海洋灾害大数据分析的系统模型研究及应用

项目名称： 海洋灾害大数据分析的系统模型研究及应用

项目编号： No.41476101

项目类型： 面上项目

立项/批准年度： 2015

项目学科： 天文学、地球科学

项目作者： 邵峰晶

作者单位： 青岛大学

项目金额： 95万元

中文摘要： 海洋灾害预测影响要素多，关系复杂且具有开放性，若干问题难以建模或即使建模也很难求解。随着海洋大数据时代到来，借助大数据分析从相互耦合的数据和已知特征、机理中发现未知规律与特征，可为海洋灾害分析预测提供新的手段。目前大数据分析仅停留在面向问题、主题，而针对海洋灾害预测的复杂性、海量性、开放性和实时性，实现其大数据分析，需建立可描述和分析复杂多要素及其关系的系统级模型及模型相关性质高效分析方法。本项目拟在复合网模型扩展研究基础上，给出海洋灾害大数据分析系统模型；将海洋灾害若干分析问题转化为该模型的拓扑和动力学等性质分析；给出动态组网运算及分析算法。为海洋灾害大数据的规律提取、机理发现提供模型与分析方法支撑。对已获取的赤潮等观测、监测数据及机理，建立赤潮、浒苔复合网络，基于模型性质的分析方法，分析其相关性质，发现赤潮、浒苔爆发的若干未知机理及其关系、演化规律，以期为赤潮、浒苔预测提供辅助支持。

中文关键词： 大数据；系统模型；复杂网络；海洋预灾

英文摘要： There are many factors affecting marine disaster prediction. Relationships among these factors are complex, which are evolving with time and space. A number of problems are difficult for modeling, or even when it could be modeled calculating is also difficult. With era of ocean big data coming, it's possible for discovering characters and laws from interacted data and known knowledge by big data analyzation. Now big data analyzation mainly focus on given problem or theme. However, problems according to marine disorders prediction is rather complex. Data are also massive. Establishing a system-level model which could describe and analyze complex factors and their complex relationships are very important. And it's also meaning for proposing efficient methods of analyzing characters of the model. Therefore, system model of big data analyzation of marine disorders will be proposed by strenghtening multi-subnet composited complex network presented in previous study. Topological properties and dynamic properties will be studied. Dynamic reorganization of networks will be given. And algorithms of calculating topological and dynamic properties also will be given. Those could be used for discovering laws and mechanisms of big data of marine disorders. On those basis, composited complex network of red tides, enteromorpha marine disaster will be constructed by known knowledge and acquired data. By analyzing properties of the model, laws of occurrence, development and death of red tide and enteromorpha will be picked up, which could provide auxiliary support for marine disaster forecasting.

英文关键词： big data;system model;complex network;marine disaster prediction