توسعه روش یادگیری تقویتی معکوس به صورت تلفیق با مدل هیدرودینامیک ICSS در کانال دز

Abbasi, F., &Abbasi, N. (2024). An analysis of irrigation efficiencies over time in Iran. Iranian Journal of Irrigation & Drainage, 17(6), 1025-1033. (In Persian)

Aghayee, Z., Ghodousi, H., & Shahverdi, K. (2024). Uncertainty Analysis of Irrigation Canals Operation. Iranian Journal of Science and Technology, Transactions of Civil Engineering, 48(6), 4769-4779.

Alibabaei, K., Gaspar, P. D., Assuncao, E., Alirezazadeh, S., & Lima, T. M. (2022). Irrigation optimization with a deep reinforcement learning model: Case study on a site in Portugal. Agricultural Water Management, 263: 0378-3774.

Arora, S., & Doshi, P. (2021). A survey of inverse reinforcement learning: Challenges, methods and progress. Artificial Intelligence, 297, 103500.

Bayat, F., Ghodousi, H., and Shahverdi, K. (2022). Operation of irrigation canals using intelligent methods. Environmental Sciences, 20(1), 57-76. (In Persian)

Clemmens, A. J., Kacerek, T. K., Grawitz, B., & W, Schuurmans. (1998). Test cases for canal control algorithms. Journal of irrigation and drainage engineering 124(1): 23-30.

Ding, X., & Du, W. (2024). Optimizing irrigation efficiency using deep reinforcement learning in the field. ACM Transactions on Sensor Networks, 20(4), 1-34.

Garcia-Espinal, M. A., Pérez-Sánchez, M., Sánchez-Romero, F. J., & López-Jiménez, P. A. (2024). Irrigation Distribution Network Design Parameters and Their Influence on Sustainability Management. Water, 16(8), 1131.

Ghodousi, H., and Dadashi, Z. (2016). Evaluation and comparison of ICSS and Rootcanal models for simulation of flow in irrigation canals (Case study: Ghoorichay irrigation network). Iranian Water Researches Journal, 10(2), 107-116. (In Persian)

Mohebbi, H., Ghodousi, H., & Shahverdi, K. (2024). Evaluating the impact of climate change on irrigation canal performance. Irrigation and Drainage, 73(3), 961-973.

Molden, D. J., & Gates, T. K. (1990). Performance measures for evaluation of irrigation-water-delivery systems. Journal of irrigation and drainage engineering, 116(6): 804-82.

Omidzade, Fatemeh, Hesam Ghodousi, and Kazem Shahverdi. Comparing fuzzy SARSA learning and ant Colony optimization algorithms in water delivery scheduling under water shortage conditions. Journal of Irrigation and Drainage Engineering 146.9 (2020): 04020028.

Savari, H., Monem, M. J. and Shahverdi, K. (2016). Comparing the performance of FSL and traditional operation methods for on-request water delivery in the Aghili network, Iran. Journal of Irrigation and Drainage Engineering, 142(11): 04016055.

Shahdany, S. H., Majd, E. A., & Firoozfar, A. (2016). Improving Operation of a Main Irrigation Canal Suffering from Inflow Fluctuation within a Centralized Model Predictive Control System: Case Study of Roodasht Canal, Iran. Journal of Irrigation and Drainage Engineering, 142(11): 05016007.

Shahverdi, K., & Javad Monem, M. (2022). Irrigation canal control using enhanced Fuzzy SARSA learning. Irrigation and Drainage, 71(3), 766-775.

Shahverdi, k. (2022). Determining operational patterns considering operator’s error in structures settings in irrigation networks. Water and Irrigation Management, 12(2), 349-358. (In Persian)

Shahverdi, K. (2023). AICSS: Automatic simulator–controller/optimizer model of open channels. Irrigation and Drainage, 72(4), 1124-1136.

Shahverdi, K., & Maestre, J. M. (2022). Gray wolf optimization for scheduling irrigation water. Journal of Irrigation and Drainage Engineering, 148(7), 04022020.

Shahverdi, K, Ghodousi, H, & Dosti, F. (2024). Effect of on time and late operation of canal structures for equitable and sustainable water distribution. Iranian Journal of Soil and Water Research, 55 (3), 467-481. (In Persian)

Shin, J. H., Nam, W. H., Jeon, M. G., Hong, E. M., Zhang, X., Sharma, V., ... & Kisekka, I. (2024). Assessing water distribution and efficiency by coupled hydraulic-hydrological modeling for irrigation canal network. Paddy and Water Environment, 1-14.

Tavana, A. H. (2024). Application of Inverse Reinforcement Learning Method in Irrigation Networks (Case Study: Dez Irrigation Network). Master dissertation, Zanjan University, Zanjan, Iran.

Zhou, K., Fan, Y., Gao, Z., Chen, H., & Kang, Y. (2024). Research progress on operation control and optimal scheduling of irrigation canal systems. Irrigation and Drainage.