کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4443173 1311181 2008 12 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Comparison of two cluster analysis methods using single particle mass spectra
موضوعات مرتبط
مهندسی و علوم پایه علوم زمین و سیارات علم هواشناسی
پیش نمایش صفحه اول مقاله
Comparison of two cluster analysis methods using single particle mass spectra
چکیده انگلیسی

Cluster analysis of aerosol time-of-flight mass spectrometry (ATOFMS) data has been an effective tool for the identification of possible sources of ambient aerosols. In this study, the clustering results of two typical methods, adaptive resonance theory-based neural networks-2a (ART-2a) and density-based clustering of application with noise (DBSCAN), on ATOFMS data were investigated by employing a set of benchmark ATOFMS data. The advantages and disadvantages of these two methods are discussed and some feasible remedies proposed for problems encountered in the clustering process. The results of this study will provide promising directions for future work on ambient aerosol cluster analysis, suggesting a more effective and feasible clustering strategy based on the integration of ART-2a and DBSCAN.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Atmospheric Environment - Volume 42, Issue 5, February 2008, Pages 881–892
نویسندگان
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