准确地预测多年冻土区地表冻结天数对于当前地表环境有重大意义。当前地表冻结地区融化时间推后,融化结束时间提前,总体冻结时长增加。对于传统置信规则库来说,只考虑了其精准性的问题,而对于地表冻结时长天数,其可解释性具有重大意义,...准确地预测多年冻土区地表冻结天数对于当前地表环境有重大意义。当前地表冻结地区融化时间推后,融化结束时间提前,总体冻结时长增加。对于传统置信规则库来说,只考虑了其精准性的问题,而对于地表冻结时长天数,其可解释性具有重大意义,需要考虑水汽、气体以及在融化过程之中的能量交换过程。因此本文使用因子分析法,对于影响地表冻结天数的因素提取因子,然后使用可解释性置信规则库,对地表冻结天数进行可解释性预测,使用中国东北地区的数据进行案例研究,结果表明可解释性置信规则库可以对多年冻土区地表冻结天数进行有效预测,验证了模型的有效性。Accurate prediction of the number of days of surface freezing in perennial permafrost regions is of great significance for the current surface environment. Currently, the thawing time is pushed back in the surface freezing region, the thawing end time is advanced, and the overall freezing duration increases. For the traditional belief rule base, only its accuracy is considered, but for the surface freezing duration days, its interpretability is of great significance, and it needs to consider the water vapor, gas, and the energy exchange process during the melting process. Therefore, this paper uses the factor analysis method to extract the factors for the number of days of surface freezing, and then uses the interpretable confidence rule base to predict the number of days of surface freezing with interpretability, and uses the data from Northeast China to conduct a case study, and the results show that the interpretable belief rule base can effectively predict the number of days of surface freezing in the perennial permafrost region, which verifies the effectiveness of the model.展开更多
文摘准确地预测多年冻土区地表冻结天数对于当前地表环境有重大意义。当前地表冻结地区融化时间推后,融化结束时间提前,总体冻结时长增加。对于传统置信规则库来说,只考虑了其精准性的问题,而对于地表冻结时长天数,其可解释性具有重大意义,需要考虑水汽、气体以及在融化过程之中的能量交换过程。因此本文使用因子分析法,对于影响地表冻结天数的因素提取因子,然后使用可解释性置信规则库,对地表冻结天数进行可解释性预测,使用中国东北地区的数据进行案例研究,结果表明可解释性置信规则库可以对多年冻土区地表冻结天数进行有效预测,验证了模型的有效性。Accurate prediction of the number of days of surface freezing in perennial permafrost regions is of great significance for the current surface environment. Currently, the thawing time is pushed back in the surface freezing region, the thawing end time is advanced, and the overall freezing duration increases. For the traditional belief rule base, only its accuracy is considered, but for the surface freezing duration days, its interpretability is of great significance, and it needs to consider the water vapor, gas, and the energy exchange process during the melting process. Therefore, this paper uses the factor analysis method to extract the factors for the number of days of surface freezing, and then uses the interpretable confidence rule base to predict the number of days of surface freezing with interpretability, and uses the data from Northeast China to conduct a case study, and the results show that the interpretable belief rule base can effectively predict the number of days of surface freezing in the perennial permafrost region, which verifies the effectiveness of the model.
