In this paper, the mechanisms and principles of economic regulation from the classical and modem approaches standpoints were analyzed, the typical for world economic theory trends of the government＇s economic role el...In this paper, the mechanisms and principles of economic regulation from the classical and modem approaches standpoints were analyzed, the typical for world economic theory trends of the government＇s economic role elaboration, of the government regulatory authority, reducing in favor of market self-organization was argued. The transnationalization as a factor of government regulation mechanisms modernization was estimated and the perspectives of government and MNC interactions development in the modem world were evaluated. The recommendations for improving the government economical regulation infrastructure and mechanisms due to the conditions of economy globalizing, transnational business developing, technologies progressing were presented展开更多
Investigation of protein-DNA interactions provides important information for understanding gene function and regulation, but identification and validation of specific interactions remain major challenges in the post-g...Investigation of protein-DNA interactions provides important information for understanding gene function and regulation, but identification and validation of specific interactions remain major challenges in the post-genomics era. Therefore, effective and economical methods to assess protein-DNA interactions are highly sought-after by molec- ular biologists.展开更多
With the liberalization of the retail market,customers can sell their demand response(DR)resources to the distribution company(Disco)through the DR aggregator(DRA).In this paper,an intelligent DR resource trading fram...With the liberalization of the retail market,customers can sell their demand response(DR)resources to the distribution company(Disco)through the DR aggregator(DRA).In this paper,an intelligent DR resource trading framework between Disco and DRA is proposed by exploiting the benefits of deep reinforcement learning(DRL).The hierarchical decision process of the two players is modeled as a Stackelberg game.In the game,Disco is the leader who determines the retail price while DRA is the follower who responds to it.To protect their privacy,a dueling deep Q-network(dueling DQN)is then constructed to model the bi-level Stackelberg game,such that the lower-level problem doesn’t need to reveal its detailed model to the upperlevel.In the learning process,the uncertainties from the DRA’s baseline load and wind power are considered.In order to boost the robustness against the estimation error,the baseline load is discretized into symbols before being used as the input states of the dueling DQN.And to mitigate the uncertainty of wind power,the scenario-based method is introduced when designing the reward.We demonstrate that the proposed dueling DQNbased method has good performance and is more robust against uncertainties.展开更多
文摘In this paper, the mechanisms and principles of economic regulation from the classical and modem approaches standpoints were analyzed, the typical for world economic theory trends of the government＇s economic role elaboration, of the government regulatory authority, reducing in favor of market self-organization was argued. The transnationalization as a factor of government regulation mechanisms modernization was estimated and the perspectives of government and MNC interactions development in the modem world were evaluated. The recommendations for improving the government economical regulation infrastructure and mechanisms due to the conditions of economy globalizing, transnational business developing, technologies progressing were presented
基金supported by the National Natural Science Foundation of China (31471564) to L. C
文摘Investigation of protein-DNA interactions provides important information for understanding gene function and regulation, but identification and validation of specific interactions remain major challenges in the post-genomics era. Therefore, effective and economical methods to assess protein-DNA interactions are highly sought-after by molec- ular biologists.
基金supported by the National Key R&D Program of China(2021YFB2401203).
文摘With the liberalization of the retail market,customers can sell their demand response(DR)resources to the distribution company(Disco)through the DR aggregator(DRA).In this paper,an intelligent DR resource trading framework between Disco and DRA is proposed by exploiting the benefits of deep reinforcement learning(DRL).The hierarchical decision process of the two players is modeled as a Stackelberg game.In the game,Disco is the leader who determines the retail price while DRA is the follower who responds to it.To protect their privacy,a dueling deep Q-network(dueling DQN)is then constructed to model the bi-level Stackelberg game,such that the lower-level problem doesn’t need to reveal its detailed model to the upperlevel.In the learning process,the uncertainties from the DRA’s baseline load and wind power are considered.In order to boost the robustness against the estimation error,the baseline load is discretized into symbols before being used as the input states of the dueling DQN.And to mitigate the uncertainty of wind power,the scenario-based method is introduced when designing the reward.We demonstrate that the proposed dueling DQNbased method has good performance and is more robust against uncertainties.
