The Application of a Grey Markov Model to Forecasting Annual Maximum Water Levels at Hydrological Stations

Compared with traditional real-time forecasting,this paper proposes a Grey Markov Model(GMM) to forecast the maximum water levels at hydrological stations in the estuary area.The GMM combines the Grey System and Markov theory into a higher precision model.The GMM takes advantage of the Grey System to predict the trend values and uses the Markov theory to forecast fluctuation values,and thus gives forecast results involving two aspects of information.The procedure for forecasting annul maximum water levels with the GMM contains five main steps:1) establish the GM(1,1) model based on the data series;2) estimate the trend values;3) establish a Markov Model based on relative error series;4) modify the relative errors caused in step 2,and then obtain the relative errors of the second order estimation;5) compare the results with measured data and estimate the accuracy.The historical water level records(from 1960 to 1992) at Yuqiao Hydrological Station in the estuary area of the Haihe River near Tianjin,China are utilized to calibrate and verify the proposed model according to the above steps.Every 25 years' data are regarded as a hydro-sequence.Eight groups of simulated results show reasonable agreement between the predicted values and the measured data.The GMM is also applied to the 10 other hydrological stations in the same estuary.The forecast results for all of the hydrological stations are good or acceptable.The feasibility and effectiveness of this new forecasting model have been proved in this paper.

Digital Twin-based Quality Management Method for the Assembly Process of Aerospace Products with the Grey-Markov Model and Apriori Algorithm

The assembly process of aerospace products such as satellites and rockets has the characteristics of single-or small-batch production,a long development period,high reliability,and frequent disturbances.How to predict and avoid quality abnormalities,quickly locate their causes,and improve product assembly quality and efficiency are urgent engineering issues.As the core technology to realize the integration of virtual and physical space,digital twin(DT)technology can make full use of the low cost,high efficiency,and predictable advantages of digital space to provide a feasible solution to such problems.Hence,a quality management method for the assembly process of aerospace products based on DT is proposed.Given that traditional quality control methods for the assembly process of aerospace products are mostly post-inspection,the Grey-Markov model and T-K control chart are used with a small sample of assembly quality data to predict the value of quality data and the status of an assembly system.The Apriori algorithm is applied to mine the strong association rules related to quality data anomalies and uncontrolled assembly systems so as to solve the issue that the causes of abnormal quality are complicated and difficult to trace.The implementation of the proposed approach is described,taking the collected centroid data of an aerospace product’s cabin,one of the key quality data in the assembly process of aerospace products,as an example.A DT-based quality management system for the assembly process of aerospace products is developed,which can effectively improve the efficiency of quality management for the assembly process of aerospace products and reduce quality abnormalities.

基于灰色马尔可夫模型的西安市商品房销售均价预测

房地产价格是人们非常关注的经济动态问题,文章基于灰色系统理论、采用灰色预测法刻画西安市商品房销售均价的发展趋势,运用马尔科夫理论刻画西安市商品房销售均价的随机波动特性,使用Grey-Markov模型预测西安市商品房销售均价波动。通过比较两种模型预测的结果,发现Grey-Markov模型能够提高预测的精度。

M市1987～2000年居民意外伤害死亡率灰色-马尔柯夫趋势研究

目的 探索安徽省马鞍山市 1987～ 2 0 0 1年居民意外伤害死亡Grey -Markov趋势。方法 用GM(1,1)模型对居民意外伤害死亡率时间序列进行预测 ,建立居民意外伤害死亡率Grey -Markov预测模型。结果 马鞍山市 2 0 0 1年居民意外伤害死亡率Grey -Markov预测值 2 4 .4 4 / 10 5。结论 马鞍山市 2 0 0 1年居民意外伤害死亡率低于 2 0 0 0年 (2 4 .2 1/ 10 5) ,但伤害作为威胁人民健康的重要公共卫生问题应引起有关部门的高度重视。