Planning the temporary takeoff/landing site's location for a pesticide spraying helicopter based on an intelligent fusion algorithm.

Comput. Electron. Agric.(2023)

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Abstract
Planning the temporary takeoff/landing site's location (TTSL) is an essential task faced by helicopter spraying pesticide operations in the forest. However, neither a scientific theoretical model nor a planning method do exist to address this issue. In this study, a mathematical model for a helicopter's TTSL planning is constructed, and an intelligent fusion algorithm (IWOA-IACO-CLC) is proposed based on the improved whale optimization algorithm (IWOA), improved ant colony optimization (IACO) algorithm, and combinatorial logic classifier (CLC). The fusion algorithm first adds a memory function and Le ' vy flight disturbance strategy to the whale optimization algorithm, which is used to enhance the global search capability of TTSL. Subsequently, the movement strategy of IACO is modified to a lateral movement within the forest and longitudinal movement between forests to calculate the fitness of the IWOA. Finally, the CLC is used to control the feasible domain of TTSL based on the idea of penalty function. In this setting, five Chinese planted forests were employed for route planning experi-ments, and the dispatch route length, spraying route length, and extra coverage rate obtained by the intelligent fusion algorithm and the artificial empirical method were analyzed. The results reveal that the IWOA-IACO-CLC algorithm achieves the optimal solution, and the five planned TTSL are more reasonable than those obtained by the artificial empirical method. The dispatch route is shortened by 13.26%, 3.27%, 13.40, 39.67% and 30.47%, the spraying route is shortened by 1.94%, 0.22%, 0.47%, 0.91% and 0.28%, and the extra coverage rate is decreased by 29.15%, 24.92%, 14.63%, 25.99% and 8.24%, respectively. Furthermore, the proposed mathe-matical model and intelligent fusion algorithm achieve the TTSL planning, while the rational TTSL planning reduces the dispatch route length and the operation cost. This study provides a theoretical basis for the TTSL planning of aerial spray helicopters, as well as a technical reference for the realization of smart forestry.
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Key words
Helicopter,Spraying pesticide,Temporary takeoff/landing site’s location,The whale optimization algorithm,The ant colony optimization,Combinatorial logic classifier
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