In order to deeply analyze the differences in the acceptance of autonomous driving technology among different gender groups,a multiple indicators and multiple causes model was constructed by integrating a technology a...In order to deeply analyze the differences in the acceptance of autonomous driving technology among different gender groups,a multiple indicators and multiple causes model was constructed by integrating a technology acceptance model and theory of planned behavior to comprehensively reveal the gender differences in the influence mechanisms of subjective and objective factors.The analysis is based on data collected from Chinese urban residents.Among objective factors,age has a significant negative impact on women's perceived behavior control and a significant positive impact on perceived ease of use.Education has a significant positive impact on men's perceived behavior control,and has a strong positive impact on women's perceived usefulness(PU).For men,income and education are found to have strong positive impacts on perceived behavior control.Among subjective factors,perceived ease of use(PEU)has the greatest influence on women's behavior intention,and it is the only influential factor for women's intention to use autonomous driving technology,with an influence coefficient of 0.72.The influencing path of men's intention to use autonomous driving technology is more complex.It is not only directly affected by the significant and positive joint effects of attitude and PU,but also indirectly affected by perceived behavior controls,subjective norms,and PEU.展开更多
Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation.This work introduces a geostatistical technique that ha...Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation.This work introduces a geostatistical technique that has been developed and tested in an iron ore deposit at Bafq mining district,in central Iran,and that,based on a probability criterion,helps to objectively model the geometry of this iron ore deposit.The main problem in reserve estimation of this ore body is its geometrical modeling and uncertainty in geological boundaries.This work deals with the geostatistical method of multiple indicator kriging,which is used to determine the real boundaries of ore body in different categories.This approach has potential to improve project performance and decrease operational risk.For this purpose,the ore body is separated into two categories including rich iron zone(w(Fe)>45%)and poor iron zone(20%<w(Fe)<45%).It significantly benefits to decrease the risk of reserve evaluation in the deposit.This case study also highlights the value of multiple indicator kriging as a tool for estimates the position of grade boundaries within the deposit.Comparison of the resultant probability maps with the real ore/waste contacts on the extracted levels shows that the first indicator model could separate the whole ore body(poor plus rich)from the waste zone by probability of more than 0.35,which concludes the total reserve of 53 million tons.The second indicator model applied to separate the rich and poor domains and the results show that the blocks with the estimated probability of equal to or more than 0.4 lay within the rich ore zone consisting of 15.8 million tons reserve.展开更多
A comprehensive evaluation method of electric power prediction models using multiple accuracy indicators is proposed.To obtain the preferred models,this paper selects a number of accuracy indicators that can reflect t...A comprehensive evaluation method of electric power prediction models using multiple accuracy indicators is proposed.To obtain the preferred models,this paper selects a number of accuracy indicators that can reflect the accuracy of single-point prediction and the correlation of predicted data,and carries out a comprehensive evaluation.First,according to Dempster-Shafer(D-S)evidence theory,a new accuracy indicator based on the relative error(RE)is proposed to solve the problem that RE is inconsistent with other indicators in the quantity of evaluation values and cannot be adopted at the same time.Next,a new dimensionless method is proposed,which combines the efficiency coefficient method with the extreme value method to unify the accuracy indicator into a dimensionless positive indicator,to avoid the conflict between pieces of evidence caused by the minimum value of zero.On this basis,the evidence fusion is used to obtain the comprehensive evaluation value of each model.Then,the principle and the process of consistency checking of the proposed method using the entropy method and the linear combination formula are described.Finally,the effectiveness and the superiority of the proposed method are validated by an illustrative instance.展开更多
The purpose of this study was to determine a suitable model for investigating the effects of climate factors on the area burned by forest fire in the Tahe forest region, Daxing'an Mountains, in northeast China. The r...The purpose of this study was to determine a suitable model for investigating the effects of climate factors on the area burned by forest fire in the Tahe forest region, Daxing'an Mountains, in northeast China. The response variables were the area burned by lightning- caused fire, human-caused fire, and total burned area. The predictor variables were nine climate variables collected from the local weather station. Three regression models were utilized, including multiple linear regression, log- linear model (log-transformation on both response and predictor variables), and gamma-generalized linear model. The goodness-of-fit of the models were compared based on model fitting statistics such as R2, AIC, and RMSE. The results revealed that the gamma-generalized linear model was generally superior to both multiple linear regressionmodel and log-linear model for fitting the fire data. Further, the best models were selected based on the criteria that the climate variables were statistically significant at at = 0.05. The gamma best models indicated that maximum wind speed, precipitation, and days that rainfall greater than 0.1 mm had significant impacts on the area burned by the lightning-caused fire, while the mean temperature and minimum relative humidity were the .main drivers of the burned area caused by human activities. Overall, the total burned area by forest fire was significantly influenced by days that rainfall greater than 0.1 mm and minimum rela- tive humidity, indicating that the moisture condition of forest stands determine the burned area by forest fire.展开更多
针对煤矿井下无线信道的信号传播模型,提出将接收信号强度复合滤波器、一元线性回归测距模型和多边定位方法相结合的改进接收信号强度指示(Received Signal Strength Indicator,RSSI)值的井下定位技术,通过利用基于无线传感器网络操作系...针对煤矿井下无线信道的信号传播模型,提出将接收信号强度复合滤波器、一元线性回归测距模型和多边定位方法相结合的改进接收信号强度指示(Received Signal Strength Indicator,RSSI)值的井下定位技术,通过利用基于无线传感器网络操作系统TinyOS的节点进行离线建模、在线测算,实现煤矿井下人员及设备的实时定位。井下巷道试验表明,该技术提高了定位精度,增强了定位系统的鲁棒性,适用于煤矿井下定位。展开更多
基金The National Key Research and Development Program of China(No.2018YFB1601304)the National Natural Science Foundation of China(No.71871107)Philosophy and Social Science Foundation Project of Universities in Jiangsu Province(No.2020SJA2059).
