2022
DOI: 10.1007/s00521-022-07696-2
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Deep Q networks-based optimization of emergency resource scheduling for urban public health events

Abstract: In today's severe situation of the global new crown virus raging, there are still efficiency problems in emergency resource scheduling, and there are still deficiencies in rescue standards. For the happiness and well-being of people's lives, adhering to the principle of a community with a shared future for mankind, the emergency resource scheduling system for urban public health emergencies needs to be improved and perfected. This paper mainly studies the optimization model of urban emergency resource scheduli… Show more

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Cited by 7 publications
(4 citation statements)
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“…Some articles investigated the role of AI in designing, implementing, and analyzing the results of simulated public health and healthcare policy interventions [43] and have introduced different improved public health service platforms that can store and transmit a large number of user data in the network environment, automatically maintaining the stability of the system and have an excellent social application value [44]. On the other hand, there are new methods, for instance, to simulate various interventions that intend to control outbreaks [45], support the extraction of actionable knowledge on bene t rules from regulatory healthcare policy text [46], effective and feasible resource scheduling optimization [47] and strategies that can increase the exibility of political decisions and identify ideal solutions for global health [45]. Some examples of other studies that would facilitate designing better policies include the identi cation of key factors associated with legislative success [48], determining the in uence of policy instruments on targets [49], providing a tool to evaluate the dispatching policies for the network of emergency departments [50], and identifying factors that can predict behaviors [51].…”
Section: Contentmentioning
confidence: 99%
“…Some articles investigated the role of AI in designing, implementing, and analyzing the results of simulated public health and healthcare policy interventions [43] and have introduced different improved public health service platforms that can store and transmit a large number of user data in the network environment, automatically maintaining the stability of the system and have an excellent social application value [44]. On the other hand, there are new methods, for instance, to simulate various interventions that intend to control outbreaks [45], support the extraction of actionable knowledge on bene t rules from regulatory healthcare policy text [46], effective and feasible resource scheduling optimization [47] and strategies that can increase the exibility of political decisions and identify ideal solutions for global health [45]. Some examples of other studies that would facilitate designing better policies include the identi cation of key factors associated with legislative success [48], determining the in uence of policy instruments on targets [49], providing a tool to evaluate the dispatching policies for the network of emergency departments [50], and identifying factors that can predict behaviors [51].…”
Section: Contentmentioning
confidence: 99%
“…During task allocation, the execution strategy corresponding to the solution x needs to be solved to meet the dependencies between tasks and environmental parameters, that is, the solution obtained should be in the feasible space. In the research of task allocation, the existing deep reinforcement learning methods usually regard it as an end-to-end learning task, and have designed different models and training methods [11][12][13][14][15][16][17]. However, by exploring each step of action, the model will not get a reward function value for completing the task until the whole scheduling task is completed, resulting in sparse rewards, large state space, and difficulty in training.…”
Section: Graph Convolution Fusion Scheduling Modelmentioning
confidence: 99%
“…The concept of "community of human destiny" in the preamble of the Constitution of the People's Republic of China outlines the content and development direction of the discourse of international exchanges with Chinese characteristics and provides an ethical code for all-around cross-border and cross-civilization exchanges [1][2][3]. "Human civilization, exchanges and mutual understanding" is the core discourse of the initiative of the community of human destiny; humanistic exchanges and the "community of human destiny" complement each other and are the core values guiding the opening up of education to the outside world and international exchanges in education.…”
Section: Introductionmentioning
confidence: 99%