文献
J-GLOBAL ID:201802276281336873
整理番号:18A0329807
イランのクルディスタン地方の乾燥地ヒヨコマメおよび冬コムギ圃場の雑草個体群を予測するためのポテンシャル法としての人工神経回路網とロジスティック回帰の比較【Powered by NICT】
Comparison of artificial neural networks and logistic regression as potential methods for predicting weed populations on dryland chickpea and winter wheat fields of Kurdistan province, Iran
著者 (5件):
Mansourian Sahar
(Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran)
,
Darbandi Ebrahim Izadi
(Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran)
,
Rashed Mohassel Mohammad Hassan
(Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran)
,
Rastgoo Mehdi
(Department of Agronomy and Plant Breeding, Faculty of Agriculture, Ferdowsi University of Mashhad, Mashhad, Iran)
,
Kanouni Homayoun
(Agricultural Research, Education and Extension Organization (AREEO), Sanandaj, Iran)
資料名:
Crop Protection
(Crop Protection)
巻:
93
ページ:
43-51
発行年:
2017年
JST資料番号:
H0443A
ISSN:
0261-2194
資料種別:
逐次刊行物 (A)
記事区分:
原著論文
発行国:
オランダ (NLD)
言語:
英語 (EN)