In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the...In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.展开更多
Aiming at reducing the deficiency of the traditional fire pre-warning algorithms and the intelligent fire pre-warning algorithms such as artificial neural network,and then to improve the accuracy of fire prewarning fo...Aiming at reducing the deficiency of the traditional fire pre-warning algorithms and the intelligent fire pre-warning algorithms such as artificial neural network,and then to improve the accuracy of fire prewarning for high-rise buildings,a composite fire pre-warning controller is designed according to the characteristic（ nonlinear,less historical data,many influence factors）,also a high-rise building fire pre-warning model is set up based on the support vector regression（ SV R）. Then the wood fire standard history data is applied to make empirical analysis. The research results can provide a reliable decision support framework for high-rise building fire pre-warning.展开更多
A West Kentucky mine operation in No. 11 seam encountered floor heave, due to the localized increase in the thickness of the fireclay mine floor. Floor heave has overridden seals installed in two mined out panels. The...A West Kentucky mine operation in No. 11 seam encountered floor heave, due to the localized increase in the thickness of the fireclay mine floor. Floor heave has overridden seals installed in two mined out panels. The third seal's location was planned for isolating that area from the Mains. A plan of support has been developed to prevent repetition of the floor heave and related problems outby the seals. The applied ground control measures were successful. An attempt of a 3D numerical modeling was made; thus, it would match the observed behavior of the mine floor and could be used as a design tool in similar conditions. The paper describes sequence of events, an applied mitigation ground control system, and the first stage of numerical modeling.展开更多
基金Project supported by the National Natural Science Foundation of China (Grant No 60573065)the Natural Science Foundation of Shandong Province,China (Grant No Y2007G33)the Key Subject Research Foundation of Shandong Province,China(Grant No XTD0708)
文摘In this paper we apply the nonlinear time series analysis method to small-time scale traffic measurement data. The prediction-based method is used to determine the embedding dimension of the traffic data. Based on the reconstructed phase space, the local support vector machine prediction method is used to predict the traffic measurement data, and the BIC-based neighbouring point selection method is used to choose the number of the nearest neighbouring points for the local support vector machine regression model. The experimental results show that the local support vector machine prediction method whose neighbouring points are optimized can effectively predict the small-time scale traffic measurement data and can reproduce the statistical features of real traffic measurements.
基金Supported by the National Natural Science Foundation of China(11072035)
文摘Aiming at reducing the deficiency of the traditional fire pre-warning algorithms and the intelligent fire pre-warning algorithms such as artificial neural network,and then to improve the accuracy of fire prewarning for high-rise buildings,a composite fire pre-warning controller is designed according to the characteristic（ nonlinear,less historical data,many influence factors）,also a high-rise building fire pre-warning model is set up based on the support vector regression（ SV R）. Then the wood fire standard history data is applied to make empirical analysis. The research results can provide a reliable decision support framework for high-rise building fire pre-warning.
文摘A West Kentucky mine operation in No. 11 seam encountered floor heave, due to the localized increase in the thickness of the fireclay mine floor. Floor heave has overridden seals installed in two mined out panels. The third seal's location was planned for isolating that area from the Mains. A plan of support has been developed to prevent repetition of the floor heave and related problems outby the seals. The applied ground control measures were successful. An attempt of a 3D numerical modeling was made; thus, it would match the observed behavior of the mine floor and could be used as a design tool in similar conditions. The paper describes sequence of events, an applied mitigation ground control system, and the first stage of numerical modeling.
