Comparing Fuzzy SARSA Learning and Ant Colony Optimization Algorithms in Water Delivery Scheduling under Water Shortage Conditions-Reference-Cited by-同舟云学术

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Comparing Fuzzy SARSA Learning and Ant Colony Optimization Algorithms in Water Delivery Scheduling under Water Shortage Conditions

Published:2020-09 Issue:9 Volume:146 Page:04020028
ISSN:0733-9437
Container-title:Journal of Irrigation and Drainage Engineering
language:en
Short-container-title:J. Irrig. Drain Eng.

Author:

Omidzade Fatemeh¹,Ghodousi Hesam²,Shahverdi Kazem³

Affiliation:

1. M.Sc. Student, Dept. of Water Engineering, Faculty of Agriculture, Univ. of Zanjan, Zanjan 45371-38791, Iran.

2. Assistant Professor, Dept. of Water Engineering, Faculty of Agriculture, Univ. of Zanjan, Zanjan 45371-38791, Iran (corresponding author).

3. Assistant Professor, Dept. of Water Science Engineering, Bu-Ali Sina Univ., Hamedan 65178-38695, Iran.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Agricultural and Biological Sciences (miscellaneous),Water Science and Technology,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29IR.1943-4774.0001496

Reference25 articles.

1. Canal Operations Planner. I: Maximizing Delivery Performance Ratio

2. Irrigation Scheduling Using Mixed-Integer Linear Programming

3. Genetic algorithms for the sequential irrigation scheduling problem

4. Test Cases for Canal Control Algorithms

5. Fuzzy Sarsa Learning and the proof of existence of its stationary points

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