Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim ...Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
弹上电缆,作为导弹设备进行信号、能量传输的重要载体,质量是否符合要求,直接决定了设备的可靠性。与传统电缆不同,弹上电缆,具备多芯、多头、大规模等特点。传统的测试设备往往存在线缆支持规模较小、测试针对性太强、扩展性差、自动...弹上电缆,作为导弹设备进行信号、能量传输的重要载体,质量是否符合要求,直接决定了设备的可靠性。与传统电缆不同,弹上电缆,具备多芯、多头、大规模等特点。传统的测试设备往往存在线缆支持规模较小、测试针对性太强、扩展性差、自动化程度低等缺点,本文提出了基于Test On Demand平台的弹上电缆测技术,阐述了测试原理和测试流程设计,使用该技术完成了对最多达300芯弹上电缆的导通、绝缘、耐压测试,可扩展多种型号电缆,具备通用性、扩展性强、测试速度快、自动化程度高、智能化等特点。展开更多
Aiming at the problem that the consumption data of new ammunition is less and the demand is difficult to predict,combined with the law of ammunition consumption under different damage grades,a Bayesian inference metho...Aiming at the problem that the consumption data of new ammunition is less and the demand is difficult to predict,combined with the law of ammunition consumption under different damage grades,a Bayesian inference method for ammunition demand based on Gompertz distribution is proposed.The Bayesian inference model based on Gompertz distribution is constructed,and the system contribution degree is introduced to determine the weight of the multi-source information.In the case where the prior distribution is known and the distribution of the field data is unknown,the consistency test is performed on the prior information,and the consistency test problem is transformed into the goodness of the fit test problem.Then the Bayesian inference is solved by the Markov chain-Monte Carlo(MCMC)method,and the ammunition demand under different damage grades is gained.The example verifies the accuracy of this method and solves the problem of ammunition demand prediction in the case of insufficient samples.展开更多
An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited i...An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.展开更多
A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there a...A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.展开更多
From the view of information flow, a super-network equilibrium optimization model is proposed to compute the solution of the operation architecture which is made up of a perceptive level, a command level and a firepow...From the view of information flow, a super-network equilibrium optimization model is proposed to compute the solution of the operation architecture which is made up of a perceptive level, a command level and a firepower level. Firstly, the optimized conditions of the perceptive level, command level and firepower level are analyzed respectively based on the demand of information relation,and then the information supply-and-demand equilibrium model of the operation architecture super-network is established. Secondly,a variational inequality transformation(VIT) model for equilibrium optimization of the operation architecture is given. Thirdly, the contraction projection algorithm for solving the operation architecture super-network equilibrium optimization model with fuzzy demands is designed. Finally, numerical examples are given to prove the validity and rationality of the proposed method, and the influence of fuzzy demands on the super-network equilibrium solution of operation architecture is discussed.展开更多
The systematism of weapon combat is the typical characteristic of a modern battlefield.The process of combat is complex and the demand description of weapon system of systems(SOS)is difficult.Granular analyzing is an ...The systematism of weapon combat is the typical characteristic of a modern battlefield.The process of combat is complex and the demand description of weapon system of systems(SOS)is difficult.Granular analyzing is an important method for solving the complex problem in the world.Granular thinking is introduced into the demand description of weapon SoS.Granular computing and granular combination based on a relation of compatibility is proposed.Based on the level of degree and degree of detail,the granular resolution of weapon SoS is defined and an example is illustrated at the end.展开更多
The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered...The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered by most of the heuristics. This acticle focuses on a combined heuristics method for determining order quantity under generalized time-varying demands. The independent policy （IP）, abnormal independent policy （AIP） and dependent policies are studied and compared. Using the concepts of normal/abnormal periods and the properties of dependent policies, a dependent policy-based heuristics （DPH） is proposed for solving the order quantity problems with a kind of time-varying demands pattern under which the first period is normal. By merging the Silver-Meal （S-M） heuristics and the dependent policy-based heuristics （DPH）, a combined heuristics （DPH/S-M） is developed for solving order quantity problems with generalized time-varying demands. The experimentation shows that （1） for the problem with one normal period, no matter which position the normal period stands, the DPH/S-M could not guarantee better than the S-M heuristics, however it is superior to the S-M heuristics in the case that the demands in the abnormal periods are in descending order, and （2） The DPH/S-M is superior to the S-M heuristics for problems with more than one normal period, and the more the number of normal periods, the greater the improvements.展开更多
