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The Users-Demand-Oriented Stochastic Scheduling Method on Seawater Desalination System

机译:面向用户需求的海水淡化系统随机调度方法

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In order to protect the water-supply scheme from the predictive error of water consumption, an user-demand oriented stochastic water-supply scheduling method on the seawater desalination system is proposed. Firstly, Classification and Regression Tree is used to estimate the prediction interval of the users' future demands. Dependent-Chance Programming and Monte Carlo Simulation are used to figure out the probability of the event that the allocated water meets the demands of users. The equilibrium of water-supply is also taken into consideration. In this way, the stochastic model is transformed into the multi-objective optimization problem. Multiple-Population Quantum Genetic Algorithm is employed to acquire the optimal solution. The result of real-world case study validates the effectiveness of the proposed method.
机译:为了保护供水方案免受耗水误差的预测误差,提出了海水淡化系统的用户需求导向随机供水调度方法。首先,分类和回归树用于估计用户未来需求的预测间隔。依赖机会编程和蒙特卡罗模拟用于弄清楚分配的水符合用户需求的事件的可能性。还考虑了供水的平衡。以这种方式,随机模型转变为多目标优化问题。采用多群量子遗传算法来获取最佳解决方案。现实案例研究的结果验证了所提出的方法的有效性。

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