和周期性，建立数字化灰信息关联模型群，研究北极航道环境风险因素与船舶航行状态的映射(互动)关系，开展北极航道船舶冰区航行环境风险因素识别和状态划分；然后利用滚动预测思想和模式识别方法，建立数字化灰信息多变量滚动预测模型和灰色面板耦合灾变预测模型，从系统宏观与因素微观两个角度对北极航道船舶航行冰困事故的的风险测度、形成概率及灾害程度进行预测和预警；最后完成北极东北航道船舶冰困风险控制对策制定及效果仿真。项目研究成果对建立数字化灰信息理论，推动北极航行安全管理系统的信息化和智能化具有重要的科学和现实意义。

Since the thickness and coverage area of Arctic ice decrease year by year along with the Global warming, the navigation of Arctic Sea routes is expected to become a reality. However, the risk warning of ship besetting in ice is the key point and difficult problem to achieve the safety of Arctic navigation. Firstly, this project studies the grey information characteristics and information fusion technology of the elements of the Arctic Sea routes, facing the digitalization of information resources of navigation environment. Then, on the view of three dimension features, including time, space location, and spatial and temporal characteristics, the group of digital grey information correlation models is established considering the delay and periodicity of the risk factors, to research the mapping relation between risk factors of Arctic Sea routes environment and navigation states of ship, as well as the recognition of risk factors and the division of navigation states. Thirdly, multi variable grey rolling prediction models of digital information and grey panel coupling catastrophe prediction models are constructed through the idea of rolling prediction and the method of pattern recognition. They are used to measure the risk and probability, and also forecast and early warn the degree of disaster to the ship besetting in ice accidents of Arctic Sea routes from the macro and micro aspects. Finally, the control strategies and simulation results of ship besetting in ice risk of the Arctic Northeastern Sea routes are completed. Based on the above research, the project would build the theory of digital grey information, and has momentous scientific and practical significance for promoting the information and intelligence of Arctic navigation safety management system.