摘要
为了解决目前常用预测模型对随机波动性较大数据预测精度偏低的问题,文章在灰色预测GM(1,1)的基础上引入马尔可夫状态转移矩阵,建立了灰色马尔可夫预测模型(GMM),并将该法运用到煤矿顶板致死人数的预测中。经计算GMM模型的预测平均相对误差为1.181%,最大相对误差3.426%,与GM(1,1)法相比,后者精度分别提高了21倍和13倍。
In order to solve the problem that the forecast accuracy of commen prediction model is low for the data which has a large random volatility,the Markov state shift matrix was introduced into the Grey prediction,and the Grey Markov prediction model(GMM) was established. The method is applied in the prediction of the death from the roof accident,the average relative error of the prediction is 1. 181% and the maximum relative error is 3. 426%,which has increased by 21 times and 13 times respectively compared with GM(1,1) method.
出处
《工业安全与环保》
北大核心
2017年第8期9-12,共4页
Industrial Safety and Environmental Protection
基金
国家自然科学基金(51574093)
贵州省科学技术基金(黔科合J字[2015]2049号)
贵州省科技厅
贵州大学联合资金计划资助项目(黔科合LH字[2014]7654)
贵州大学引进人才项目(贵大人基合字(2015)30号)
关键词
灰色系统
马尔可夫预测
转移概率
顶板事故
gray system
Markov prediction
transition probability
roof accident