To achieve CO2 emissions reductions, the UK Building Regulations require developers of new residential buildings to calculate expected CO2 emissions arising from their energy consumption using a methodology such as St...To achieve CO2 emissions reductions, the UK Building Regulations require developers of new residential buildings to calculate expected CO2 emissions arising from their energy consumption using a methodology such as Standard Assessment Procedure （SAP 2005） or, more recently SAP 2009. SAP encompasses all domestic heat consumption and a limited proportion of the electricity consumption. However, these calculations are rarely verified with real energy consumption and related CO2 emissions. This work presents the results of an analysis based on weekly heat demand data for more than 200 individual fiats. The data were collected from a recently built residential development connected to a district heating network. A method for separating out the domestic hot water （DHW） use and space heating （SH） demand has been developed and these values are compared to the demand calculated using SAP 2005 and SAP 2009 methodologies. The analysis also shows the variation in DHW and SH consumption with size of flats and with tenure （privately owned or social housing）. Evaluation of the space heating consumption also includes an estimate of the heating degree day （HDD） base temperature for each block of fiats and compares this to the average base temperature calculated using the SAP 2005 methodology.展开更多
Based on the modern economic theory and the characteristics of China's energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China's energy demand model, and examines ...Based on the modern economic theory and the characteristics of China's energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China's energy demand model, and examines the long-run relationship between China's aggregate energy consumption and the main economic variables such as GDP by using the Johansen multivariate approach. It is found that there exists unique long-run relationship among the variables in the model over the sampling period. An error-correction model provides an appropriate framework for forecasting the short-run fluctuations in the aggregate demand of China.展开更多
In the integrated production-shipment models for the single-vendor-single-buyer system presented hitherto, the demand rate of items is treated as a constant. However, many researchers have observed that the presence o...In the integrated production-shipment models for the single-vendor-single-buyer system presented hitherto, the demand rate of items is treated as a constant. However, many researchers have observed that the presence of more quantities of the same product tends to attract more customers. This suggests that the demand rate should depend on the stock level. This paper presents a single-vendor-single-buyer production-shipment model with the stock dependent demand rate, based on the demand rate linearly depending upon the stock level at any instant of time.展开更多
In this paper, a deterministic lot-sizing model is developed for an item during its lifeperiod. A demand for the item is approximated by a special polynomial function. And shortages areallowed to occur in the proposed...In this paper, a deterministic lot-sizing model is developed for an item during its lifeperiod. A demand for the item is approximated by a special polynomial function. And shortages areallowed to occur in the proposed model. A simple dynamic programming method is presented forgenerating the optimal replenishment policy. A numerical example is used to illustrate the solutionprocedure for the special case with quadric demand. Sensitivity analysis for parameters is alsoincluded.展开更多
The long-term energy demand in China and the-Chinese share in global CO2 emission are forecasted on the basis of scenarios of population growth and economy development up to 2050 proposed in view of the interaction of...The long-term energy demand in China and the-Chinese share in global CO2 emission are forecasted on the basis of scenarios of population growth and economy development up to 2050 proposed in view of the interaction of energy, economy, environment and social development. The total energy demand in 2050 will reach 4.4~ 5.4 billion tce. It is shown in energy supply analysis that coal is China’s major energy in primary energy supply. The share of CO2 emission in the future Chinese energy system will be out of proportion to its energy consumption share because of the high persentage of coal to be consumed. It will reach about 27%. The nuclear option which would replace 30.7% of coal in the total primary energy supply will reduce the share by 9.8%. So the policy considerations on the future Chinese energy system is of great importance to the global CO2 issues.展开更多
