Abstract The design and evaluation of algorithms for adaptive stochastic control of reservoir function of the water reservoir using artificial intelligence methods (learning fuzzy model and neural networks) are described in this article. This procedure was tested on an artificial reservoir. Reservoir parameters have been designed to cause critical disturbances during the control process, and therefore the influences of control algorithms can be demonstrated in the course of controlled outflow of water from the reservoir. The results of the stochastic adaptive models were compared. Further, stochastic model results were compared with a resultant course of management obtained using the method of classical optimisation (differential evolution), which used stochastic forecast data from real series (100% forecast). Finally, the results of the dispatcher graph and adaptive stochastic control were compared. Achieved results of adaptive stochastic management provide inspiration for continuing research in the field.

中文翻译：

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基于人工智能的大型露天水库蓄水功能自适应随机管理

摘要 本文描述了使用人工智能方法（学习模糊模型和神经网络）的水库水库函数自适应随机控制算法的设计和评估。该程序在人工水库上进行了测试。水库参数被设计为在控制过程中引起临界扰动，因此控制算法的影响可以在水库控制出水过程中得到证明。对随机自适应模型的结果进行了比较。此外，将随机模型结果与使用经典优化（差分进化）方法获得的管理结果进行比较，该方法使用来自真实序列的随机预测数据（100% 预测）。最后，调度程序图和自适应随机控制的结果进行了比较。自适应随机管理取得的成果为该领域的继续研究提供了灵感。