基于自适应网络的模糊推理系统估算楼梯踏面宽度,以满足人们的舒适和安全需求

IF 1.6 0 ARCHITECTURE
Fadime Diker, M. Arslan, Ilker Erkan
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引用次数: 0

摘要

本研究旨在建立一个基于自适应网络的模糊推理系统(ANFIS)模型,该模型可以根据人的身体特征估计出适合舒适性和安全性需求的胎面宽度值。输入值是通过测量200人样本组的身高、步长和鞋底长度获得的。为了将踏面宽度值作为输出值,我们使用了一个可以体验不同步长的原型楼梯模型。利用所建立的ANFIS模型中测试数据得到的胎面宽度值与实验研究得到的胎面宽度值进行了比较。结果表明,通过比较建立的ANFIS模型可以作为估算楼梯踏面宽度值的有效工具,能够满足人们的身体舒适度需求。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Estimating tread width values for stair design appropriated to people’s comfort and safety needs with adaptive network-based fuzzy inference system
In this study, it is aimed to develop an adaptive network-based fuzzy inference system (ANFIS) model that can estimate tread width values based on the physical characteristics of people and suitable for comfort and safety needs. The input values were obtained by measuring the height, step, and shoe sole lengths of the sample group of 200 people. For the tread width value to be used as output value, a prototype stair model in which different step sizes can be experienced was used. The tread width value obtained by using the test data in the developed ANFIS model was compared with the tread width value obtained from the experimental study. It has been concluded that the ANFIS model developed as a result of the comparison can be used as an efficient tool in estimating the value of stair tread width, which can meet people’s physical comfort needs.
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来源期刊
CiteScore
3.20
自引率
17.60%
发文量
44
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