文摘In order to deeply analyze the differences in the acceptance of autonomous driving technology among different gender groups,a multiple indicators and multiple causes model was constructed by integrating a technology acceptance model and theory of planned behavior to comprehensively reveal the gender differences in the influence mechanisms of subjective and objective factors.The analysis is based on data collected from Chinese urban residents.Among objective factors,age has a significant negative impact on women's perceived behavior control and a significant positive impact on perceived ease of use.Education has a significant positive impact on men's perceived behavior control,and has a strong positive impact on women's perceived usefulness(PU).For men,income and education are found to have strong positive impacts on perceived behavior control.Among subjective factors,perceived ease of use(PEU)has the greatest influence on women's behavior intention,and it is the only influential factor for women's intention to use autonomous driving technology,with an influence coefficient of 0.72.The influencing path of men's intention to use autonomous driving technology is more complex.It is not only directly affected by the significant and positive joint effects of attitude and PU,but also indirectly affected by perceived behavior controls,subjective norms,and PEU.
基金supported by Iron Ore Research Center of Yazd University
文摘Uncertainty on the geological contacts and the block volumes of the models along boundaries is often a major part of the global uncertainty of reserve estimation.This work introduces a geostatistical technique that has been developed and tested in an iron ore deposit at Bafq mining district,in central Iran,and that,based on a probability criterion,helps to objectively model the geometry of this iron ore deposit.The main problem in reserve estimation of this ore body is its geometrical modeling and uncertainty in geological boundaries.This work deals with the geostatistical method of multiple indicator kriging,which is used to determine the real boundaries of ore body in different categories.This approach has potential to improve project performance and decrease operational risk.For this purpose,the ore body is separated into two categories including rich iron zone(w(Fe)>45%)and poor iron zone(20%<w(Fe)<45%).It significantly benefits to decrease the risk of reserve evaluation in the deposit.This case study also highlights the value of multiple indicator kriging as a tool for estimates the position of grade boundaries within the deposit.Comparison of the resultant probability maps with the real ore/waste contacts on the extracted levels shows that the first indicator model could separate the whole ore body(poor plus rich)from the waste zone by probability of more than 0.35,which concludes the total reserve of 53 million tons.The second indicator model applied to separate the rich and poor domains and the results show that the blocks with the estimated probability of equal to or more than 0.4 lay within the rich ore zone consisting of 15.8 million tons reserve.
基金supported by National Key R&D Program of China(No.2016YFB0901405)Guangdong Provincial Science and Technology Planning Project of China(No.2020A0505100004,No.2018A050506069)Guangdong Provincial Special Fund Project for Marine Economic Development of China(No.GDNRC[2020]020)。
文摘A comprehensive evaluation method of electric power prediction models using multiple accuracy indicators is proposed.To obtain the preferred models,this paper selects a number of accuracy indicators that can reflect the accuracy of single-point prediction and the correlation of predicted data,and carries out a comprehensive evaluation.First,according to Dempster-Shafer(D-S)evidence theory,a new accuracy indicator based on the relative error(RE)is proposed to solve the problem that RE is inconsistent with other indicators in the quantity of evaluation values and cannot be adopted at the same time.Next,a new dimensionless method is proposed,which combines the efficiency coefficient method with the extreme value method to unify the accuracy indicator into a dimensionless positive indicator,to avoid the conflict between pieces of evidence caused by the minimum value of zero.On this basis,the evidence fusion is used to obtain the comprehensive evaluation value of each model.Then,the principle and the process of consistency checking of the proposed method using the entropy method and the linear combination formula are described.Finally,the effectiveness and the superiority of the proposed method are validated by an illustrative instance.
基金funded by Asia-Pacific Forests Net(APFNET/2010/FPF/001)National Natural Science Foundation of China(Grant No.31400552)Forestry industry research special funds for public welfare projects(201404402)
文摘The purpose of this study was to determine a suitable model for investigating the effects of climate factors on the area burned by forest fire in the Tahe forest region, Daxing'an Mountains, in northeast China. The response variables were the area burned by lightning- caused fire, human-caused fire, and total burned area. The predictor variables were nine climate variables collected from the local weather station. Three regression models were utilized, including multiple linear regression, log- linear model (log-transformation on both response and predictor variables), and gamma-generalized linear model. The goodness-of-fit of the models were compared based on model fitting statistics such as R2, AIC, and RMSE. The results revealed that the gamma-generalized linear model was generally superior to both multiple linear regressionmodel and log-linear model for fitting the fire data. Further, the best models were selected based on the criteria that the climate variables were statistically significant at at = 0.05. The gamma best models indicated that maximum wind speed, precipitation, and days that rainfall greater than 0.1 mm had significant impacts on the area burned by the lightning-caused fire, while the mean temperature and minimum relative humidity were the .main drivers of the burned area caused by human activities. Overall, the total burned area by forest fire was significantly influenced by days that rainfall greater than 0.1 mm and minimum rela- tive humidity, indicating that the moisture condition of forest stands determine the burned area by forest fire.
文摘针对煤矿井下无线信道的信号传播模型,提出将接收信号强度复合滤波器、一元线性回归测距模型和多边定位方法相结合的改进接收信号强度指示(Received Signal Strength Indicator,RSSI)值的井下定位技术,通过利用基于无线传感器网络操作系统TinyOS的节点进行离线建模、在线测算,实现煤矿井下人员及设备的实时定位。井下巷道试验表明,该技术提高了定位精度,增强了定位系统的鲁棒性,适用于煤矿井下定位。