首页 | 本学科首页   官方微博 | 高级检索  
     

基于认知规律的用户界面信息布局设计方法
引用本文:姬文渊,吕健,刘翔,徐小萍,赵子健.基于认知规律的用户界面信息布局设计方法[J].计算机工程与设计,2020,41(5):1358-1366.
作者姓名:姬文渊  吕健  刘翔  徐小萍  赵子健
作者单位:贵州大学现代制造技术教育部重点实验室,贵州贵阳550025;贵州大学现代制造技术教育部重点实验室,贵州贵阳550025;贵州大学现代制造技术教育部重点实验室,贵州贵阳550025;贵州大学现代制造技术教育部重点实验室,贵州贵阳550025;贵州大学现代制造技术教育部重点实验室,贵州贵阳550025
基金项目:贵州省科技厅自然科学研究项目;国家自然科学基金
摘    要:为进一步提高工作效率,提出一种基于人的认知因素和几何位置匹配因素的界面信息布局设计方法。建立任务模型,获取合理的待布局任务信息元素;从人的认知规律中提取3个布局原则,分别将其以定量化的形式构建数学模型,以目标函数变量的形式作用于界面布局过程中;引入带有惯性权重的粒子群算法求解目标函数,对界面中所有待布局元素的几何位置寻求最优布局方案。以隧道应急救援培训系统的决策界面布局为例,提出解决方案并验证该方法的可行性。实验结果表明,该方法具有一定的实用性。

关 键 词:用户界面  认知规律  界面布局  任务模型  粒子群算法

Design method of interface task information layout based on cognitive law
JI Wen-yuan,LYU Jian,LIU Xiang,XU Xiao-ping,ZHAO Zi-jian.Design method of interface task information layout based on cognitive law[J].Computer Engineering and Design,2020,41(5):1358-1366.
Authors:JI Wen-yuan  LYU Jian  LIU Xiang  XU Xiao-ping  ZHAO Zi-jian
Affiliation:(Key Laboratory of Advanced Manufacturing Technology of Ministry of Education,Guizhou University,Guiyang 550025,China)
Abstract:To improve the work efficiency,a method of interface information layout design based on human cognitive factors and geometric position matching factors was proposed.A task model was established to obtain reasonable task information elements to be laid out.Three layout principles were extracted from human cognitive law,and the mathematical model was constructed in quantitative form,and the objective function variables were used in the process of interface layout design.Particle swarm optimization with inertia weight was introduced to solve the objective function and find the optimal layout scheme for the geometric position of the elements to be laid out in the interface.Taking the decision-making interface layout of tunnel emergency rescue trai-ning system as an example,the solution was proposed and the feasibility of the method was verified.The results show that the method is practical.
Keywords:user interface  cognitive rule  interface layout  task model  particle swarm optimization algorithm
本文献已被 维普 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号