{"id":41024,"date":"2024-09-25T11:28:23","date_gmt":"2024-09-25T11:28:23","guid":{"rendered":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-%d9%be%d8%b1-%da%a9%d8%b1%d8%af%d9%86-%d9%88-%d8%b1%db%8c%d8%ae%d8%aa%d9%86-%d8%b1%d9%88%d8%b4\/"},"modified":"2024-09-25T11:29:36","modified_gmt":"2024-09-25T11:29:36","slug":"%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-%d9%be%d8%b1-%da%a9%d8%b1%d8%af%d9%86-%d9%88-%d8%b1%db%8c%d8%ae%d8%aa%d9%86-%d8%b1%d9%88%d8%b4","status":"publish","type":"product","link":"https:\/\/express24.ir\/d\/product\/%d8%aa%d8%b1%d8%ac%d9%85%d9%87-%d9%81%d8%a7%d8%b1%d8%b3%db%8c-%d9%85%d9%82%d8%a7%d9%84%d9%87-%d9%be%d8%b1-%da%a9%d8%b1%d8%af%d9%86-%d9%88-%d8%b1%db%8c%d8%ae%d8%aa%d9%86-%d8%b1%d9%88%d8%b4\/","title":{"rendered":"\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u067e\u0631 \u06a9\u0631\u062f\u0646 \u0648 \u0631\u06cc\u062e\u062a\u0646: \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u0633\u06cc\u0627\u0633\u062a \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062a\u0642\u0648\u06cc\u062a\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0631\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645\u200c\u06af\u06cc\u0631\u06cc \u0648 \u06a9\u0646\u062a\u0631\u0644 \u0639\u0645\u0644\u06cc\u0627\u062a \u0645\u062e\u0632\u0646"},"content":{"rendered":"\n\n\n\n\n\n\n\n\n\n\n\n\n\n\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nFill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control<\/td>\n<\/tr>\n
\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u067e\u0631 \u06a9\u0631\u062f\u0646 \u0648 \u0631\u06cc\u062e\u062a\u0646: \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u0633\u06cc\u0627\u0633\u062a \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062a\u0642\u0648\u06cc\u062a\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0631\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645\u200c\u06af\u06cc\u0631\u06cc \u0648 \u06a9\u0646\u062a\u0631\u0644 \u0639\u0645\u0644\u06cc\u0627\u062a \u0645\u062e\u0632\u0646<\/td>\n<\/tr>\n
\u0646\u0648\u06cc\u0633\u0646\u062f\u06af\u0627\u0646 <\/td>\nSadegh Sadeghi Tabas, Vidya Samadi<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc <\/td>\nPDF<\/td>\n<\/tr>\n
\u0632\u0628\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u062a\u062d\u0648\u06cc\u0644\u06cc <\/td>\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc<\/td>\n<\/tr>\n
\u0641\u0631\u0645\u062a \u0645\u0642\u0627\u0644\u0647 \u062a\u0631\u062c\u0645\u0647 \u0634\u062f\u0647 <\/td>\n\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\n<\/tr>\n
\u0646\u062d\u0648\u0647 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 <\/td>\n\u062f\u0648 \u062a\u0627 \u0633\u0647 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634 (\u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u062f\u0627\u0646\u0644\u0648\u062f\u06cc)<\/td>\n<\/tr>\n
\u062a\u0639\u062f\u0627\u062f \u0635\u0641\u062d\u0627\u062a<\/td>\n39<\/td>\n<\/tr>\n
