An improved energy demand forecasting model is built based on the autoregressive distributed lag (ARDL) bounds testing approach and an adaptive genetic algorithm (AGA) to obtain credible energy demand forecasting results. The ARDL bounds analysis is first employed to select the appropriate input variables of the energy demand model. After the existence of a cointegration relationship in the model is confirmed, the AGA is then employed to optimize the coefficients of both linear and quadratic forms with gross domestic product, economic structure, urbanization, and technological progress as the input variables. On the basis of historical annual data from 1985 to 2015, the simulation results indicate that the proposed model has greater accuracy and reliability than conventional optimization methods. The predicted results of the proposed model also demonstrate that China will demand approximately 4.9, 5.6, and 6.1 billion standard tons of coal equivalent in 2020, 2025, and 2030, respectively. 相似文献
With the development of the city, the number of establishments that are proposed or under construction is increasing year by year, and if they are industries that handle flammable, explosive, toxic, harmful, and dangerous substances, the public safety will face great threats, which will bring great challenges to emergency rescue work. Therefore, providing reasonable solutions to the problem of location selection of emergency supplies repositories are necessary for improving the emergency response efficiency in chemical industrial parks. A mathematical model for location selection of emergency supplies repositories in emergency logistics management are presented considering more actual factors. The optimization objectives of the model are to minimize total transport length and cost. And then a Variable Weighted Algorithm is designed to solve the model, where an auxiliary function was constructed with different methods of building weighting factors based on the theory and method of solving multi-objective optimization problems in operational research. Simulation results show the effectiveness and feasibility of the models and algorithms presented in this paper. 相似文献
The gas detector layout should be highly attuned to combustible gas leakage and attain a good reliability in avoiding detector malfunction, which is an important guarantee for the normal production of the chemical industry and other related enterprises. Herein, a gas detector layout optimization method based on double coverage and reliability is proposed. The key gas leakage monitoring area is determined through layout scene field investigation. To improve the detection probability and detection system reliability, the dual coverage target and voting mechanism are set, and the gas detector layout is determined with the ray-casting algorithm according to the coverage target. Combined with FLACS software to simulate a variety of typical leakage conditions under different layout scenarios, the relationship between the leaked gas concentration detected by gas detectors in each layout scheme and time is obtained, and the gas leakage detection probability in each layout scheme, number of detectors that can trigger the alarm, shortest time to trigger the alarm and reliability are comprehensively evaluated. The decision-maker selects the final gas detector layout plan according to the evaluation results and actual site needs. The study shows that the detection probability of each layout scheme set according to the double coverage is high, and multiple detectors can trigger the alarm (up to 100%), which ensures that the alarm can be triggered within 10 s under all applicable conditions. According to the evaluation results, the decision-maker can obtain a layout scheme that not only agrees with the actual site conditions but also attains a high detection probability, short detection time and strong reliability. 相似文献
Objective: This study examined the risk factors of driving under the influence of alcohol (DUI) among drivers of specific vehicle categories (DSC). On the basis of this research, the variables related to DUI and involvement in traffic crashes were defined. The analysis was conducted for car drivers, bicyclists, motorcyclists, bus drivers, and truck drivers.
Method: The research sample included drivers involved in traffic crashes on the territory of Serbia in 2016 (60,666). Two types of analyses were conducted in this study. Logistic regression established the correlation between DUI and DSC and the The Technique for Order of Preference by Similarity to Ideal Solution (Multi-criteria decision making) method was applied to consider the scoring and explore the potential for the prevalence of DUI on the basis of 2 data sets (DUI and non DUI).
Results: The study results showed that driver error and male drivers were the 2 most significant risk factors for DUI, with the highest scores and potential for prevalence. The nonuse of restraint systems, driver experience, and driver age are the factors with a significant prediction of involvement in an accident and an insignificant prediction of DUI.
Conclusions: Following the development of the logistic prediction models for DUI drivers, testing of the model was conducted for 3 control driver groups: Car, motorcycle, and bicycle. The prediction model with a probability greater than 50% showed that 77% of car drivers were under the influence of alcohol. Similarly, the prediction percentage for motorcyclists and bicyclists amounted to 71 and 67%, respectively. The recommendation of the study is that drivers whose DUI probability is above 50% should be potentially suspected of DUI. The results of this study can help to understand the problem of DUI among specific driver categories and detect DUI drivers, with the aim of creating successful traffic safety policy. 相似文献
Based on the observation by a Regional Air Quality Monitoring Network including 16 monitoring stations, temporal and spatial variations of ozone(O3), NO2and total oxidant(Ox) were analyzed by both linear regression and cluster analysis. A fast increase of regional O3concentrations of 0.86 ppbV/yr was found for the annual averaged values from 2006 to 2011 in Guangdong, China. Such fast O3increase is accompanied by a correspondingly fast NOx reduction as indicated by a fast NO2 reduction rate of 0.61 ppbV/yr. Based on a cluster analysis, the monitoring stations were classified into two major categories – rural stations(non-urban) and suburban/urban stations. The O3concentrations at rural stations were relatively conserved while those at suburban/urban stations showed a fast increase rate of 2.0 ppbV/yr accompanied by a NO2 reduction rate of 1.2 ppbV/yr. Moreover, a rapid increase of the averaged O3 concentrations in springtime(13%/yr referred to 2006 level) was observed, which may result from the increase of solar duration, reduction of precipitation in Guangdong and transport from Eastern Central China. Application of smog production algorithm showed that the photochemical O3production is mainly volatile organic compounds(VOC)-controlled. However, the photochemical O3production is sensitive to both NOx and VOC for O3pollution episode. Accordingly, it is expected that a combined NOx and VOC reduction will be helpful for the reduction of the O3 pollution episodes in Pearl River Delta while stringent VOC emission control is in general required for the regional O3 pollution control. 相似文献