Oil and gas exploration and production is the most important and key segment in the whole business chain of the petroleum industry.Therefore,oil companies always put much emphasis on making scientific and reasonable d...Oil and gas exploration and production is the most important and key segment in the whole business chain of the petroleum industry.Therefore,oil companies always put much emphasis on making scientific and reasonable decisions about investment scale and structure in the upstream sector,so that they can minimise business risks and obtain high returns.According to the system dynamics theories and methods and based on the actual results from an oil company＇s practice in China,a system dynamics model is built in this paper for analyzing and forecasting the upstream investment scale and structure for an oil company.This model was used to analyze the investment effect of a large oil company in China, and the results showed that the total upstream investment scale will decline slowly in a short period and the investment proportion of different parts should be adjusted if some influencing factors are taken into account.This application practice was compared with the actual data and indicated that the system dynamics（SD） model presented in this paper is a useful tool for analyzing and forecasting of upstream investment scale and structure of oil companies in their investment decisions.展开更多
How to obtain fast-growth errors, which is comparable to the actual forecast growth error, is a crucial problem in ensemble forecast （EF）. The method, Breeding of Growth Modes （BGM）, which has been used to generat...How to obtain fast-growth errors, which is comparable to the actual forecast growth error, is a crucial problem in ensemble forecast （EF）. The method, Breeding of Growth Modes （BGM）, which has been used to generate perturbations for medium-range EF at NCEP, simulates the development of fast-growth errors in the analysis cycle, and is a reasonable choice in capturing growing errors modes, especially for extreme weather by BGM. An ideal supercell storm, simulated by Weather Research Forecast model （WRF）, occurred in central Oklahoma on 20 May 1977. This simulation was used to study the application of BGM methods in the meso-scale strong convective Ensemble Prediction System （EPS）. We compared the forecasting skills of EPS by different pertubation methods, like Monte-Carlo and BGM. The results show that the ensemble average forecast based on Monte-Carlo with statistics meaning is superior to the single-deterministic prediction, but a less dynamic process of the method leads to a smaller spread than expected. The fast-growth errors of BGM are comparable to the actual short-range forecast error and a more appropriate ensemble spread. Considering evaluation indexes and scores, the forecast skills of EPS by BGM is higher than Monte-Carlo＇s. Furthermore, various breeding cycles have different effects on precipitation and non-precipitation fields, confirmation of reasonable cycles need consider balance between variables.展开更多
With the rapid development of China's modern cities,the scale of urban construction land has experienced dramatic changes.The forecast of urban construction land is the important content of urban construction deve...With the rapid development of China's modern cities,the scale of urban construction land has experienced dramatic changes.The forecast of urban construction land is the important content of urban construction development,and guarantee for healthy,rapid and intensive development of cities,therefore,we must reasonably determine the scale of urban construction land.Based on the status quo of construction land in Chongqing Municipality during the period 2000-2009,this article selects GM(1,1) model,linear model and non-linear model,to forecast the scale of construction land and each type of land subordinate to it in Chongqing Municipality during the period 2010-2014,respectively.The results show that the construction land in Chongqing Municipality will increase substantially during the period 2010-2014,and the area of each type of land subordinate to construction land will also increase to varying degrees,therefore the land contradictions will become more prominent.展开更多
This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolut...This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.展开更多
With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to eva...With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.展开更多
