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Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features

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Bibliographic Details
Published in:Applied Computational Intelligence and Soft Computing
Format: Online Article RSS Article
Published: 2026
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container_title Applied Computational Intelligence and Soft Computing
description
discipline_display Mathematics
discipline_facet Mathematics
format Online Article
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genre Journal Article
id rss_article:106662
institution FRELIP
journal_source_facet Applied Computational Intelligence and Soft Computing
last_indexed 2026-07-26T02:01:08.348Z
publishDate 2026
publishDateSort 2026
record_format rss_article
spellingShingle Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
Mathematics
General
Mathematics
sub_discipline_display General
sub_discipline_facet General
subject_display Mathematics
General
Mathematics
Mathematics
General
Mathematics
subject_facet Mathematics
General
Mathematics
title Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
title_auth Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
title_full Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
title_fullStr Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
title_full_unstemmed Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
title_short Hybrid Optimization of Wheat Yield Using Genetic Algorithms and Machine Learning With Phenotypic and Climatic Features
title_sort hybrid optimization of wheat yield using genetic algorithms and machine learning with phenotypic and climatic features
topic Mathematics
General
Mathematics
url https://www.hindawi.com/journals/acisc/2026/5473137/