Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squ...Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squares support vector machine(LS-SVM) algorithm is an improved algorithm of SVM.But the common LS-SVM algorithm,used directly in safety predictions,has some problems.We have first studied gas prediction problems and the basic theory of LS-SVM.Given these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on LS-SVM.Finally,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance.The simulation results have verified the validity of the new algorithm.展开更多
The effects of the mat preprocessing method on total volatile organic compounds （TVOC） emission of car mat are studied in this paper. An appropriate TVOC emission period for car mat is suggested. The emission factor...The effects of the mat preprocessing method on total volatile organic compounds （TVOC） emission of car mat are studied in this paper. An appropriate TVOC emission period for car mat is suggested. The emission factors for to- tal volatile organic compounds from three kinds of new car mats are discussed. The car mats are preprocessed by washing, baking and ventilation. When car mats are preprocessed by washing, the TVOC emission for all samples tested are lower than that preprocessed in other methods. The TVOC emission is in stable situation for a mini- mum of 4 days. The TVOC emitted from some samples may exceed 25001ag/kg. But the TVOC emitted from washed Polyamide （PA） and wool mat is less than 25001ag/kg. The emission factors of total volatile organic com- pounds （TVOC） are experimentally investigated in the case of different preprocessing methods. The air tempera- ture in environment chamber and the water temperature for washing are important factors influencing on emission of car mats.展开更多
文摘Traditional coal mine safety prediction methods are off-line and do not have dynamic prediction functions.The Support Vector Machine(SVM) is a new machine learning algorithm that has excellent properties.The least squares support vector machine(LS-SVM) algorithm is an improved algorithm of SVM.But the common LS-SVM algorithm,used directly in safety predictions,has some problems.We have first studied gas prediction problems and the basic theory of LS-SVM.Given these problems,we have investigated the affect of the time factor about safety prediction and present an on-line prediction algorithm,based on LS-SVM.Finally,given our observed data,we used the on-line algorithm to predict gas emissions and used other related algorithm to compare its performance.The simulation results have verified the validity of the new algorithm.
基金supported by National Key Technology R&D Program(No.2012BAB12B02)
文摘The effects of the mat preprocessing method on total volatile organic compounds （TVOC） emission of car mat are studied in this paper. An appropriate TVOC emission period for car mat is suggested. The emission factors for to- tal volatile organic compounds from three kinds of new car mats are discussed. The car mats are preprocessed by washing, baking and ventilation. When car mats are preprocessed by washing, the TVOC emission for all samples tested are lower than that preprocessed in other methods. The TVOC emission is in stable situation for a mini- mum of 4 days. The TVOC emitted from some samples may exceed 25001ag/kg. But the TVOC emitted from washed Polyamide （PA） and wool mat is less than 25001ag/kg. The emission factors of total volatile organic com- pounds （TVOC） are experimentally investigated in the case of different preprocessing methods. The air tempera- ture in environment chamber and the water temperature for washing are important factors influencing on emission of car mats.
