基于改进目标进化算法的城市园林GIS数据均衡化技术研究

Data Equalization Technology of Urban Landscape GIS Based on Improved Objective Evolutionary Algorithm

传统城市园林GIS数据均衡化处理技术忽略了对调整参数的全面寻优,导致部分数据仍存在不均衡问题。为此,提出基于改进目标进化算法的城市园林GIS数据均衡化技术。针对城市园林GIS数据,结合SMOTE算法与遗传算法,形成一种新的改进目标进化算法——GSA算法,对GIS数据完成二次采样,通过鸡群算法求解目标函数最优解,以此得到多个最优调整参数,使图像灰度分布更加均匀,实现城市园林GIS数据均衡化处理。实验结果表明,与传统技术相比,改进目标进化算法的GIS数据均衡化效果更好,证明该技术具有理想应用性能。

The traditional urban landscape GIS data equalization processing technology ignores the comprehensive optimization of the adjustment parameters,which leads to the imbalance of some data.Therefore,a data equalization technology of urban landscape GIS based on improved objective evolutionary algorithm was proposed.A new objective evolutionary algorithm——GSA algorithm was formed by combining SMOTE algorithm and genetic algorithm for urban landscape GIS data.The secondary sampling on GIS data was completed,and the optimal solution of the objective function was solved through chicken swarm algorithm to get more optimal adjustment of parameters,making the image gray scale distribution more uniform and realizing the city garden equalization processing of GIS data.The experimental results showed that compared with the traditional technique,the GIS data equalization effect of the proposed technique was better,which proved that the proposed technique had ideal application performance.