Chan A H, Courtney A J
Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong.
Percept Mot Skills. 1998 Aug;87(1):251-60. doi: 10.2466/pms.1998.87.1.251.
A random search model was fit to a total of 2592 visual search times on a single-target detection task. By using a competing homogeneous background and uniform stimulus material, specifying viewing distance, controlling the presentation of search task material, and eliminating some options for extreme search strategies, very high correlation coefficients were found when a random search model was fit to both the individual data and to pooled data. A response time parameter was incorporated into the traditional random-search model and very good predictions of search performance were obtained.
一个随机搜索模型被用于拟合单目标检测任务中的总共2592次视觉搜索时间。通过使用具有竞争力的同质背景和均匀的刺激材料、指定观察距离、控制搜索任务材料的呈现以及消除一些极端搜索策略的选项，当随机搜索模型拟合个体数据和汇总数据时，发现了非常高的相关系数。一个反应时间参数被纳入传统的随机搜索模型中，并获得了对搜索性能的非常好的预测。
