The coal of Anyuan Mine has the characteristic of easy spontaneous combustion. Conventional method is difficult to predict it. Coal samples from this mine were tested in laboratory. The data obtained from laboratory d...The coal of Anyuan Mine has the characteristic of easy spontaneous combustion. Conventional method is difficult to predict it. Coal samples from this mine were tested in laboratory. The data obtained from laboratory determination were initialized for the value which was defined as "K". The ratio of each index gas and value of "K", and the ratio of combination index gases and value of "K", were analyzed simultaneously. The research results show that for this coal mine, if there is carbon monoxide in the gas sample, the phenomenon of oxidation and temperature rising for coal exists in this mine; if there is C_2H_4 in the gas sample, the temperature of coal perhaps exceeds 130 °C. If the coal temperature is between 35 °C and 130 °C, prediction and forecast for coal spontaneous combustion depend on the value of Φ(CO)/K mainly; if the temperature of coal is between 130 °C and 300 °C, prediction and forecast for coal spontaneous combustion depend on the value of Φ(C_2H_6)/Φ(C_2H_2) and Φ(C_2H_6)/K. The research results provide experimental basis for the prediction of coal spontaneous combustion in Anyuan coal mine, and have better guidance on safe production of this coal mine.展开更多
The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of ...The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.展开更多
Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual charac...Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.展开更多
According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are comput...According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.展开更多
Structure damage identification and alarming of long-span bridge were conducted with three-dimensional dynamic displacement data collected by GPS subsystem of health monitoring system on Runyang Suspension Bridge.Firs...Structure damage identification and alarming of long-span bridge were conducted with three-dimensional dynamic displacement data collected by GPS subsystem of health monitoring system on Runyang Suspension Bridge.First,the effects of temperature on the main girder spatial position coordinates were analyzed from the transverse,longitudinal and vertical directions of bridge,and the correlation regression models were built between temperature and the position coordinates of main girder in the longitudinal and vertical directions;then the alarming indices of coordinate residuals were conducted,and the mean-value control chart was applied to making statistical pattern identification for abnormal changes of girder dynamic coordinates;and finally,the structural damage alarming method of main girder was established.Analysis results show that temperature has remarkable correlation with position coordinates in the longitudinal and vertical directions of bridge,and has weak correlation with the transverse coordinates.The 3%abnormal change of the longitudinal coordinates and 5%abnormal change of the vertical ones caused by structural damage are respectively identified by the mean-value control chart method based on GPS dynamic monitoring data and hence the structural abnormalities state identification and damage alarming for main girder of long-span suspension bridge can be realized in multiple directions.展开更多
The drawn copper wires have been analyzed by differential scanning calorimeter(DSC) and a new method, which uses DSC measurements to determine the Johnson-Mehl-Avrami-Kolmogorov(JMAK) exponent via introducing Arrheniu...The drawn copper wires have been analyzed by differential scanning calorimeter(DSC) and a new method, which uses DSC measurements to determine the Johnson-Mehl-Avrami-Kolmogorov(JMAK) exponent via introducing Arrhenius behavior and modifying the baseline of DSC curves, has been proposed. The results show that JMAK exponent and recrystallization activation energy of the drawn copper wires with a strain of 2.77 are about 2.39 and 125 k J/mol, respectively. The line linking the tangency points of DSC curve hypotenuse can be used as the baseline when calculating recrystallization fraction. The JMAK exponent obtained by the DSC method is in a good agreement with that obtained by microhardness measurements. Compared to traditional methods to measure the exponent, the proposed method is faster and less labor intensive.展开更多
基金Projects(51274099,51474106)supported by the National Natural Science Foundation of China
文摘The coal of Anyuan Mine has the characteristic of easy spontaneous combustion. Conventional method is difficult to predict it. Coal samples from this mine were tested in laboratory. The data obtained from laboratory determination were initialized for the value which was defined as "K". The ratio of each index gas and value of "K", and the ratio of combination index gases and value of "K", were analyzed simultaneously. The research results show that for this coal mine, if there is carbon monoxide in the gas sample, the phenomenon of oxidation and temperature rising for coal exists in this mine; if there is C_2H_4 in the gas sample, the temperature of coal perhaps exceeds 130 °C. If the coal temperature is between 35 °C and 130 °C, prediction and forecast for coal spontaneous combustion depend on the value of Φ(CO)/K mainly; if the temperature of coal is between 130 °C and 300 °C, prediction and forecast for coal spontaneous combustion depend on the value of Φ(C_2H_6)/Φ(C_2H_2) and Φ(C_2H_6)/K. The research results provide experimental basis for the prediction of coal spontaneous combustion in Anyuan coal mine, and have better guidance on safe production of this coal mine.
基金Project(2012CB725402)supported by the National Key Basic Research Program of ChinaProjects(51338003,50908051)supported by the National Natural Science Foundation of China
文摘The techniques to forecast available parking space(APS) are indispensable components for parking guidance systems(PGS). According to the data collected in Newcastle upon Tyne, England, the changing characteristics of APS were studied. Thereafter, aiming to build up a multi-step APS forecasting model that provides richer information than a conventional one-step model, the largest Lyapunov exponents(largest LEs) method was introduced into PGS. By experimental tests conducted using the same dataset, its prediction performance was compared with traditional wavelet neural network(WNN) method in both one-step and multi-step processes. Based on the results, a new multi-step forecasting model called WNN-LE method was proposed, where WNN, which enjoys a more accurate performance along with a better learning ability in short-term forecasting, was applied in the early forecast steps while the Lyapunov exponent prediction method in the latter steps precisely reflect the chaotic feature in latter forecast period. The MSE of APS forecasting for one hour time period can be reduced from 83.1 to 27.1(in a parking building with 492 berths) by using largest LEs method instead of WNN and further reduced to 19.0 by conducted the new method.
