气候变化领域集成服务门户(CCPortal): Tools for enhancing the application of self-organizing maps in water resources research and engineering

CCPortal

DOI	10.1016/j.advwatres.2020.103676
	Tools for enhancing the application of self-organizing maps in water resources research and engineering
	Clark S.; Sisson S.A.; Sharma A.
发表日期	2020
ISSN	0309-1708
卷号	143
英文摘要	Environmental measurements generate great volumes of high-dimensional data (often noisy and with missing values) from which meaningful messages may be extracted through appropriate organisation and summarisation. The self-organizing map (SOM) is an artificial neural network popular for recognizing patterns, relationships and clusters in such data. Through the finetuning of configuration and training parameters, the SOM can be tailored to best suit a specific data set. Presently, most hydrologic applications continue to rely on heuristics, software defaults or arbitrarily chosen parameters, forfeiting some of the potential benefits of the method, and often resulting in an output that does not best represent the actual features of the data. This paper guides researchers through the knowledgeable creation and interpretation of an appropriately customised SOM relevant to their particular high-dimensional, nonlinear data set. An understanding of the effects that parameter selection and training options have on the extracted information is developed, practical guidance is given for appropriately modifying parameter sets, and comparisons are made with closely-related methods. Data pre-processing, parameter selection, initialisation, training, visualisation and interpretation of the output map for pattern extraction and clustering are discussed. Through individually customised SOMs, more meaningful information can be gained from data-driven exploratory analysis of the inter-component relationships involved in water resource systems. © 2020
关键词	Application programs Clustering algorithms Conformal mapping Data mining Heuristic methods Self organizing maps Environmental measurements Exploratory analysis High dimensional data Hydrologic applications Modifying parameters Parameter selection Training parameters Water resource systems Water resources
语种	英语
来源机构	Advances in Water Resources
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/131735
推荐引用方式 GB/T 7714	Clark S.,Sisson S.A.,Sharma A.. Tools for enhancing the application of self-organizing maps in water resources research and engineering[J]. Advances in Water Resources,2020,143.
APA	Clark S.,Sisson S.A.,&Sharma A..(2020).Tools for enhancing the application of self-organizing maps in water resources research and engineering.,143.
MLA	Clark S.,et al."Tools for enhancing the application of self-organizing maps in water resources research and engineering".143(2020).