\u0644\u06cc\u0646\u06a9 \u062f\u0627\u0646\u0644\u0648\u062f \u0631\u0627\u06cc\u06af\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc<\/td>\n\u062f\u0627\u0646\u0644\u0648\u062f \u0645\u0642\u0627\u0644\u0647<\/a><\/td>\n<\/tr>\n
\u062f\u0633\u062a\u0647 \u0628\u0646\u062f\u06cc \u0645\u0648\u0636\u0648\u0639\u0627\u062a <\/td>\nMachine Learning,Optimization and Control,\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u0645\u0627\u0634\u06cc\u0646 , \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u0648 \u06a9\u0646\u062a\u0631\u0644 ,<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a <\/td>\nSubmitted 6 March, 2024; originally announced March 2024.<\/td>\n<\/tr>\n
\u062a\u0648\u0636\u06cc\u062d\u0627\u062a \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc <\/td>\n\u0627\u0631\u0633\u0627\u0644 6 \u0645\u0627\u0631\u0633 2024 \u061b\u062f\u0631 \u0627\u0628\u062a\u062f\u0627 \u0645\u0627\u0631\u0633 2024 \u0627\u0639\u0644\u0627\u0645 \u0634\u062f.<\/td>\n<\/tr>\n
\u0627\u0637\u0644\u0627\u0639\u0627\u062a \u0628\u06cc\u0634\u062a\u0631 \u0627\u0632 \u0627\u06cc\u0646 \u0645\u0642\u0627\u0644\u0647 \u062f\u0631 \u067e\u0627\u06cc\u06af\u0627\u0647 \u0647\u0627\u06cc \u0639\u0644\u0645\u06cc <\/td>\n\n INSPIRE HEP<\/a>
\n
\n NASA ADS<\/a>
\n
\n Google Scholar<\/a>
\n
\n Semantic Scholar<\/a>
\n
\n arXiv<\/a><\/p>\n<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n

\u0686\u06a9\u06cc\u062f\u0647<\/h2>\n

Changes in demand, various hydrological inputs, and environmental stressors are among the issues that water managers and policymakers face on a regular basis. These concerns have sparked interest in applying different techniques to determine reservoir operation policy decisions. As the resolution of the analysis increases, it becomes more difficult to effectively represent a real-world system using traditional methods such as Dynamic Programming (DP) and Stochastic Dynamic Programming (SDP) for determining the best reservoir operation policy. One of the challenges is the “curse of dimensionality,” which means the number of samples needed to estimate an arbitrary function with a given level of accuracy grows exponentially with respect to the number of input variables (i.e., dimensionality) of the function. Deep Reinforcement Learning (DRL) is an intelligent approach to overcome the curses of stochastic optimization problems for reservoir operation policy decisions. To our knowledge, this study is the first attempt that examine various novel DRL continuous-action policy gradient methods (PGMs), including Deep Deterministic Policy Gradients (DDPG), Twin Delayed DDPG (TD3), and two different versions of Soft Actor-Critic (SAC18 and SAC19) for optimizing reservoir operation policy. In this study, multiple DRL techniques were implemented in order to find the optimal operation policy of Folsom Reservoir in California, USA. The reservoir system supplies agricultural, municipal, hydropower, and environmental flow demands and flood control operations to the City of Sacramento. Analysis suggests that the TD3 and SAC are robust to meet the Folsom Reservoir’s demands and optimize reservoir operation policies.<\/p>\n

