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Input-output dynamic model for optimal environmental pollution control

机译:最优环境污染控制的输入输出动态模型

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This paper describes the allocation of a wastewater treatment fund within a region based on a dynamic input-output model. Considering the complexity of the input-output process, many indeterminate factors must be included in the model. For example, with the aging of machines, an unexpected loss will be caused by the retention of raw materials during an operation; this can be realistically considered as a random variable, because of the sufficiently large amount of historical data. By contrast, actions such as a temporary transfer or inexperienced operators can only be regard as uncertain variables, because of a lack of historical data. First, the pollution control model is formulated in an uncertain environment by including both human uncertainty and objective randomness. Second, an optimal control model subject to an uncertain random singular system is established; this model can be transformed into an equivalent optimization problem. To solve such a problem, recurrence equations are presented based on Bellman's principle, and these were successfully applied to address the optimal control problem in two special cases. Moreover, two algorithms are formulated for solving the pollution control problem. Finally, the optimal distribution strategies of the pollution control fund used to control the emissions of COD and NH_3-H, which are two indicators of wastewater in China, were obtained through the proposed algorithms.
机译:本文介绍了基于动态输入输出模型的区域内的废水处理基金的分配。考虑到输入输出过程的复杂性,必须在模型中包含许多不确定因子。例如,随着机器的老化,在操作期间的原料保持原材料会引起意外损失;这可以将其现实地被视为随机变量,因为历史数据量足够大。相比之下,由于缺乏历史数据,诸如临时转移或缺乏经验的运营商的行为只能视为不确定的变量。首先,通过包括人的不确定性和客观随机性,在不确定的环境中制定污染控制模型。其次,建立了不确定的随机奇异系统的最佳控制模型;该模型可以转换为等同的优化问题。为了解决这样的问题,基于Bellman的原理提出了复发方程,并成功地应用了两个特殊情况下的最佳控制问题。此外,配制了两种算法以解决污染控制问题。最后,通过所提出的算法获得了用于控制COD和NH_3-H排放的污染控制基金的最佳分布策略,这是中国废水的两个指标。

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