基于改进鲸鱼算法的地理空间数据可视化提取系统设计

Geospatial Data Visual Extraction System Based on Improved Whale Algorithm

数据规模的不断扩大,导致地理空间数据提取在安全性与连续性方面存在一定缺陷,提出基于改进鲸鱼算法的地理空间数据可视化提取系统。利用自组织神经网络模型,经过细致的权值调整,实现数据降维预处理;将鲸鱼算法分为觅食、缩小包围、捕食三个过程,确定每个过程的数学模型,再增加变异、交叉等操作,改进该算法性能;结合算法特点,从客户端、逻辑端与服务器端三方面设置系统模式,完成数据获取、格式转变、数据排序与可视化提取。仿真实验表明,该系统的可视化提取的长宽比性能较好,数据的连续性与安全性得到保障。

With the continuous expansion of data scale, there are some defects in the security and continuity of geospatial data extraction.This paper proposes a visualization extraction system of geospatial data based on improved whale algorithm. Using the self-organizing neural network model, after careful weight adjustment, the data dimension reduction preprocessing is realized;the whale algorithm is divided into three processes: foraging, shrinking encirclement and predation, the mathematical model of each process is determined, and then mutation, crossover and other operations are added to improve the performance of the algorithm. Combined with the characteristics of the algorithm, the system mode is set from three aspects of client, logic and server to complete data acquisition, format transformation, data sorting and visual extraction. The simulation results show that the aspect ratio performance of the system is good, and the continuity and security of the data are guaranteed.