As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-deman...As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-demand mismatches.How-ever,existing literatures try to adjust customers’load profiles optimally,instead of electricity overhead,energy consumption patterns of residential appliances,customer satisfaction levels,and energy consumption habits.In this paper,a novel DR method is investigated by mixing the aforementioned factors,where the residential customer cluster is proposed to enhance the performance.Clustering approaches are leveraged to study the electricity consumption habits of various customers by extracting their features and characteristics from historical data.Based on the extracted information,the residential appliances can be scheduled effectively and flexibly.Moreover,we propose and study an efficient optimization framework to obtain the optimal scheduling solution by using clustering and deep learning methods.Extensive simulation experiments are conducted with real-world traces.Numerical results show that the proposed DR method and optimization framework outperform other baseline schemes in terms of the system overhead and peak-to-average ratio(PAR).The impact of various factors on the system utility is further analyzed,which provides useful insights on improving the efficiency of the DR strategy.With the achievement of efficient and intelligent energy management,the proposed method also promotes the realization of China’s carbon peaking and carbon neutrality goals.展开更多
Exchange rate functions under systems of centrallyplanned economy and market economy are quite different,and the mechanism to determine such exchange rate is alsodifferent. To adopt a socialist market economic system ...Exchange rate functions under systems of centrallyplanned economy and market economy are quite different,and the mechanism to determine such exchange rate is alsodifferent. To adopt a socialist market economic system inChina, the exchange rate mechanism of Renminbi must bethoroughly transformed. To accomplish this goal, I believethere are three problems that must be solved: first,展开更多
Agricultural Products Processing and Storage (ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature) is an international,pect-review ed open access journal with the a...Agricultural Products Processing and Storage (ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature) is an international,pect-review ed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additio nally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.展开更多
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘Agricultural Products Processing and Storage(ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature)is an international,peer-reviewed open access journal with the aim to offer a platform for the rapid dissemination of signifi cant,novel,and high-impact research in the fi elds of agricultural product processing science,technology,engineering,and nutrition.Additionally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
文摘弹上电缆,作为导弹设备进行信号、能量传输的重要载体,质量是否符合要求,直接决定了设备的可靠性。与传统电缆不同,弹上电缆,具备多芯、多头、大规模等特点。传统的测试设备往往存在线缆支持规模较小、测试针对性太强、扩展性差、自动化程度低等缺点,本文提出了基于Test On Demand平台的弹上电缆测技术,阐述了测试原理和测试流程设计,使用该技术完成了对最多达300芯弹上电缆的导通、绝缘、耐压测试,可扩展多种型号电缆,具备通用性、扩展性强、测试速度快、自动化程度高、智能化等特点。
基金the Army Scientific Research(KYSZJWJK1744,012016012600B11403).
文摘Aiming at the problem that the consumption data of new ammunition is less and the demand is difficult to predict,combined with the law of ammunition consumption under different damage grades,a Bayesian inference method for ammunition demand based on Gompertz distribution is proposed.The Bayesian inference model based on Gompertz distribution is constructed,and the system contribution degree is introduced to determine the weight of the multi-source information.In the case where the prior distribution is known and the distribution of the field data is unknown,the consistency test is performed on the prior information,and the consistency test problem is transformed into the goodness of the fit test problem.Then the Bayesian inference is solved by the Markov chain-Monte Carlo(MCMC)method,and the ammunition demand under different damage grades is gained.The example verifies the accuracy of this method and solves the problem of ammunition demand prediction in the case of insufficient samples.
基金Project(51606225) supported by the National Natural Science Foundation of ChinaProject(2016JJ2144) supported by Hunan Provincial Natural Science Foundation of ChinaProject(502221703) supported by Graduate Independent Explorative Innovation Foundation of Central South University,China
文摘An accurate long-term energy demand forecasting is essential for energy planning and policy making. However, due to the immature energy data collecting and statistical methods, the available data are usually limited in many regions. In this paper, on the basis of comprehensive literature review, we proposed a hybrid model based on the long-range alternative energy planning (LEAP) model to improve the accuracy of energy demand forecasting in these regions. By taking Hunan province, China as a typical case, the proposed hybrid model was applied to estimating the possible future energy demand and energy-saving potentials in different sectors. The structure of LEAP model was estimated by Sankey energy flow, and Leslie matrix and autoregressive integrated moving average (ARIMA) models were used to predict the population, industrial structure and transportation turnover, respectively. Monte-Carlo method was employed to evaluate the uncertainty of forecasted results. The results showed that the hybrid model combined with scenario analysis provided a relatively accurate forecast for the long-term energy demand in regions with limited statistical data, and the average standard error of probabilistic distribution in 2030 energy demand was as low as 0.15. The prediction results could provide supportive references to identify energy-saving potentials and energy development pathways.