基金Project(50934006) supported by the National Natural Science Foundation of ChinaProject(2010CB732004) supported by the National Basic Research Program of China+1 种基金Project(2009ssxt230) supported by the Central South University Innovation Fund,ChinaProject(CX2011B119) supported by the Graduated Students’Research and Innovation Fund of Hunan Province,China
文摘Due to the complex features of rock mass blastability assessment systems, an evaluation model of rock mass blastability was established on the basis of the unascertained measurement （UM） theory and the actual characteristics of the project. Considering a comprehensive range of intact rock properties and discontinuous structures of rock mass, twelve main factors influencing the evaluation blastability of rock mass were taken into account in the UM model, and the blastability evaluation index system of rock mass was constructed. The unascertained evaluation indices corresponding to the selected factors for the actual situation were solved both qualitatively and quantitatively. Then, the UM function of each evaluation index was obtained based on the initial data for the analysis of the blastability of six rock mass at a highway improvement cutting site in North Wales. The index weights of the factors were calculated by entropy theory, and credible degree identification （CDI） criteria were established according to the UM theory. The results of rock mass blastability evaluation were obtained by the CDI criteria. The results show that the UM model assessment results agree well with the actual records, and are consistent with those of the fuzzy sets evaluation method. Meanwhile, the unascertained superiority degree of rock mass blastability of samples S1-$6 which can be calculated by scoring criteria are 3.428 5, 3.453 3, 4.058 7, 3.675 9, 3.516 7 and 3.289 7, respectively. Furthermore, the proposed method can take into account large amount of uncertain information in blastability evaluation, which can provide an effective, credible and feasible way for estimating the blastability of rock mass. Engineering practices show that it can complete the blastability assessment systematically and scientifically without any assumption by the proposed model, which can be applied to practical engineering.
基金Project(70671039) supported by the National Natural Science Foundation of China
文摘According to the chaotic and non-linear characters of power load data,the time series matrix is established with the theory of phase-space reconstruction,and then Lyapunov exponents with chaotic time series are computed to determine the time delay and the embedding dimension.Due to different features of the data,data mining algorithm is conducted to classify the data into different groups.Redundant information is eliminated by the advantage of data mining technology,and the historical loads that have highly similar features with the forecasting day are searched by the system.As a result,the training data can be decreased and the computing speed can also be improved when constructing support vector machine(SVM) model.Then,SVM algorithm is used to predict power load with parameters that get in pretreatment.In order to prove the effectiveness of the new model,the calculation with data mining SVM algorithm is compared with that of single SVM and back propagation network.It can be seen that the new DSVM algorithm effectively improves the forecast accuracy by 0.75%,1.10% and 1.73% compared with SVM for two random dimensions of 11-dimension,14-dimension and BP network,respectively.This indicates that the DSVM gains perfect improvement effect in the short-term power load forecasting.
基金Project(51078080)supported by the National Natural Science Foundation of ChinaProject(20130969010)supported by Aeronautical Science Foundation of China+1 种基金Project(2011Y03-6)supported by Traffic Transportation Technology Project of Jiangsu Province,ChinaProject(BK2012562)supported by the Natural Science Foundation of Jiangsu Province,China
文摘Structure damage identification and alarming of long-span bridge were conducted with three-dimensional dynamic displacement data collected by GPS subsystem of health monitoring system on Runyang Suspension Bridge.First,the effects of temperature on the main girder spatial position coordinates were analyzed from the transverse,longitudinal and vertical directions of bridge,and the correlation regression models were built between temperature and the position coordinates of main girder in the longitudinal and vertical directions;then the alarming indices of coordinate residuals were conducted,and the mean-value control chart was applied to making statistical pattern identification for abnormal changes of girder dynamic coordinates;and finally,the structural damage alarming method of main girder was established.Analysis results show that temperature has remarkable correlation with position coordinates in the longitudinal and vertical directions of bridge,and has weak correlation with the transverse coordinates.The 3%abnormal change of the longitudinal coordinates and 5%abnormal change of the vertical ones caused by structural damage are respectively identified by the mean-value control chart method based on GPS dynamic monitoring data and hence the structural abnormalities state identification and damage alarming for main girder of long-span suspension bridge can be realized in multiple directions.
基金Projects(51171135,51371132,51471123) supported by the National Natural Science Foundation of ChinaProjects(2012K07-08,2013KJXX-61) supported by Key Science and Technology Program of Shaanxi Province,ChinaProject(2013JC14) supported by the Education Department Foundation of Shaanxi Province,China
文摘The drawn copper wires have been analyzed by differential scanning calorimeter(DSC) and a new method, which uses DSC measurements to determine the Johnson-Mehl-Avrami-Kolmogorov(JMAK) exponent via introducing Arrhenius behavior and modifying the baseline of DSC curves, has been proposed. The results show that JMAK exponent and recrystallization activation energy of the drawn copper wires with a strain of 2.77 are about 2.39 and 125 k J/mol, respectively. The line linking the tangency points of DSC curve hypotenuse can be used as the baseline when calculating recrystallization fraction. The JMAK exponent obtained by the DSC method is in a good agreement with that obtained by microhardness measurements. Compared to traditional methods to measure the exponent, the proposed method is faster and less labor intensive.
