This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this p...This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this paper to get 5 minutes traffic volume variation as input data for the Gaussian interval type-2 fuzzy sets which can reflect the distribution of historical traffic volume in one statistical period. Moreover, the cluster with the largest collection of data obtained by K-means clustering method is calculated to get the key parameters of type-2 fuzzy sets, mean and standard deviation of the Gaussian membership function.Using the range of data as the input of Gaussian interval type-2 fuzzy sets leads to the range of traffic volume forecasting output with the ability of describing the possible range of the traffic volume as well as the traffic volume prediction data with high accuracy. The simulation results show that the average relative error is reduced to 8% based on the combined K-means Gaussian interval type-2 fuzzy sets forecasting method. The fluctuation range in terms of an upper and a lower forecasting traffic volume completely envelopes the actual traffic volume and reproduces the fluctuation range of traffic flow.展开更多
There are well coherences between annual averaged air temperatures at every meteorological station along the Qinghai-Xizang railway, and its 10-year moving average correlation coefficient is 0.92. Thus, the regional a...There are well coherences between annual averaged air temperatures at every meteorological station along the Qinghai-Xizang railway, and its 10-year moving average correlation coefficient is 0.92. Thus, the regional averaged annual mean temperature series along the Qinghai-Xizang railway (Trw) from 1935 to 2000 are constructed. The investigation is suggested that: Trw had significant responses to the 5-year lagged sunspot cycle length (SCL) and 15-year lagged concentration of atmospheric carbon dioxide (CO2), and the correlation coefficients between them are -0.76 (SCL) and 0.88 (CO2), respectively. The future SCL is predicted by the model of average generated function constructed with its main cycles of 76a, 93a, 108a, 205a and 275a. The result shows that the SCL would be becoming longer in the first half of the 21st century, and then it could be becoming shorter in the second half of the 21st century. Based on the natural change of SCL and the effect of double CO2 concentration, Trw in the 21st century is forecasted. It could warm up about 0.50℃ in the first half of the 21st century compared with the last decade of last century. The mean maximum air temperature could be likely about 0.20℃ in July and from 0.40℃ to 1.10℃ in January. The annual air temperature difference would likely reduce 0.3-1.00℃. The probability of above predictions ranges from 0.64 to 0.73.展开更多
基金supported by the National Key Research and Development Program of China(2018YFB1201500)
文摘This paper uses Gaussian interval type-2 fuzzy se theory on historical traffic volume data processing to obtain a 24-hour prediction of traffic volume with high precision. A K-means clustering method is used in this paper to get 5 minutes traffic volume variation as input data for the Gaussian interval type-2 fuzzy sets which can reflect the distribution of historical traffic volume in one statistical period. Moreover, the cluster with the largest collection of data obtained by K-means clustering method is calculated to get the key parameters of type-2 fuzzy sets, mean and standard deviation of the Gaussian membership function.Using the range of data as the input of Gaussian interval type-2 fuzzy sets leads to the range of traffic volume forecasting output with the ability of describing the possible range of the traffic volume as well as the traffic volume prediction data with high accuracy. The simulation results show that the average relative error is reduced to 8% based on the combined K-means Gaussian interval type-2 fuzzy sets forecasting method. The fluctuation range in terms of an upper and a lower forecasting traffic volume completely envelopes the actual traffic volume and reproduces the fluctuation range of traffic flow.
文摘There are well coherences between annual averaged air temperatures at every meteorological station along the Qinghai-Xizang railway, and its 10-year moving average correlation coefficient is 0.92. Thus, the regional averaged annual mean temperature series along the Qinghai-Xizang railway (Trw) from 1935 to 2000 are constructed. The investigation is suggested that: Trw had significant responses to the 5-year lagged sunspot cycle length (SCL) and 15-year lagged concentration of atmospheric carbon dioxide (CO2), and the correlation coefficients between them are -0.76 (SCL) and 0.88 (CO2), respectively. The future SCL is predicted by the model of average generated function constructed with its main cycles of 76a, 93a, 108a, 205a and 275a. The result shows that the SCL would be becoming longer in the first half of the 21st century, and then it could be becoming shorter in the second half of the 21st century. Based on the natural change of SCL and the effect of double CO2 concentration, Trw in the 21st century is forecasted. It could warm up about 0.50℃ in the first half of the 21st century compared with the last decade of last century. The mean maximum air temperature could be likely about 0.20℃ in July and from 0.40℃ to 1.10℃ in January. The annual air temperature difference would likely reduce 0.3-1.00℃. The probability of above predictions ranges from 0.64 to 0.73.