基金Project(70901025) supported by the National Natural Science Foundation of China
文摘A support vector machine (SVM) forecasting model based on rough set (RS) data preprocess was proposed by combining the rough set attribute reduction and the support vector machine regression algorithm, because there are strong complementarities between two models. Firstly, the rough set was used to reduce the condition attributes, then to eliminate the attributes that were redundant for the forecast, Secondly, it adopted the minimum condition attributes obtained by reduction and the corresponding original data to re-form a new training sample, which only kept the important attributes affecting the forecast accuracy. Finally, it studied and trained the SVM with the training samples after reduction, inputted the test samples re-formed by the minimum condition attributes and the corresponding original data, and then got the mapping relationship model between condition attributes and forecast variables after testing it. This model was used to forecast the power supply and demand. The results show that the average absolute error rate of power consumption of the whole society and yearly maximum load are 14.21% and 13.23%, respectively, which indicates that the RS-SVM forecast model has a higher degree of accuracy.
基金supported by the National Natural Science Foundation of China (71771216,71701209)Shaanxi Natural Science Foundation (2019 JQ-250)。
文摘From the view of information flow, a super-network equilibrium optimization model is proposed to compute the solution of the operation architecture which is made up of a perceptive level, a command level and a firepower level. Firstly, the optimized conditions of the perceptive level, command level and firepower level are analyzed respectively based on the demand of information relation,and then the information supply-and-demand equilibrium model of the operation architecture super-network is established. Secondly,a variational inequality transformation(VIT) model for equilibrium optimization of the operation architecture is given. Thirdly, the contraction projection algorithm for solving the operation architecture super-network equilibrium optimization model with fuzzy demands is designed. Finally, numerical examples are given to prove the validity and rationality of the proposed method, and the influence of fuzzy demands on the super-network equilibrium solution of operation architecture is discussed.
文摘The systematism of weapon combat is the typical characteristic of a modern battlefield.The process of combat is complex and the demand description of weapon system of systems(SOS)is difficult.Granular analyzing is an important method for solving the complex problem in the world.Granular thinking is introduced into the demand description of weapon SoS.Granular computing and granular combination based on a relation of compatibility is proposed.Based on the level of degree and degree of detail,the granular resolution of weapon SoS is defined and an example is illustrated at the end.
基金the National Natural Science Foundation of China (70625001 70431003+2 种基金 70601004)theKey Project of Scientific and Research of MOE (104064)the Program of New Century Excellent Talents ( NCET-04-0280) ofMOE.
文摘The time-varying demands for a certain period are often assumed to be less than the basic economic order quantity （EOQ） so that total replenishment quantity rather than economic order quantity is normally considered by most of the heuristics. This acticle focuses on a combined heuristics method for determining order quantity under generalized time-varying demands. The independent policy （IP）, abnormal independent policy （AIP） and dependent policies are studied and compared. Using the concepts of normal/abnormal periods and the properties of dependent policies, a dependent policy-based heuristics （DPH） is proposed for solving the order quantity problems with a kind of time-varying demands pattern under which the first period is normal. By merging the Silver-Meal （S-M） heuristics and the dependent policy-based heuristics （DPH）, a combined heuristics （DPH/S-M） is developed for solving order quantity problems with generalized time-varying demands. The experimentation shows that （1） for the problem with one normal period, no matter which position the normal period stands, the DPH/S-M could not guarantee better than the S-M heuristics, however it is superior to the S-M heuristics in the case that the demands in the abnormal periods are in descending order, and （2） The DPH/S-M is superior to the S-M heuristics for problems with more than one normal period, and the more the number of normal periods, the greater the improvements.
文摘To achieve CO2 emissions reductions, the UK Building Regulations require developers of new residential buildings to calculate expected CO2 emissions arising from their energy consumption using a methodology such as Standard Assessment Procedure （SAP 2005） or, more recently SAP 2009. SAP encompasses all domestic heat consumption and a limited proportion of the electricity consumption. However, these calculations are rarely verified with real energy consumption and related CO2 emissions. This work presents the results of an analysis based on weekly heat demand data for more than 200 individual fiats. The data were collected from a recently built residential development connected to a district heating network. A method for separating out the domestic hot water （DHW） use and space heating （SH） demand has been developed and these values are compared to the demand calculated using SAP 2005 and SAP 2009 methodologies. The analysis also shows the variation in DHW and SH consumption with size of flats and with tenure （privately owned or social housing）. Evaluation of the space heating consumption also includes an estimate of the heating degree day （HDD） base temperature for each block of fiats and compares this to the average base temperature calculated using the SAP 2005 methodology.
