海盗袭击事件预警模型

构建一个科学的海盗袭击事件预警模型，可以在海盗袭击事件发生前给出预警信息，大幅降低运输船舶被海盗袭击的概率.采用决策树方法研究海盗袭击事件的严重程度与其他因素的相关性，并以此进行海上预警.以船舶类型、地理区域为模型输入数据，海盗袭击后果为模型输出数据，构建海盗袭击事件预警模型.以东非海域的海盗袭击事件为研究对象进行实例研究，并进行模型检验.结果表明，该方法获得的预测结果远优于随机猜测，证明了模型的有效性和科学性.
A scientific early warning model for pirate attack was built, which can give early warning information before the pirate attack, and greatly reduce the probability of the ship being attacked by pirates. The decision tree method was used to study the correlation between the severity of piracy attacks and other factors, so as to conduct maritime early warning. Taking ship type and geographical area as model input data and pirate attack consequence as model output data, a pirate attack early warning model was constructed. The case study of pirate attacks in East Africa was conducted and model checking was carried out. Results show that the prediction result obtained by this method is much better than that of random guess, which proves the validity and scientificity of the model.