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    Development of Generalized Higher-Order Synaptic Neural–Based ETo Models for Different Agroecological Regions in India

    Source: Journal of Irrigation and Drainage Engineering:;2014:;Volume ( 140 ):;issue: 012
    Author:
    S. Adamala
    ,
    N. S. Raghuwanshi
    ,
    A. Mishra
    ,
    M. K. Tiwari
    DOI: 10.1061/(ASCE)IR.1943-4774.0000784
    Publisher: American Society of Civil Engineers
    Abstract: This paper aims at developing generalized higher-order synaptic neural (GHSN), i.e., generalized quadratic synaptic neural (GQSN) and generalized cubic synaptic neural (GCSN), reference evapotranspiration (
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      Development of Generalized Higher-Order Synaptic Neural–Based ETo Models for Different Agroecological Regions in India

    URI
    http://yetl.yabesh.ir/yetl1/handle/yetl/72125
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    • Journal of Irrigation and Drainage Engineering

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    contributor authorS. Adamala
    contributor authorN. S. Raghuwanshi
    contributor authorA. Mishra
    contributor authorM. K. Tiwari
    date accessioned2017-05-08T22:08:22Z
    date available2017-05-08T22:08:22Z
    date copyrightDecember 2014
    date issued2014
    identifier other32255213.pdf
    identifier urihttp://yetl.yabesh.ir/yetl/handle/yetl/72125
    description abstractThis paper aims at developing generalized higher-order synaptic neural (GHSN), i.e., generalized quadratic synaptic neural (GQSN) and generalized cubic synaptic neural (GCSN), reference evapotranspiration (
    publisherAmerican Society of Civil Engineers
    titleDevelopment of Generalized Higher-Order Synaptic Neural–Based ETo Models for Different Agroecological Regions in India
    typeJournal Paper
    journal volume140
    journal issue12
    journal titleJournal of Irrigation and Drainage Engineering
    identifier doi10.1061/(ASCE)IR.1943-4774.0000784
    treeJournal of Irrigation and Drainage Engineering:;2014:;Volume ( 140 ):;issue: 012
    contenttypeFulltext
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    DSpace software copyright © 2002-2015  DuraSpace
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