The regularities of the dynamics of the average annual temperature of Berlin from 1701 to 2021 are revealed.A total of 65 wavelets were received.The temperature has a high quantum certainty,and the change in the...The regularities of the dynamics of the average annual temperature of Berlin from 1701 to 2021 are revealed.A total of 65 wavelets were received.The temperature has a high quantum certainty,and the change in the average annual temperature of Berlin was identified by a model that contains only two components for prediction.The basis of the forecast at 320 years makes it possible to look into the future until the year 2340.The forecast confirms the conclusions made in the CMIP5 report on global warming.With an increase in the number of components in the model up to five,the forecast is possible only until 2060.Therefore,the model with only two components is workable.The trend is characterized by a modified Mandelbrot equation showing exponential growth with a high growth rate of 1.47421.The wave equation also has an amplitude in the form of the Mandelbrot law(in mathematics,the Laplace law,in biology,the Zipf-Pearl law,in econometrics,the Pareto law),when the exponential growth activity is equal to 1.For 1701,the period of oscillation was 2×60.33333≈120.7 years.By 2021,the period decreased and became equal to 87.6 years.The trend is such that by 2340 the period of oscillation will decrease to 30.2 years.Such an increase in fluctuations indicates an imbalance in climate disturbances in temperature in Berlin.For Berlin,the last three years are characterized by sharp decreases in the average annual temperature from 11.8℃ to 10.5℃,i.e.by 12.4% in 2021.Therefore,the forecast is still unstable,as a further decrease in the average annual temperature of Berlin in the near future may change the picture of the forecast.展开更多
In regression, despite being both aimed at estimating the Mean Squared Prediction Error (MSPE), Akaike’s Final Prediction Error (FPE) and the Generalized Cross Validation (GCV) selection criteria are usually derived ...In regression, despite being both aimed at estimating the Mean Squared Prediction Error (MSPE), Akaike’s Final Prediction Error (FPE) and the Generalized Cross Validation (GCV) selection criteria are usually derived from two quite different perspectives. Here, settling on the most commonly accepted definition of the MSPE as the expectation of the squared prediction error loss, we provide theoretical expressions for it, valid for any linear model (LM) fitter, be it under random or non random designs. Specializing these MSPE expressions for each of them, we are able to derive closed formulas of the MSPE for some of the most popular LM fitters: Ordinary Least Squares (OLS), with or without a full column rank design matrix;Ordinary and Generalized Ridge regression, the latter embedding smoothing splines fitting. For each of these LM fitters, we then deduce a computable estimate of the MSPE which turns out to coincide with Akaike’s FPE. Using a slight variation, we similarly get a class of MSPE estimates coinciding with the classical GCV formula for those same LM fitters.展开更多
In this article, using generalized weighted mean and difference matrix of order m, we introduce the paranormed sequence space l（u, v, p; △（m））, which consist of the sequences whose generalized weighted △（m）-di...In this article, using generalized weighted mean and difference matrix of order m, we introduce the paranormed sequence space l（u, v, p; △（m））, which consist of the sequences whose generalized weighted △（m）-difference means are in the linear space l（p） defined by I.J.Maddox. Also, we determine the basis of this space and compute its α-, β- and γ-duals. Further, we give the characterization of the classes of matrix mappings from l（u, v, p, △（m）） to l∞, c, and co. Finally, we apply the Hausdorff measure of noncompacness to characterize some classes of compact operators given by matrices on the space lp（U, v, △（m）） （1 ≤ p 〈 ∞）.展开更多
Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also ...Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.展开更多
In October2003,China signed to join in”The Treaty on Friendship and Cooperation in Southeast Asia”,thus joining the efforts in constructing the Sino-ASEANsecurity regime.With the Treaty in its core part,this securit...In October2003,China signed to join in”The Treaty on Friendship and Cooperation in Southeast Asia”,thus joining the efforts in constructing the Sino-ASEANsecurity regime.With the Treaty in its core part,this security regime seeks to solve the security problems through political means,thereby providing a problem-solving framework for their bilateral security problems.展开更多
文摘The regularities of the dynamics of the average annual temperature of Berlin from 1701 to 2021 are revealed.A total of 65 wavelets were received.The temperature has a high quantum certainty,and the change in the average annual temperature of Berlin was identified by a model that contains only two components for prediction.The basis of the forecast at 320 years makes it possible to look into the future until the year 2340.The forecast confirms the conclusions made in the CMIP5 report on global warming.With an increase in the number of components in the model up to five,the forecast is possible only until 2060.Therefore,the model with only two components is workable.The trend is characterized by a modified Mandelbrot equation showing exponential growth with a high growth rate of 1.47421.The wave equation also has an amplitude in the form of the Mandelbrot law(in mathematics,the Laplace law,in biology,the Zipf-Pearl law,in econometrics,the Pareto law),when the exponential growth activity is equal to 1.For 1701,the period of oscillation was 2×60.33333≈120.7 years.By 2021,the period decreased and became equal to 87.6 years.The trend is such that by 2340 the period of oscillation will decrease to 30.2 years.Such an increase in fluctuations indicates an imbalance in climate disturbances in temperature in Berlin.For Berlin,the last three years are characterized by sharp decreases in the average annual temperature from 11.8℃ to 10.5℃,i.e.by 12.4% in 2021.Therefore,the forecast is still unstable,as a further decrease in the average annual temperature of Berlin in the near future may change the picture of the forecast.
