基于数据挖掘技术的船体毁伤修复能力评价

Assessment of hull damage repair capability based on data mining technology

船体毁伤修复能力评价结果具有重要实际意义,针对当前模型无法准确描述船体毁伤修复能力,使得船体毁伤修复能力评价存在错误率高的缺陷,设计了一种基于数据挖掘技术的船体毁伤修复能力评价模型。首先对船体毁伤修复能力评价原理进行分析,构建船体毁伤修复能力评价的目标函数,然后采用数据挖掘技术中的最小二乘支持向量机对船体毁伤修复能力评价样本进行学习,并对最小二乘支持向量机进行在线性能优化,建立船体毁伤修复能力评价模型,最后在Matlab 2018平台对船体毁伤修复能力评价效果进行测试,测试结果表明,基于数据挖掘技术的船体毁伤修复能力评价正确率超过90%,降低了船体毁伤修复能力评价的时间复杂度,船体毁伤修复能力评价速度更快。

The evaluation result of hull damage repair capability is of great practical significance.In view of the fact that the current model can not accurately describe hull damage repair capability,which leads to high error rate of hull damage repair capability evaluation,in order to improve the accuracy of hull damage repair capability evaluation,a hull damage repair capability evaluation model based on data mining technology is designed.Firstly,hull damage repair is carried out.The principle of capability evaluation is analyzed,and the objective function of hull damage repair ability evaluation is constructed.Then the least squares support vector machine(LSSVM)in data mining technology is used to learn the samples of hull damage repair ability evaluation,and the LSSVM is optimized linearly.The evaluation model of hull damage repair ability is established.Finally,the hull damage repair is carried out on Matlab 2018 platform.The accuracy rate of hull damage repair ability evaluation based on data mining technology is more than 90%,which reduces the time complexity of hull damage repair ability evaluation and makes hull damage repair ability evaluation faster.