| At present,the efficiency of operations for cleaning corn seeds in my country has not yet reached an ideal standard,and there are still remnants of unharvested plants that have been missed.Currently,manual seed processing is mainly used,which is low efficiency,complex and high cost.Therefore,it is increasingly important and urgent to study a method of emastioning that can optimize the operation path of scattered and distributed unemasoned plants,save time and cost,and promote the development of smart agriculture and modern agriculture.In this paper,the work environment in the field of corn seed production after two largescale mechanical clearing operations for motorcycles is taken as the basis of the problem,and the missing,unexplained parents of the woman are taken as the object of research.Using existing technologies,satellite positioning,image recognition,etc.Information about the geographical location of male plants is transformed into a multi-objective path planning problem.After the path planning process is performed by the fusion algorithm proposed in this study,the efficiency of tag clearing operations in corn cultivation is further improved.The main content and research findings of this article are as follows:(1)By aiming at the advantages of the positive response system of a traditional ant cluster algorithm,the efficiency of the iteration of the algorithm is improved.By targeting the advantages of neighborhood search capabilities of traditional simulated annealing algorithms,the solution field is expanded.It is added to each other’s strengths and combined in sequence,so the shortest route plan in the route planning process is more detailed,more options are chosen when choosing the shortest route,and the final optimal solution is more precise.(2)Based on Matlab software,the initial simulation and verification of the problem environment of corn seed production is performed,and the path planning is carried out using three commonly used traditional algorithms,fusion algorithms and traditional S-type operation.path planning method.By comparing and analyzing the shortest path,execution time and convergence ratio,and comparing it with the path length of the traditional S-shaped path planning method,the feasibility of using the path planning algorithm to solve this problem is verified,and the operation effect of the fusion algorithm is more in line with the work requirements.(3)Five control groups with different rates of deandrogenic activity were established and the control groups were treated using five methods and analysed separately.The path complexity of fusion algorithm is obviously reduced.The final result of fusion algorithm is better than the other three algorithms,and the iterative convergence rate is similar to the standard ant colony algorithm,and the number of times is relatively small.The effectiveness and feasibility of the fusion algorithm are verified.The fusion algorithm has higher processing efficiency,and the optimal solution obtained is more accurate,which significantly improves the path optimization problem of randomly distributed scattered missing emasculated plants,and improves the operational efficiency.This study proves that the proposed fusion algorithm is feasible,effective and reasonable for the path optimization of unemcastrated plants missed in the field of maize seed production,which provides further development for the promotion of smart agriculture. |