文摘In regression, despite being both aimed at estimating the Mean Squared Prediction Error (MSPE), Akaike’s Final Prediction Error (FPE) and the Generalized Cross Validation (GCV) selection criteria are usually derived from two quite different perspectives. Here, settling on the most commonly accepted definition of the MSPE as the expectation of the squared prediction error loss, we provide theoretical expressions for it, valid for any linear model (LM) fitter, be it under random or non random designs. Specializing these MSPE expressions for each of them, we are able to derive closed formulas of the MSPE for some of the most popular LM fitters: Ordinary Least Squares (OLS), with or without a full column rank design matrix;Ordinary and Generalized Ridge regression, the latter embedding smoothing splines fitting. For each of these LM fitters, we then deduce a computable estimate of the MSPE which turns out to coincide with Akaike’s FPE. Using a slight variation, we similarly get a class of MSPE estimates coinciding with the classical GCV formula for those same LM fitters.
文摘In this article, using generalized weighted mean and difference matrix of order m, we introduce the paranormed sequence space l（u, v, p; △（m））, which consist of the sequences whose generalized weighted △（m）-difference means are in the linear space l（p） defined by I.J.Maddox. Also, we determine the basis of this space and compute its α-, β- and γ-duals. Further, we give the characterization of the classes of matrix mappings from l（u, v, p, △（m）） to l∞, c, and co. Finally, we apply the Hausdorff measure of noncompacness to characterize some classes of compact operators given by matrices on the space lp（U, v, △（m）） （1 ≤ p 〈 ∞）.
基金financially supported by the National Natural Science Foundation of China(41771535)the National Social Science Foundation Major Project(20&ZD092)。
文摘Within the context of CO_(2)emission peaking and carbon neutrality,the study of CO_(2)emissions at the provincial level is few.Sichuan Province in China has not only superior clean energy resources endowment but also great potential for the reduction of CO_(2)emissions.Therefore,using logarithmic mean Divisia index(LMDI)model to analysis the influence degree of different influencing factors on CO_(2)emissions from final energy consumption in Sichuan Province,so as to formulate corresponding emission reduction countermeasures from different paths according to the influencing factors.Based on the data of final energy consumption in Sichuan Province from 2010 to 2019,we calculated CO_(2)emission by the indirect emission calculation method.The influencing factors of CO_(2)emissions originating from final energy consumption in Sichuan Province were decomposed into population size,economic development,industrial structure,energy consumption intensity,and energy consumption structure by the Kaya-logarithmic mean Divisia index(LMDI)decomposition model.At the same time,grey correlation analysis was used to identify the correlation between CO_(2)emissions originating from final energy consumption and the influencing factors in Sichuan Province.The results showed that population size,economic development and energy consumption structure have positive contributions to CO_(2)emissions from final energy consumption in Sichuan Province,and economic development has a significant contribution to CO_(2)emissions from final energy consumption,with a contribution rate of 519.11%.The industrial structure and energy consumption intensity have negative contributions to CO_(2)emissions in Sichuan Province,and both of them have significant contributions,among which the contribution rate of energy consumption structure was 325.96%.From the perspective of industrial structure,secondary industry makes significant contributions and will maintain a restraining effect;from the perspective of energy consumption structure,industry sector has a significant contribution.The results of this paper are conducive to the implementation of carbon emission reduction policies in Sichuan Province.
文摘In October2003,China signed to join in”The Treaty on Friendship and Cooperation in Southeast Asia”,thus joining the efforts in constructing the Sino-ASEANsecurity regime.With the Treaty in its core part,this security regime seeks to solve the security problems through political means,thereby providing a problem-solving framework for their bilateral security problems.