Debris flow forecast is an important means of disaster mitigation. However, the accuracy of the statistics-based debris flow forecast is unsatisfied while the mechanism-based forecast is unavailable at the watershed s...Debris flow forecast is an important means of disaster mitigation. However, the accuracy of the statistics-based debris flow forecast is unsatisfied while the mechanism-based forecast is unavailable at the watershed scale because most of existing researches on the initiation mechanism of debris flow took a single slope as the main object. In order to solve this problem, this paper developed a model of debris flow forecast based on the water-soil coupling mechanism at the watershed scale. In this model, the runoff and the instable soil caused by the rainfall in a watershed is estimated by the distrib- uted hydrological model （GBHM） and an instable identification model of the unsaturated soil. Because the debris flow is a special fluid composed of soil and water and has a bigger density, the density esti- mated by the runoff and instable soil mass in a watershed under the action of a rainfall is employed as a key factor to identify the formation probability of debris flow in the forecast model. The Jiangjia Gulley, a typical debris flow valley with a several debris flow events each year, is selected as a case study watershed to test this forecast model of debris flow. According the observation data of Dongchuan Debris Flow Observation and Research Station, CAS located in Jiangjia Gulley, there were 4 debris flow events in 2006. The test results show that the accuracy of the model is satisfied.展开更多
The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A roll...The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.展开更多
目的分析Alberta卒中项目早期CT评分(Alberta stroke program early CT score,ASPECTS)、洛桑急性脑卒中登记分析(Acute Stroke Registry and Analysis of Lausanne,ASTRAL)及血管事件总体健康风险(Totaled Health risks in Vascular Ev...目的分析Alberta卒中项目早期CT评分(Alberta stroke program early CT score,ASPECTS)、洛桑急性脑卒中登记分析(Acute Stroke Registry and Analysis of Lausanne,ASTRAL)及血管事件总体健康风险(Totaled Health risks in Vascular Events,THRIVE)评分对老年急性脑梗死患者静脉溶栓治疗预后的预测价值。方法前瞻性选取2021年1月至2024年9月胜利油田中心医院急诊科收治的行静脉溶栓的老年急性脑梗死患者118例。所有患者接受静脉溶栓,治疗3个月后根据改良的Rankin量表评分分为预后良好组73例,预后不良组45例。比较两组ASPECTS、ASTRAL评分及THRIVE评分,ROC曲线评估三种模型对3个月预后的预测能力,并计算曲线下面积(area under curve,AUC)。结果预后不良组ASTRAL、THRIVE评分明显高于预后良好组,ASPECTS明显低于预后良好组,差异有统计学意义(P<0.01)。ROC曲线分析显示,ASPECTS、ASTRAL评分及THRIVE评分评估预后的AUC分别为0.731、0.935、0.799(P<0.01),且拟合度优异。结论三种模型均可以有效预测老年急性脑梗死患者静脉溶栓3个月预后。展开更多
文摘Oil and gas exploration and production is the most important and key segment in the whole business chain of the petroleum industry.Therefore,oil companies always put much emphasis on making scientific and reasonable decisions about investment scale and structure in the upstream sector,so that they can minimise business risks and obtain high returns.According to the system dynamics theories and methods and based on the actual results from an oil company＇s practice in China,a system dynamics model is built in this paper for analyzing and forecasting the upstream investment scale and structure for an oil company.This model was used to analyze the investment effect of a large oil company in China, and the results showed that the total upstream investment scale will decline slowly in a short period and the investment proportion of different parts should be adjusted if some influencing factors are taken into account.This application practice was compared with the actual data and indicated that the system dynamics（SD） model presented in this paper is a useful tool for analyzing and forecasting of upstream investment scale and structure of oil companies in their investment decisions.
基金supported jointly by the Nature Science Foundation of China (Project No:40875068)Public-Welfare Meteorological Research Foundation (ProjectNo:GYHY200806029)
文摘How to obtain fast-growth errors, which is comparable to the actual forecast growth error, is a crucial problem in ensemble forecast （EF）. The method, Breeding of Growth Modes （BGM）, which has been used to generate perturbations for medium-range EF at NCEP, simulates the development of fast-growth errors in the analysis cycle, and is a reasonable choice in capturing growing errors modes, especially for extreme weather by BGM. An ideal supercell storm, simulated by Weather Research Forecast model （WRF）, occurred in central Oklahoma on 20 May 1977. This simulation was used to study the application of BGM methods in the meso-scale strong convective Ensemble Prediction System （EPS）. We compared the forecasting skills of EPS by different pertubation methods, like Monte-Carlo and BGM. The results show that the ensemble average forecast based on Monte-Carlo with statistics meaning is superior to the single-deterministic prediction, but a less dynamic process of the method leads to a smaller spread than expected. The fast-growth errors of BGM are comparable to the actual short-range forecast error and a more appropriate ensemble spread. Considering evaluation indexes and scores, the forecast skills of EPS by BGM is higher than Monte-Carlo＇s. Furthermore, various breeding cycles have different effects on precipitation and non-precipitation fields, confirmation of reasonable cycles need consider balance between variables.
