The back propagation (BP)-based artificial neural nets (ANN) can identify complicated relationships among dissolved gas contents in transformer oil and corresponding fault types, using the highly nonlinear mapping nat...The back propagation (BP)-based artificial neural nets (ANN) can identify complicated relationships among dissolved gas contents in transformer oil and corresponding fault types, using the highly nonlinear mapping nature of the neural nets. An efficient BP-ALM (BP with Adaptive Learning Rate and Momentum coefficient) algorithm is proposed to reduce the training time and avoid being trapped into local minima, where the learning rate and the momentum coefficient are altered at iterations. We developed a system of transformer fault diagnosis based on Dissolved Gases Analysis (DGA) with a BP-ALM algorithm. Training patterns were selected from the results of a Refined Three-Ratio method (RTR). Test results show that the system has a better ability of quick learning and global convergence than other methods and a superior performance in fault diagnosis compared to convectional BP-based neural networks and RTR.展开更多
It is essential to predict the scour depth around bridge piers for hydraulic engineers involved in the economical design of bridge pier foundation. Conventional investigations have long been of the opinion that empiri...It is essential to predict the scour depth around bridge piers for hydraulic engineers involved in the economical design of bridge pier foundation. Conventional investigations have long been of the opinion that empirical scour prediction equations based on laboratory data over predict scour depths. In this article, the Back-Propagation Neural Network （BPN） was applied to predict the scour depth in order to overcome the problem of exclusive and the nonlinear relationships. The observations obtained from thirteen states in USA was verified by the present model. From the comparison with conventional experimental methods, it can be found that the scour depth around bridge piers can be efficiently predicted using the BPN.展开更多
Objective： To explore the impact of meteorological factors on the outbreak of bacillary dysentery, so as to provide suggestions for disease prevention. Methods： Based on the Chinese medicine theory of Yunqi, the des...Objective： To explore the impact of meteorological factors on the outbreak of bacillary dysentery, so as to provide suggestions for disease prevention. Methods： Based on the Chinese medicine theory of Yunqi, the descriptive statistics, single-factor correlation analysis and back-propagation artificial neural net-work were conducted using data on five basic meteorological factors and data on incidence of bacillary dysentery in Beijing, China, for the period 1970-2004. Results： The incidence of bacillary dysentery showed significant positive correlation relationship with the precipitation, relative humidity, vapor pressure, and temperature, respectively. The incidence of bacillary dysentery showed a negatively correlated relationship with the wind speed and the change trend of average wind speed. The results of medical-meteorological forecast model showed a relatively high accuracy rate. Conclusions： There is a close relationship between the meteorological factors and the incidence of bacillary dysentery, but the contributions of which to the onset of bacillary dysentery are different to each other.展开更多
An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) mod...An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.展开更多
ABSTRACT Objective： To analyze the correlations between the incidence of tuberculosis and meteorological factors over the same period and previous periods including 1, 2 and 3 years ago, defined according to the Chin...ABSTRACT Objective： To analyze the correlations between the incidence of tuberculosis and meteorological factors over the same period and previous periods including 1, 2 and 3 years ago, defined according to the Chinese medicine theory of five circuits （Wu Yun） and six qi, to establish medical-meteorological forecast models for the Beijing area of China. Methods： Data regarding the incidence of tuberculosis between 1990 and 2004 were obtained from the Beijing Center for Disease Control and Prevention, and the data regarding the meteorological factors （including daily average temperatures, wind speeds, precipitations, relative humidities, vapor pressures and low cloud covers） between 1987 and 2004 were collected from the Beijing Meteorological Observatory and analyzed. Descriptive statistics and a back-propagation artificial neural network were adopted to analyze the data. Results： There were significant correlations between the incidence of tuberculosis and the meteorological factors in the corresponding year and previous years. Among these correlations, wind speed was the factor with the strongest influence on tuberculosis （the standardized significance was 100%）. Additionally, all prediction models would successfully established, suggesting the use of a collection of meteorological factors spanning from three years ago to the present is superior to the use of single data. Conclusions： The incidence of tuberculosis in Beijing area is correlated to meteorological factors in the current year and previous years, which verifies the practicality of the theory of five circuits and six qi.展开更多
文摘The back propagation (BP)-based artificial neural nets (ANN) can identify complicated relationships among dissolved gas contents in transformer oil and corresponding fault types, using the highly nonlinear mapping nature of the neural nets. An efficient BP-ALM (BP with Adaptive Learning Rate and Momentum coefficient) algorithm is proposed to reduce the training time and avoid being trapped into local minima, where the learning rate and the momentum coefficient are altered at iterations. We developed a system of transformer fault diagnosis based on Dissolved Gases Analysis (DGA) with a BP-ALM algorithm. Training patterns were selected from the results of a Refined Three-Ratio method (RTR). Test results show that the system has a better ability of quick learning and global convergence than other methods and a superior performance in fault diagnosis compared to convectional BP-based neural networks and RTR.
