Data-Driven Simulator: Redesign of Chickpea Harvester Reels

Conventional redesign methodologies applied on the grain harvester headers for mechanical harvesting of chickpeas cause its progress to not be as rapid and technological. This paper presents a hybrid modeling-optimization methodology design reels efficient chickpea harvesting. The five fabricated were tested in both real virtual modeling environments optimize operational parameters reel minimum losses. Harvesting losses data gathered from fields over ten years trials fed into fuzzy logic model, which turn was merged with simulated annealing develop simulator. To this end, used produce combinations diameter number bats, model until achieving loss. proposed predicts structure measured in-field evaluation, fits well previously established mathematical model. A significant improvement performance, 71% pod harvesting, validates benefits fuzzy-simulated approach headers.