In order to forecast the cotton output of China in the year 2011, Gray Metabolic Forecast Model is established based on both the Gray Forecast Model and the Metabolic Theory. According to the actual situation, forecas...In order to forecast the cotton output of China in the year 2011, Gray Metabolic Forecast Model is established based on both the Gray Forecast Model and the Metabolic Theory. According to the actual situation, forecast results of conventional GM (1, 1) Model and Metabolism GM (1, 1) Model are analyzed, showing that Metabolic Forecast Model has higher precision than the conventional forecast model. Therefore, Metabolism GM (1, 1) Model is used to forecast the cotton output of China in the year 2011, which is 614 968.3 thousand tons.展开更多
The gray GM( 1,1) prediction model and Logistic equation gray prediction model were established separately,and then the combined prediction model was established. Taking the water consumption in Ningxia Hui Autonomous...The gray GM( 1,1) prediction model and Logistic equation gray prediction model were established separately,and then the combined prediction model was established. Taking the water consumption in Ningxia Hui Autonomous Region from 2006 to 2012 as modeling data,the total water consumption of the whole region of Ningxia in 2018-2020 was analyzed and predicted. The results show that the accuracy of the three prediction models meets the accuracy requirements,but the gray GM( 1,1) and combined prediction models better conform to the actual situation and have better applicability.展开更多
The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived usi...The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.展开更多
文摘In order to forecast the cotton output of China in the year 2011, Gray Metabolic Forecast Model is established based on both the Gray Forecast Model and the Metabolic Theory. According to the actual situation, forecast results of conventional GM (1, 1) Model and Metabolism GM (1, 1) Model are analyzed, showing that Metabolic Forecast Model has higher precision than the conventional forecast model. Therefore, Metabolism GM (1, 1) Model is used to forecast the cotton output of China in the year 2011, which is 614 968.3 thousand tons.
基金Supported by Ningxia Natural Science Foundation (NZ17032)Key Research and Development Program of Ningxia (2018BEG03008)+1 种基金First-rate Discipline (Hydraulic Engineering Discipline) Project of Colleges and Universities in Ningxia (NXYLXK2017A03)National Natural Science Foundation (51269022)
文摘The gray GM( 1,1) prediction model and Logistic equation gray prediction model were established separately,and then the combined prediction model was established. Taking the water consumption in Ningxia Hui Autonomous Region from 2006 to 2012 as modeling data,the total water consumption of the whole region of Ningxia in 2018-2020 was analyzed and predicted. The results show that the accuracy of the three prediction models meets the accuracy requirements,but the gray GM( 1,1) and combined prediction models better conform to the actual situation and have better applicability.
基金The National Natural Science Foundation of China(No.51778485).
文摘The mixed model of improved exponential and power function and unequal interval gray GM(1,1)model have poor accuracy in predicting the maximum pull-out load of anchor bolts.An optimal combination model was derived using the optimally weighted combination theory and the minimum sum of logarithmic squared errors as the objective function.Two typical anchor bolt pull-out engineering cases were selected to compare the performance of the proposed model with those of existing ones.Results showed that the optimal combination model was suitable not only for the slow P-s curve but also for the steep P-s curve.Its accuracy and stable reliability,as well as its prediction capability classification,were better than those of the other prediction models.Therefore,the optimal combination model is an effective processing method for predicting the maximum pull-out load of anchor bolts according to measured data.