文摘It is essential to predict the scour depth around bridge piers for hydraulic engineers involved in the economical design of bridge pier foundation. Conventional investigations have long been of the opinion that empirical scour prediction equations based on laboratory data over predict scour depths. In this article, the Back-Propagation Neural Network （BPN） was applied to predict the scour depth in order to overcome the problem of exclusive and the nonlinear relationships. The observations obtained from thirteen states in USA was verified by the present model. From the comparison with conventional experimental methods, it can be found that the scour depth around bridge piers can be efficiently predicted using the BPN.
基金Supported by the National Natural Science Foundation of China(No.81072896)Beijing University of Chinese Medicine(No. 2009JYZZ-JS001)
文摘Objective： To explore the impact of meteorological factors on the outbreak of bacillary dysentery, so as to provide suggestions for disease prevention. Methods： Based on the Chinese medicine theory of Yunqi, the descriptive statistics, single-factor correlation analysis and back-propagation artificial neural net-work were conducted using data on five basic meteorological factors and data on incidence of bacillary dysentery in Beijing, China, for the period 1970-2004. Results： The incidence of bacillary dysentery showed significant positive correlation relationship with the precipitation, relative humidity, vapor pressure, and temperature, respectively. The incidence of bacillary dysentery showed a negatively correlated relationship with the wind speed and the change trend of average wind speed. The results of medical-meteorological forecast model showed a relatively high accuracy rate. Conclusions： There is a close relationship between the meteorological factors and the incidence of bacillary dysentery, but the contributions of which to the onset of bacillary dysentery are different to each other.
基金Funded by the Natural Science Foundation of China (No. 59778021)
文摘An effective approach for describing complicated water quality processes is very important for river water quality management. We built two artificial neural network(ANN) models,a feed-forward back-propagation(BP) model and a radial basis function(RBF) model,to simulate the water quality of the Yangtze and Jialing Rivers in reaches crossing the city of Chongqing,P. R. China. Our models used the historical monitoring data of biological oxygen demand,dissolved oxygen,ammonia,oil and volatile phenolic compounds. Comparison with the one-dimensional traditional water quality model suggest that both BP and RBF models are superior; their higher accuracy and better goodness-of-fit indicate that the ANN calculation of water quality agrees better with measurement. It is demonstrated that ANN modeling can be a tool for estimating the water quality of the Yangtze River. Of the two ANN models,the RBF model calculates with a smaller mean error,but a larger root mean square error. More effort to identify out the causes of these differences would help optimize the structures of neural network water-quality models.
基金Supported by the National Natural Science Foundation of China(No.81072896)
文摘ABSTRACT Objective： To analyze the correlations between the incidence of tuberculosis and meteorological factors over the same period and previous periods including 1, 2 and 3 years ago, defined according to the Chinese medicine theory of five circuits （Wu Yun） and six qi, to establish medical-meteorological forecast models for the Beijing area of China. Methods： Data regarding the incidence of tuberculosis between 1990 and 2004 were obtained from the Beijing Center for Disease Control and Prevention, and the data regarding the meteorological factors （including daily average temperatures, wind speeds, precipitations, relative humidities, vapor pressures and low cloud covers） between 1987 and 2004 were collected from the Beijing Meteorological Observatory and analyzed. Descriptive statistics and a back-propagation artificial neural network were adopted to analyze the data. Results： There were significant correlations between the incidence of tuberculosis and the meteorological factors in the corresponding year and previous years. Among these correlations, wind speed was the factor with the strongest influence on tuberculosis （the standardized significance was 100%）. Additionally, all prediction models would successfully established, suggesting the use of a collection of meteorological factors spanning from three years ago to the present is superior to the use of single data. Conclusions： The incidence of tuberculosis in Beijing area is correlated to meteorological factors in the current year and previous years, which verifies the practicality of the theory of five circuits and six qi.