\u0686\u06a9\u06cc\u062f\u0647 \u0628\u0647 \u0641\u0627\u0631\u0633\u06cc (\u062a\u0631\u062c\u0645\u0647 \u0645\u0627\u0634\u06cc\u0646\u06cc)<\/h2>\n

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\u0645\u062e\u062a\u0644\u0641 \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u062a\u0635\u0645\u06cc\u0645\u0627\u062a \u0633\u06cc\u0627\u0633\u062a \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062e\u0632\u0646 \u062a\u0628\u062f\u06cc\u0644 \u0634\u0648\u062f.\u0628\u0627 \u0627\u0641\u0632\u0627\u06cc\u0634 \u0648\u0636\u0648\u062d \u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u060c \u0627\u0631\u0627\u0626\u0647 \u0645\u0624\u062b\u0631 \u06cc\u06a9 \u0633\u06cc\u0633\u062a\u0645 \u062f\u0631 \u062f\u0646\u06cc\u0627\u06cc \u0648\u0627\u0642\u0639\u06cc \u0628\u0627 \u0627\u0633\u062a\u0641\u0627\u062f\u0647 \u0627\u0632 \u0631\u0648\u0634 \u0647\u0627\u06cc \u0633\u0646\u062a\u06cc \u0645\u0627\u0646\u0646\u062f \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0648\u06cc\u0627 (DP) \u0648 \u0628\u0631\u0646\u0627\u0645\u0647 \u0646\u0648\u06cc\u0633\u06cc \u067e\u0648\u06cc\u0627 \u062a\u0635\u0627\u062f\u0641\u06cc (SDP) \u0628\u0631\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u0628\u0647\u062a\u0631\u06cc\u0646 \u0633\u06cc\u0627\u0633\u062a \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062e\u0632\u0646 \u062f\u0634\u0648\u0627\u0631\u062a\u0631 \u0645\u06cc \u0634\u0648\u062f.\u06cc\u06a9\u06cc \u0627\u0632 \u0686\u0627\u0644\u0634 \u0647\u0627 “\u0646\u0641\u0631\u06cc\u0646 \u0627\u0628\u0639\u0627\u062f” \u0627\u0633\u062a \u060c \u0628\u0647 \u0627\u06cc\u0646 \u0645\u0639\u0646\u06cc \u06a9\u0647 \u062a\u0639\u062f\u0627\u062f \u0646\u0645\u0648\u0646\u0647 \u0647\u0627\u06cc \u0645\u0648\u0631\u062f \u0646\u06cc\u0627\u0632 \u0628\u0631\u0627\u06cc \u0628\u0631\u0622\u0648\u0631\u062f \u06cc\u06a9 \u0639\u0645\u0644\u06a9\u0631\u062f \u062f\u0644\u062e\u0648\u0627\u0647 \u0628\u0627 \u06cc\u06a9 \u0633\u0637\u062d \u0645\u0639\u06cc\u0646 \u0627\u0632 \u062f\u0642\u062a \u0628\u0627 \u062a\u0648\u062c\u0647 \u0628\u0647 \u062a\u0639\u062f\u0627\u062f \u0645\u062a\u063a\u06cc\u0631\u0647\u0627\u06cc \u0648\u0631\u0648\u062f\u06cc (\u06cc\u0639\u0646\u06cc \u0627\u0628\u0639\u0627\u062f) \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647 \u0635\u0648\u0631\u062a \u062a\u0635\u0627\u0639\u062f\u06cc \u0631\u0634\u062f \u0645\u06cc \u06a9\u0646\u062f.\u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062a\u0642\u0648\u06cc\u062a \u0639\u0645\u06cc\u0642 (DRL) \u06cc\u06a9 \u0631\u0648\u06cc\u06a9\u0631\u062f \u0647\u0648\u0634\u0645\u0646\u062f\u0627\u0646\u0647 \u0628\u0631\u0627\u06cc \u063a\u0644\u0628\u0647 \u0628\u0631 \u0644\u0639\u0646\u062a \u0647\u0627\u06cc \u0645\u0634\u06a9\u0644\u0627\u062a \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u062a\u0635\u0627\u062f\u0641\u06cc \u0628\u0631\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645\u0627\u062a \u0633\u06cc\u0627\u0633\u062a \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062e\u0632\u0646 \u0627\u0633\u062a.