Evidence map›Paper›PMID 32996095›Full record

ArticleEnvironmental science and pollution research international2021

Generalized gene expression programming models for estimating reference evapotranspiration through cross-station assessment and exogenous data supply.

Mohammad Hossein Kazemi, Abolfazl Majnooni-Heris, Ozgur Kisi, Jalal Shiri

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Article in Environmental science and pollution research international, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

4 authors.

Mohammad Hossein KazemiWater Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
Abolfazl Majnooni-HerisWater Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran.
Ozgur KisiCivil Engineering Department, Ilia State University, Tbilisi, Georgia.
Jalal ShiriWater Engineering Department, Faculty of Agriculture, University of Tabriz, Tabriz, Iran. j_shiri2005@yahoo.com.ORCID http://orcid.org/0000-0002-5726-7924

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Adopting methodologies utilizing exogenous data from ancillary stations for determining crop water requirement is a suitable approach to exempt local shortcomings due to the lack of meteorological data/stations. Meanwhile, soft computing techniques might be suitable tools to be used with such data management scenarios. The present paper aimed at evaluating the generalizability of the gene expression programming (GEP) technique for estimating reference evapotranspiration (ET

Indexed as

Crops, AgriculturalPlant TranspirationGene ExpressionIranTurkeyData managementData supplantingExtrapolationGeneralized models

Identifiers

PMID32996095

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.