| With the scale of inter-regional agricultural operations continue to expand,the number of agricultural machinery is also not increase.Artificial agricultural machinery monitoring and dispatching has been unable to adapt to the development trend of agricultural machinery at this time,resulting in low efficiency of agricultural operations,uneven distribution of agricultural machinery,information is not timely and unreasonable planning routes and so on.In the continuous development of information today,foreign developed countries to develop agricultural machinery intelligent control scheduling earlier,in the agricultural machinery assembly GPS positioning,to achieve the automatic driving machine functions,such as precision planting,fertilization and harvesting.From the beginning of the 1990 s,with the continuous development of China’s Internet and GPRS communication network,the coverage has been expanding,and the Internet technology and GPS positioning technology have matured,and provide technical guarantee for solving the modern intelligent agricultural control.The era of information big bang has arrived.Agricultural information has become an important field of development in China,many scholars have already carried out in-depth study on intelligent agricultural monitoring and scheduling,genetic algorithm used to calculate the optimal path of the vehicle has been a lot of research,and very mature,based on this algorithm for agricultural The research of dispatching system is also innovating.In this context,this paper has carried on the research on the agricultural machinery monitoring and dispatching system and the genetic algorithm,and has obtained the following achievements: improving the genetic algorithm to verify its improvement effect,monitoring the development and application of the dispatching system and correcting the accuracy of its monitoring.The main contents of this paper are as follows:(1)Genetic algorithm improvement and application.This paper studies scheduling strategy in detail,sets the constraint condition,establishes the objective function,briefly introduces the concept and operation process of the genetic algorithm.Because the algorithm itself has both advantages and disadvantages,the advantages and disadvantages of the algorithm are analyzed,the algorithm is improved,The advantages of eliminating the defects of the algorithm are improved by comparing the traditional genetic algorithms before the improved analysis.Design a multi-regional,multi-farm machine-based route planning based on time windows,so as to minimize the cost of scheduling of agricultural machinery within the time stipulated to complete the task.In the system of the monitoring side of the collection of the collection of scheduling factors,through the algorithm automatically calculated by the algorithm to determine the optimal scheduling results,generate scheduling instructions,through the Internet or GPRS communication network transmission to the vehicle side of the hand.(2)In the system development based on WebGIS,the system structure is analyzed.The system is divided into the vehicle side and the monitoring side.Each farm machine is equipped with a smart phone as the hardware support of the vehicle terminal.The monitoring side is based on the enterprise management system developed by the Web browser.Baidu Map is used as the system network map design The Analysis of demand,according to demand,research and development of major system functions,such as the collection of agricultural operations status information,machine information management,agricultural information management,location monitoring,scheduling decision generation and path playback.All functions are based on the realization of the GPS coordinates of the acquisition,the experimental vehicle-side hardware support to choose smart phones.Finally,the overall system test and display.(3)due to the existence of GPS positioning error,the use of large data to accurately analyze the measurement of agricultural workload and actual value of the error range,analysis of error and the linear relationship between the workload to make up for the error. |
