干旱区生态环境知识资源中心(Arid): Generalized Quadratic Synaptic Neural Networks for ETo Modeling

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DOI	10.1007/s40710-015-0066-6
	Generalized Quadratic Synaptic Neural Networks for ETo Modeling
	Adamala, Sirisha; Raghuwanshi, N. S.; Mishra, Ashok
通讯作者	Adamala, S
来源期刊	ENVIRONMENTAL PROCESSES-AN INTERNATIONAL JOURNAL
ISSN	2198-7491
EISSN	2198-7505
出版年	2015
卷号	2 期号:2 页码:309-329
英文摘要	This study aims at developing generalized quadratic synaptic neural (GQSN) based reference evapotranspiration (ETo) models corresponding to the Hargreaves (HG) method. The GQSN models were developed using pooled climate data from different locations under four agro-ecological regions (semi-arid, arid, sub-humid, and humid) in India. The inputs for the development of GQSN models include daily climate data of minimum and maximum air temperatures (T-min and T-max), extra terrestrial radiation (R-a) and altitude (alt) with different combinations, and the target consists of the FAO-56 Penman Monteith (FAO-56 PM) ETo. Comparisons of developed GQSN models with the generalized linear synaptic neural (GLSN) models were also made. Based on the comparisons, it is concluded that the GQSN and GLSN models performed better than the HG and calibrated HG (HG-C) methods. Comparison of GQSN and GLSN models, reveal that the GQSN models performed better than the GLSN models for all regions. Both GLSN and GQSN models with the inputs of T-min and T-max and R-a performed better compared to other combinations. Further, GLSN and GQSN models were applied to locations of model development and model testing to test the generalizing capability. The testing results suggest that the GQSN and GLSN models with the inputs of T-min, T-max and R-a have a good generalizing capability for all regions.
英文关键词	Neural networks Synaptic operation ANN generalization Evapotranspiration
类型	Article
语种	英语
开放获取类型	Bronze
收录类别	ESCI
WOS记录号	WOS:000429896200003
WOS关键词	REFERENCE EVAPOTRANSPIRATION ; TEMPERATURE ; ANN
WOS类目	Engineering, Environmental
WOS研究方向	Engineering
资源类型	期刊论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/331382
作者单位	[Adamala, Sirisha; Raghuwanshi, N. S.; Mishra, Ashok] Indian Inst Technol, Agr & Food Engn Dept, Kharagpur 721302, W Bengal, India
推荐引用方式 GB/T 7714	Adamala, Sirisha,Raghuwanshi, N. S.,Mishra, Ashok. Generalized Quadratic Synaptic Neural Networks for ETo Modeling[J],2015,2(2):309-329.
APA	Adamala, Sirisha,Raghuwanshi, N. S.,&Mishra, Ashok.(2015).Generalized Quadratic Synaptic Neural Networks for ETo Modeling.ENVIRONMENTAL PROCESSES-AN INTERNATIONAL JOURNAL,2(2),309-329.
MLA	Adamala, Sirisha,et al."Generalized Quadratic Synaptic Neural Networks for ETo Modeling".ENVIRONMENTAL PROCESSES-AN INTERNATIONAL JOURNAL 2.2(2015):309-329.