文摘With the rapid development of China's modern cities,the scale of urban construction land has experienced dramatic changes.The forecast of urban construction land is the important content of urban construction development,and guarantee for healthy,rapid and intensive development of cities,therefore,we must reasonably determine the scale of urban construction land.Based on the status quo of construction land in Chongqing Municipality during the period 2000-2009,this article selects GM(1,1) model,linear model and non-linear model,to forecast the scale of construction land and each type of land subordinate to it in Chongqing Municipality during the period 2010-2014,respectively.The results show that the construction land in Chongqing Municipality will increase substantially during the period 2010-2014,and the area of each type of land subordinate to construction land will also increase to varying degrees,therefore the land contradictions will become more prominent.
基金supported by the National Natural Science Foundation of China(Grant No.70871082)the Shanghai Leading Academic Discipline Project,China(Grant No.S30504)
文摘This paper studies and predicts the number growth of China＇s mobile users by using the power-law regression. We find that the number growth of the mobile users follows a power law. Motivated by the data on the evolution of the mobile users, we consider scenarios of self-organization of accelerating growth networks into scale-free structures and propose a directed network model, in which the nodes grow following a power-law acceleration. The expressions for the transient and the stationary average degree distributions are obtained by using the Poisson process. This result shows that the model generates appropriate power-law connectivity distributions. Therefore, we find a power-law acceleration invariance of the scale-free networks. The numerical simulations of the models agree with the analytical results well.
基金supported in part by the National Key R&D Program of China (No.2017YFE0109000)the project of China Datang Corporation Ltd
文摘With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy.
基金supported by the foundation of the Research Fund for Commonweal Trades (Meteorology) (No. GYHY201006039)
文摘Debris flow forecast is an important means of disaster mitigation. However, the accuracy of the statistics-based debris flow forecast is unsatisfied while the mechanism-based forecast is unavailable at the watershed scale because most of existing researches on the initiation mechanism of debris flow took a single slope as the main object. In order to solve this problem, this paper developed a model of debris flow forecast based on the water-soil coupling mechanism at the watershed scale. In this model, the runoff and the instable soil caused by the rainfall in a watershed is estimated by the distrib- uted hydrological model （GBHM） and an instable identification model of the unsaturated soil. Because the debris flow is a special fluid composed of soil and water and has a bigger density, the density esti- mated by the runoff and instable soil mass in a watershed under the action of a rainfall is employed as a key factor to identify the formation probability of debris flow in the forecast model. The Jiangjia Gulley, a typical debris flow valley with a several debris flow events each year, is selected as a case study watershed to test this forecast model of debris flow. According the observation data of Dongchuan Debris Flow Observation and Research Station, CAS located in Jiangjia Gulley, there were 4 debris flow events in 2006. The test results show that the accuracy of the model is satisfied.
文摘The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.
文摘目的分析Alberta卒中项目早期CT评分(Alberta stroke program early CT score,ASPECTS)、洛桑急性脑卒中登记分析(Acute Stroke Registry and Analysis of Lausanne,ASTRAL)及血管事件总体健康风险(Totaled Health risks in Vascular Events,THRIVE)评分对老年急性脑梗死患者静脉溶栓治疗预后的预测价值。方法前瞻性选取2021年1月至2024年9月胜利油田中心医院急诊科收治的行静脉溶栓的老年急性脑梗死患者118例。所有患者接受静脉溶栓,治疗3个月后根据改良的Rankin量表评分分为预后良好组73例,预后不良组45例。比较两组ASPECTS、ASTRAL评分及THRIVE评分,ROC曲线评估三种模型对3个月预后的预测能力,并计算曲线下面积(area under curve,AUC)。结果预后不良组ASTRAL、THRIVE评分明显高于预后良好组,ASPECTS明显低于预后良好组,差异有统计学意义(P<0.01)。ROC曲线分析显示,ASPECTS、ASTRAL评分及THRIVE评分评估预后的AUC分别为0.731、0.935、0.799(P<0.01),且拟合度优异。结论三种模型均可以有效预测老年急性脑梗死患者静脉溶栓3个月预后。
