On the Use of Data Driven and Fuzzy Techniques to Calculate the Wind Speed in Urban Canyons

M. Santamouris, C. Georgakis, A. Niachou
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引用次数: 1

Abstract

The present per presents the results of an extensive study aiming to develop and validate alternative data driven techniques able to estimate the wind speed in urban canyons. The use of deterministic techniques to calculate the wind speed in canyons present a low accuracy because of the high uncertainty of the input data and the incomplete description of the physical phenomena. (C. Georgakis et al., 2004) Extended experimental data collected from seven urban canyons have been used to create a data base of the main parameters that define the phenomenon. Using fuzzy clustering techniques, clusters of input-output data have been developed using as criteria the inertia and gravitational forces. For each cluster using statistical analysis, the more probable wind speed inside the canyon and the corresponding input values have been estimated. Thus, a reduced data space has been created. This reduced data space has been used to develop four data driven prediction models. The models are : a 3D graphical interpolation method, a tree based model as well as a linear regression model. Using the results of the graphical interpolation model, a fuzzy estimation model has been developed as well. All methods have been compared against the experimental data
数据驱动和模糊技术在城市峡谷风速计算中的应用
本文介绍了一项广泛研究的结果,旨在开发和验证能够估计城市峡谷风速的替代数据驱动技术。由于输入数据的不确定性和对物理现象的描述不完整,使用确定性技术计算峡谷风速的精度较低。(C. Georgakis et al., 2004)从七个城市峡谷收集的扩展实验数据已用于创建定义该现象的主要参数的数据库。利用模糊聚类技术,以惯性和重力为标准,建立了输入-输出数据的聚类。通过统计分析,估算出峡谷内最可能的风速和相应的输入值。因此,创建了一个简化的数据空间。这个简化的数据空间被用来开发四种数据驱动的预测模型。模型包括三维图形插值法、基于树的模型和线性回归模型。利用图形插值模型的结果,建立了模糊估计模型。所有方法都与实验数据进行了比较
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