文摘Based on the modern economic theory and the characteristics of China's energy consumption, this paper analyzes the determinants of energy demand in China, builds up a China's energy demand model, and examines the long-run relationship between China's aggregate energy consumption and the main economic variables such as GDP by using the Johansen multivariate approach. It is found that there exists unique long-run relationship among the variables in the model over the sampling period. An error-correction model provides an appropriate framework for forecasting the short-run fluctuations in the aggregate demand of China.
文摘In the integrated production-shipment models for the single-vendor-single-buyer system presented hitherto, the demand rate of items is treated as a constant. However, many researchers have observed that the presence of more quantities of the same product tends to attract more customers. This suggests that the demand rate should depend on the stock level. This paper presents a single-vendor-single-buyer production-shipment model with the stock dependent demand rate, based on the demand rate linearly depending upon the stock level at any instant of time.
文摘In this paper, a deterministic lot-sizing model is developed for an item during its lifeperiod. A demand for the item is approximated by a special polynomial function. And shortages areallowed to occur in the proposed model. A simple dynamic programming method is presented forgenerating the optimal replenishment policy. A numerical example is used to illustrate the solutionprocedure for the special case with quadric demand. Sensitivity analysis for parameters is alsoincluded.
文摘The long-term energy demand in China and the-Chinese share in global CO2 emission are forecasted on the basis of scenarios of population growth and economy development up to 2050 proposed in view of the interaction of energy, economy, environment and social development. The total energy demand in 2050 will reach 4.4~ 5.4 billion tce. It is shown in energy supply analysis that coal is China’s major energy in primary energy supply. The share of CO2 emission in the future Chinese energy system will be out of proportion to its energy consumption share because of the high persentage of coal to be consumed. It will reach about 27%. The nuclear option which would replace 30.7% of coal in the total primary energy supply will reduce the share by 9.8%. So the policy considerations on the future Chinese energy system is of great importance to the global CO2 issues.
基金supported by the National Natural Science Foundation of China(62171218)。
文摘As a typical industrial Internet of things(IIOT)service,demand response(DR)is becoming a promising enabler for intelligent energy management in 6 G-enabled smart grid systems,to achieve quick response for supply-demand mismatches.How-ever,existing literatures try to adjust customers’load profiles optimally,instead of electricity overhead,energy consumption patterns of residential appliances,customer satisfaction levels,and energy consumption habits.In this paper,a novel DR method is investigated by mixing the aforementioned factors,where the residential customer cluster is proposed to enhance the performance.Clustering approaches are leveraged to study the electricity consumption habits of various customers by extracting their features and characteristics from historical data.Based on the extracted information,the residential appliances can be scheduled effectively and flexibly.Moreover,we propose and study an efficient optimization framework to obtain the optimal scheduling solution by using clustering and deep learning methods.Extensive simulation experiments are conducted with real-world traces.Numerical results show that the proposed DR method and optimization framework outperform other baseline schemes in terms of the system overhead and peak-to-average ratio(PAR).The impact of various factors on the system utility is further analyzed,which provides useful insights on improving the efficiency of the DR strategy.With the achievement of efficient and intelligent energy management,the proposed method also promotes the realization of China’s carbon peaking and carbon neutrality goals.
文摘Exchange rate functions under systems of centrallyplanned economy and market economy are quite different,and the mechanism to determine such exchange rate is alsodifferent. To adopt a socialist market economic system inChina, the exchange rate mechanism of Renminbi must bethoroughly transformed. To accomplish this goal, I believethere are three problems that must be solved: first,
文摘Agricultural Products Processing and Storage (ISSN 3059-4510,Owner:Hunan Academy of Agricultural Sciences,China.Production and hosting:Springer Nature) is an international,pect-review ed open access journal with the aim to offer a platform for the rapid dissemination of significant,novel,and high-impact research in the fields of agricultural product processing science,technology,engineering,and nutrition.Additio nally,supplemental issues are curated and published to facilitate in-depth discussions on special topics.
