Intelligent Forecasting on Composite Regeneration Endpoint of DPF in the Vehicle
A mathematical model based on fuzzy least squares support vector machines has been developed to forecast the composite regeneration endpoint of the diesel particulate filter in Vehicle. The results show that the relative error of forecasting model of composite regeneration endpoint is less than 3.5%, and the oxygen concentration of exhaust gas has the biggest effect on the endpoint of composite regeneration, followed by the mass flow rate of exhaust gas, the microwave power, the temperature of exhaust gas and the amount of cerium-based additive.
Identification on rock and soil parameters for vibration drilling rock in metal mine based on fuzzy least square support vector machine
A single freedom degree model of drilling bit-rock was established according to the vibration mechanism and its dynamic characteristics. Moreover, a novel identification method of rock and soil parameters for vibration drilling based on the fuzzy least squares (FLS)-support vector machine (SVM) was developed, in which the fuzzy membership function was set by using linear distance, and its parameters, such as penalty factor and kernel parameter, were optimized by using adaptive genetic algorithm. And FLS-SVM identification on rock and soil parameters for vibration drilling was made by changing the input/output data from single freedom degree model of drilling bit-rock. The results of identification simulation and resonance column experiment show that relative error of natural frequency for some hard sand from identification simulation and resonance column experiment is 1.1% and the identification precision based on the fuzzy least squares-support vector machine is high.
Climatology of the cusp-related thermospheric mass density anomaly, as derived from CHAMP observations
We report on the thermospheric mass density anomaly in the vicinity of the ionospheric cusp. A systematic survey of the anomalies is presented, based on a statistical analysis of 4 years of data (2002–2005) obtained by the accelerometer onboard CHAMP. The anomalies are detected during all years and seasons in both hemispheres but with stronger signatures in the Northern Hemisphere. For the same geophysical conditions, solar flux and geomagnetic activity the anomalies in the north are larger by a factor of about 1.35. Over the course of the survey period the amplitude decreases by more than a factor of 5 while the level of solar flux reduces by a factor of 2. The anomaly strength also depends on the solar wind input. The merging electric field, E merg , is generally enhanced for about an hour before the anomaly detection. There is a quadratic response of the anomaly amplitude to E merg . For geophysical conditions of P10.7 E merg E merg , where the weight of E merg , in mV/m, is by about 50 times higher than that of the solar flux level. The solar zenith angle and the influence of particle precipitation are found to play a minor role as a controlling parameter of seasonal variation. The well-known annual variation of the thermospheric density with a minimum around June also influences the formation of the cusp anomalies. This leads to a clear hemispheric asymmetry with very weak anomalies in the south during June solstice, which is supposed to be a combined effect of the minimum in annual variation and the seasonal decrease of solar insolation in this region.