\u0628\u0647 \u062f\u0627\u0646\u0634 \u0645\u0627 \u060c \u0627\u06cc\u0646 \u0645\u0637\u0627\u0644\u0639\u0647 \u0627\u0648\u0644\u06cc\u0646 \u062a\u0644\u0627\u0634\u06cc \u0627\u0633\u062a \u06a9\u0647 \u0631\u0648\u0634\u0647\u0627\u06cc \u0645\u062e\u062a\u0644\u0641 \u0634\u06cc\u0628 \u0633\u06cc\u0627\u0633\u062a \u0645\u062f\u0627\u0648\u0645 DRL \u0631\u0627 \u0628\u0631\u0631\u0633\u06cc \u0645\u06cc \u06a9\u0646\u062f (PGM) \u060c \u0627\u0632 \u062c\u0645\u0644\u0647 \u0634\u06cc\u0628 \u0633\u06cc\u0627\u0633\u062a \u0647\u0627\u06cc \u062a\u0639\u06cc\u06cc\u0646 \u06a9\u0646\u0646\u062f\u0647 \u0639\u0645\u06cc\u0642 (DDPG) \u060c DDPG \u0628\u0627 \u062a\u0623\u062e\u06cc\u0631 \u062f\u0648\u0642\u0644\u0648\u06cc (TD3) \u0648 \u062f\u0648 \u0646\u0633\u062e\u0647 \u0645\u062e\u062a\u0644\u0641 \u0627\u0632 \u0628\u0627\u0632\u06cc\u06af\u0631 \u0646\u0631\u0645 \u0648 \u0627\u0646\u062a\u0642\u0627\u062f\u06cc \u0628\u0627\u0632\u06cc\u06af\u0631 \u0646\u0631\u0645(SAC18 \u0648 SAC19) \u0628\u0631\u0627\u06cc \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u0633\u06cc\u0627\u0633\u062a \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062e\u0632\u0646.\u062f\u0631 \u0627\u06cc\u0646 \u0645\u0637\u0627\u0644\u0639\u0647 \u060c \u0686\u0646\u062f \u062a\u06a9\u0646\u06cc\u06a9 DRL \u0628\u0647 \u0645\u0646\u0638\u0648\u0631 \u06cc\u0627\u0641\u062a\u0646 \u0633\u06cc\u0627\u0633\u062a \u0639\u0645\u0644\u06a9\u0631\u062f \u0628\u0647\u06cc\u0646\u0647 \u0645\u062e\u0632\u0646 Folsom \u062f\u0631 \u06a9\u0627\u0644\u06cc\u0641\u0631\u0646\u06cc\u0627 \u060c \u0627\u06cc\u0627\u0644\u0627\u062a \u0645\u062a\u062d\u062f\u0647 \u0622\u0645\u0631\u06cc\u06a9\u0627 \u0627\u062c\u0631\u0627 \u0634\u062f.\u0633\u06cc\u0633\u062a\u0645 \u0645\u062e\u0632\u0646 \u0646\u06cc\u0627\u0632\u0647\u0627\u06cc \u062c\u0631\u06cc\u0627\u0646 \u06a9\u0634\u0627\u0648\u0631\u0632\u06cc \u060c \u0634\u0647\u0631\u062f\u0627\u0631\u06cc \u060c \u0646\u06cc\u0631\u0648\u06af\u0627\u0647 \u0648 \u0645\u062d\u06cc\u0637 \u0632\u06cc\u0633\u062a \u0648 \u0639\u0645\u0644\u06cc\u0627\u062a \u06a9\u0646\u062a\u0631\u0644 \u0633\u06cc\u0644 \u0631\u0627 \u0628\u0647 \u0634\u0647\u0631 \u0633\u0627\u06a9\u0631\u0627\u0645\u0646\u062a\u0648 \u062a\u0623\u0645\u06cc\u0646 \u0645\u06cc \u06a9\u0646\u062f.\u062a\u062c\u0632\u06cc\u0647 \u0648 \u062a\u062d\u0644\u06cc\u0644 \u0646\u0634\u0627\u0646 \u0645\u06cc \u062f\u0647\u062f \u06a9\u0647 TD3 \u0648 SAC \u0628\u0631\u0627\u06cc \u067e\u0627\u0633\u062e\u06af\u0648\u06cc\u06cc \u0628\u0647 \u062e\u0648\u0627\u0633\u062a\u0647 \u0647\u0627\u06cc \u0645\u062e\u0632\u0646 Folsom \u0648 \u0628\u0647\u06cc\u0646\u0647 \u0633\u0627\u0632\u06cc \u0633\u06cc\u0627\u0633\u062a \u0647\u0627\u06cc \u0639\u0645\u0644\u06a9\u0631\u062f \u0645\u062e\u0632\u0646 \u0642\u0648\u06cc \u0647\u0633\u062a\u0646\u062f.<\/p>\n\r\n\r\n \r\n \r\n \r\n \r\n
