基于LMDI(Logarithmic Mean Divisia Index Method)方法分析2001-2016年京津冀地区电力部门CO2排放的8个影响因素,考虑了京津冀地区电力部门从生产投入、转换、传输到消费的整个过程;并分析了2001-2016年影响京、津、冀各地区CO2排放的...基于LMDI(Logarithmic Mean Divisia Index Method)方法分析2001-2016年京津冀地区电力部门CO2排放的8个影响因素,考虑了京津冀地区电力部门从生产投入、转换、传输到消费的整个过程;并分析了2001-2016年影响京、津、冀各地区CO2排放的各因素贡献值。结果表明,1)2001-2016年京津冀地区电力部门CO2排放总体呈现递增趋势,2012年出现负增长;河北省电力部门对京津冀电力部门CO2排放贡献最大,2001-2016年累计CO2排放变化量为145.70 Mt,但河北省电力部门的减排潜力巨大;2)人均GDP效应和人口规模效应是促进京津冀地区电力部门CO2排放增长的主要因素,2001-2016年累计贡献值分别为261.86 Mt和36.47 Mt;3)用电效率效应和电力输入输出效应是京津冀地区电力部门CO2排放量增长的主要抑制作用,2001-2016年累计贡献值分别为-49.40 Mt和-47.93 Mt;4)造成京、津、冀电力部门CO2排放差异的主要因素是人均GDP、化石能源转换效率和用电效率。展开更多
Optimal policies in Markov decision problems may be quite sensitive with regard to transition probabilities.In practice,some transition probabilities may be uncertain.The goals of the present study are to find the rob...Optimal policies in Markov decision problems may be quite sensitive with regard to transition probabilities.In practice,some transition probabilities may be uncertain.The goals of the present study are to find the robust range for a certain optimal policy and to obtain value intervals of exact transition probabilities.Our research yields powerful contributions for Markov decision processes(MDPs)with uncertain transition probabilities.We first propose a method for estimating unknown transition probabilities based on maximum likelihood.Since the estimation may be far from accurate,and the highest expected total reward of the MDP may be sensitive to these transition probabilities,we analyze the robustness of an optimal policy and propose an approach for robust analysis.After giving the definition of a robust optimal policy with uncertain transition probabilities represented as sets of numbers,we formulate a model to obtain the optimal policy.Finally,we define the value intervals of the exact transition probabilities and construct models to determine the lower and upper bounds.Numerical examples are given to show the practicability of our methods.展开更多
文摘基于LMDI(Logarithmic Mean Divisia Index Method)方法分析2001-2016年京津冀地区电力部门CO2排放的8个影响因素,考虑了京津冀地区电力部门从生产投入、转换、传输到消费的整个过程;并分析了2001-2016年影响京、津、冀各地区CO2排放的各因素贡献值。结果表明,1)2001-2016年京津冀地区电力部门CO2排放总体呈现递增趋势,2012年出现负增长;河北省电力部门对京津冀电力部门CO2排放贡献最大,2001-2016年累计CO2排放变化量为145.70 Mt,但河北省电力部门的减排潜力巨大;2)人均GDP效应和人口规模效应是促进京津冀地区电力部门CO2排放增长的主要因素,2001-2016年累计贡献值分别为261.86 Mt和36.47 Mt;3)用电效率效应和电力输入输出效应是京津冀地区电力部门CO2排放量增长的主要抑制作用,2001-2016年累计贡献值分别为-49.40 Mt和-47.93 Mt;4)造成京、津、冀电力部门CO2排放差异的主要因素是人均GDP、化石能源转换效率和用电效率。
基金Supported by the National Natural Science Foundation of China(71571019).
文摘Optimal policies in Markov decision problems may be quite sensitive with regard to transition probabilities.In practice,some transition probabilities may be uncertain.The goals of the present study are to find the robust range for a certain optimal policy and to obtain value intervals of exact transition probabilities.Our research yields powerful contributions for Markov decision processes(MDPs)with uncertain transition probabilities.We first propose a method for estimating unknown transition probabilities based on maximum likelihood.Since the estimation may be far from accurate,and the highest expected total reward of the MDP may be sensitive to these transition probabilities,we analyze the robustness of an optimal policy and propose an approach for robust analysis.After giving the definition of a robust optimal policy with uncertain transition probabilities represented as sets of numbers,we formulate a model to obtain the optimal policy.Finally,we define the value intervals of the exact transition probabilities and construct models to determine the lower and upper bounds.Numerical examples are given to show the practicability of our methods.
