Shapes classification of dust deposition using fuzzy kernel-based approaches

被引：24

作者：

Proietti, Andrea ^{[1
]}

Liparulo, Luca ^{[1
]}

Leccese, Fabio ^{[2
]}

Panella, Massimo ^{[1
]}

机构：

[1] Univ Roma La Sapienza, Dept Informat Engn Elect & Telecommun, I-00184 Rome, Italy

[2] Univ Rome Tre, Dept Sci, I-00146 Rome, Italy

来源：

MEASUREMENT | 2016年 / 77卷

关键词：

Dust; Shape analysis; Classification; Fuzzy; Membership functions; ALGORITHM; IDENTIFICATION; SYSTEMS;

D O I：

10.1016/j.measurement.2015.09.025

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Dust deposition and pollution are relevant issues in indoor environments, especially concerning human health and conservation of things and works. In this framework, several tools have been proposed in the last years in order to analyze dust deposition and extract useful information for addressing the phenomenon. In this paper, a novel approach for dust analysis and classification is proposed, employing machine learning and fuzzy logic to set up a simple and actual tool. The proposed approach is tested and compared with other already introduced similar techniques, in order to evaluate its performance. (C) 2015 Elsevier Ltd. All rights reserved.

引用

页码：344 / 350

页数：7

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