\u0641\u0631\u0645\u062a \u0627\u0631\u0627\u0626\u0647 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u062a\u062d\u0648\u06cc\u0644 \u0628\u0647 \u0635\u0648\u0631\u062a \u0641\u0627\u06cc\u0644 \u0648\u0631\u062f<\/td>\r\n <\/tr>\r\n
\u0632\u0645\u0627\u0646 \u062a\u062d\u0648\u06cc\u0644 \u062a\u0631\u062c\u0645\u0647 \u0645\u0642\u0627\u0644\u0647 <\/td>\r\n \u0628\u06cc\u0646 2 \u062a\u0627 3 \u0631\u0648\u0632 \u067e\u0633 \u0627\u0632 \u062b\u0628\u062a \u0633\u0641\u0627\u0631\u0634<\/td>\r\n <\/tr>\r\n\t
\u06a9\u06cc\u0641\u06cc\u062a \u062a\u0631\u062c\u0645\u0647 <\/td>\r\n \u0628\u0633\u06cc\u0627\u0631 \u0628\u0627\u0644\u0627. \u0645\u0642\u0627\u0644\u0647 \u0641\u0642\u0637 \u062a\u0648\u0633\u0637 \u0645\u062a\u0631\u062c\u0645\u06cc\u0646 \u0628\u0627 \u0645\u062f\u0631\u06a9 \u062f\u0627\u0646\u0634\u06af\u0627\u0647\u06cc \u0645\u062a\u0631\u062c\u0645\u06cc \u062a\u0631\u062c\u0645\u0647 \u0645\u06cc\u200c\u0634\u0648\u062f.<\/td>\r\n <\/tr>\r\n\t\t
\u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 <\/td>\r\n \u06a9\u0644\u06cc\u0647 \u062c\u062f\u0627\u0648\u0644 \u0648 \u0641\u0631\u0645\u0648\u0644 \u0647\u0627 \u0646\u06cc\u0632 \u062f\u0631 \u0641\u0627\u06cc\u0644 \u062a\u062d\u0648\u06cc\u0644\u06cc \u0648\u0631\u062f \u062f\u0631\u062c \u0645\u06cc\u200c\u0634\u0648\u0646\u062f.<\/td>\r\n <\/tr>\r\n<\/table>\r\n\r\n\n","protected":false},"excerpt":{"rendered":"

\u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 \u0627\u0646\u06af\u0644\u06cc\u0633\u06cc Fill-and-Spill: Deep Reinforcement Learning Policy Gradient Methods for Reservoir Operation Decision and Control \u0639\u0646\u0648\u0627\u0646 \u0645\u0642\u0627\u0644\u0647 \u0628\u0647 […]<\/p>\n","protected":false},"featured_media":27,"comment_status":"open","ping_status":"closed","template":"","meta":{"pmpro_default_level":"","site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-gradient":""}}},"product_cat":[15,21],"product_tag":[19,242,318,267],"class_list":{"0":"post-41024","1":"product","2":"type-product","3":"status-publish","4":"has-post-thumbnail","6":"product_cat-15","7":"product_cat-21","8":"product_tag-machine-learning","9":"product_tag-optimization-and-control","10":"product_tag-318","11":"product_tag-267","12":"pmpro-has-access","13":"desktop-align-left","14":"tablet-align-left","15":"mobile-align-left","17":"first","18":"instock","19":"downloadable","20":"shipping-taxable","21":"purchasable","22":"product-type-simple"},"yoast_head":"\n\u062a\u0631\u062c\u0645\u0647 \u0641\u0627\u0631\u0633\u06cc \u0645\u0642\u0627\u0644\u0647 \u067e\u0631 \u06a9\u0631\u062f\u0646 \u0648 \u0631\u06cc\u062e\u062a\u0646: \u0631\u0648\u0634\u200c\u0647\u0627\u06cc \u06af\u0631\u0627\u062f\u06cc\u0627\u0646 \u0633\u06cc\u0627\u0633\u062a \u06cc\u0627\u062f\u06af\u06cc\u0631\u06cc \u062a\u0642\u0648\u06cc\u062a\u06cc \u0639\u0645\u06cc\u0642 \u0628\u0631\u0627\u06cc \u062a\u0635\u0645\u06cc\u0645\u200c\u06af\u06cc\u0631\u06cc \u0648 \u06a9\u0646\u062a\u0631\u0644 \u0639\u0645\u0644\u06cc\u0627\u062a \u0645\u062e\u0632\u0646 - 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