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Canal Structure Automation Rules Using An Accuracy-Based Learning Classifier System, A Genetic Algorithm, And A Hydraulic Simulation Model. I: Design, J. E. Hernandez, G. P. Merkley
Canal Structure Automation Rules Using An Accuracy-Based Learning Classifier System, A Genetic Algorithm, And A Hydraulic Simulation Model. I: Design, J. E. Hernandez, G. P. Merkley
Jairo E. Hernández
Using state-of-the-art computational techniques, a genetic algorithm (GA) and an accuracy-based learning classifier system (XCS) were shown to produce optimal operational solutions for gate structures in irrigation canals. An XCS successfully developed a set of operational rules for canal gates through the exploration and exploitation of rules using a GA, with the support of an unsteady-state hydraulic simulation model. A computer program which implemented the XCS was used to develop operational rules to operate all canal gate structures simultaneously, while maintaining water depth near target values during variable-demand periods, and with a hydraulically stabilized system when demands no longer changed. …
Canal Structure Automation Rules Using An Accuracy-Based Learning Classifier System, A Genetic Algorithm, And A Hydraulic Simulation Model. Ii: Results, J. E. Hernández, G. P. Merkley
Canal Structure Automation Rules Using An Accuracy-Based Learning Classifier System, A Genetic Algorithm, And A Hydraulic Simulation Model. Ii: Results, J. E. Hernández, G. P. Merkley
Jairo E. Hernández
An accuracy-based learning classifier system (XCS), as described in a companion paper (Part I: Design), was developed and evaluated to produce operational rules for canal gate structures. The XCS was applied together with a genetic algorithm and an unsteady hydraulic simulation model, which was used to predict responses to gate operation rules. In the tested cases, from 100 to 2,000 XCS simulations, each involving thousands of hydraulic simulations, were required to produce satisfactory rules. However, the overall fitness of the set of rules increased monotonically as XCS simulations progressed. Initial fitness started at an arbitrary value, and rules increased in …