Based on the discussion of characteristic and mechanism of the stock prices volatility in Chinese emerging stock markets, this research designs an index system for risk forewarn, and builds up an investment decision m...Based on the discussion of characteristic and mechanism of the stock prices volatility in Chinese emerging stock markets, this research designs an index system for risk forewarn, and builds up an investment decision model based on the forewarn of the market risk signal. Then, on probing into the structure and function of the realization of the model, the paper presents the method of data interface.展开更多
Three forecasting models are set up: the auto\|regressive moving average model, the grey forecasting model for the rate of qualified products P t, and the grey forecasting model for time intervals of the quality cata...Three forecasting models are set up: the auto\|regressive moving average model, the grey forecasting model for the rate of qualified products P t, and the grey forecasting model for time intervals of the quality catastrophes. Then a combined forewarning system for the quality of products is established, which contains three models, judgment rules and forewarning state illustration. Finally with an example of the practical production, this modeling system is proved fairly effective.展开更多
To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-...To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-SVM) multi-classifier and regression machine. For the forecasting model, the methane concentration can be considered as a nonlinear time series and the time series analysis method is adopted to predict the change in methane concentration using LS-SVM regression. For the forewarning model, which is based on the forecasting results, by the multi-classification method of LS-SVM, the methane hazard was identified to four grades: normal, attention, warning and danger. According to the forewarning results, corresponding measures are taken. The model was used to forecast and forewarn the K9 working face. The results obtained by LS-SVM regression show that the forecast- ing have a high precision and forewarning results based on a LS-SVM multi-classifier are credible. Therefore, it is an effective model building method for continuous prediction of methane concentration and hazard forewarning in working face.展开更多
In the experimental study, AGE-782 thermal instrument was used to detect the infrared radiation variation of coal and sandstone (wave-length range 3.6～5.5 μm was used). It's discovered that coal and sandstone fa...In the experimental study, AGE-782 thermal instrument was used to detect the infrared radiation variation of coal and sandstone (wave-length range 3.6～5.5 μm was used). It's discovered that coal and sandstone failure under load have three kinds of infrared thermal features as well as infrared forewarning messages. That are: (1) temperature rises gradually but drops before failure ; (2) temperature rises gradually but quickly rises before failure; (3) first rises,then drops and lower temperature emerges before failure. The further researches and the prospect of micro-wave remote sensing detection .on ground pressure is also discussed.展开更多
To realize real-time monitoring and short-term forecasting and forewarning of coalmine ventilation systems(CVS), in this paper, we first established a joint surface and underground CVS safety management system consist...To realize real-time monitoring and short-term forecasting and forewarning of coalmine ventilation systems(CVS), in this paper, we first established a joint surface and underground CVS safety management system consisting of main ventilation fan, safety-partition linked passageways, and air-required locations. We then applied chaos theory to identify the air quantity and gas concentration of underground partition boundaries, and adopted a fixed data quantity, multi-step progressive, weighted first-order local-domain method to setup a chaos prediction model and a CVS safety forecasting and forewarning system formed by the normal change level, orange forewarning level, and red alarm level. We next conduct the on-field application of the system in a coalmine in Jining, Shandong, China. The results showed that (1) in the statistical scale of 5 min, the changes in both air quantity and gas concentration along CVS partition airflow boundaries were characteristic of chaos and could be used for short-term chaos prediction, and the latter was more chaotic than the former;(2) the setup chaos prediction model had a higher prediction precision and the established safety prediction system could not only predict the variation in CVS stability but also reflect the rationality of underground mining intensity. Thus, this CVS safety forecasting and forewarning system is of better application value.展开更多
文摘Based on the discussion of characteristic and mechanism of the stock prices volatility in Chinese emerging stock markets, this research designs an index system for risk forewarn, and builds up an investment decision model based on the forewarn of the market risk signal. Then, on probing into the structure and function of the realization of the model, the paper presents the method of data interface.
文摘Three forecasting models are set up: the auto\|regressive moving average model, the grey forecasting model for the rate of qualified products P t, and the grey forecasting model for time intervals of the quality catastrophes. Then a combined forewarning system for the quality of products is established, which contains three models, judgment rules and forewarning state illustration. Finally with an example of the practical production, this modeling system is proved fairly effective.
基金Project 50674111 supported by the National Natural Science Foundation of China
文摘To improve the precision and reliability in predicting methane hazard in working face of coal mine, we have proposed a forecasting and forewarning model for methane hazard based on the least square support vector (LS-SVM) multi-classifier and regression machine. For the forecasting model, the methane concentration can be considered as a nonlinear time series and the time series analysis method is adopted to predict the change in methane concentration using LS-SVM regression. For the forewarning model, which is based on the forecasting results, by the multi-classification method of LS-SVM, the methane hazard was identified to four grades: normal, attention, warning and danger. According to the forewarning results, corresponding measures are taken. The model was used to forecast and forewarn the K9 working face. The results obtained by LS-SVM regression show that the forecast- ing have a high precision and forewarning results based on a LS-SVM multi-classifier are credible. Therefore, it is an effective model building method for continuous prediction of methane concentration and hazard forewarning in working face.
文摘In the experimental study, AGE-782 thermal instrument was used to detect the infrared radiation variation of coal and sandstone (wave-length range 3.6～5.5 μm was used). It's discovered that coal and sandstone failure under load have three kinds of infrared thermal features as well as infrared forewarning messages. That are: (1) temperature rises gradually but drops before failure ; (2) temperature rises gradually but quickly rises before failure; (3) first rises,then drops and lower temperature emerges before failure. The further researches and the prospect of micro-wave remote sensing detection .on ground pressure is also discussed.
基金supported by the National Natural Science Foundation of China(Nos.51304128 and 51674158)the Natural Science Foundation of Shandong Province(No.ZR2013EEQ015)
文摘To realize real-time monitoring and short-term forecasting and forewarning of coalmine ventilation systems(CVS), in this paper, we first established a joint surface and underground CVS safety management system consisting of main ventilation fan, safety-partition linked passageways, and air-required locations. We then applied chaos theory to identify the air quantity and gas concentration of underground partition boundaries, and adopted a fixed data quantity, multi-step progressive, weighted first-order local-domain method to setup a chaos prediction model and a CVS safety forecasting and forewarning system formed by the normal change level, orange forewarning level, and red alarm level. We next conduct the on-field application of the system in a coalmine in Jining, Shandong, China. The results showed that (1) in the statistical scale of 5 min, the changes in both air quantity and gas concentration along CVS partition airflow boundaries were characteristic of chaos and could be used for short-term chaos prediction, and the latter was more chaotic than the former;(2) the setup chaos prediction model had a higher prediction precision and the established safety prediction system could not only predict the variation in CVS stability but also reflect the rationality of underground mining intensity. Thus, this CVS safety forecasting and forewarning system is of better application value.
