2016•Crop ProtectionRequires access

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

Sahar Mansourian, Ebrahim Izadi Darbandi, Mohammad Hassan Rashed Mohassel, Mehdi Rastgoo, Homayoun Kanouni

Open publisher page 28 citations

Abstract

This record does not include an abstract. Use the full-text link above if available.

About this research paper

What this paper is about

An abstract is not available in the OpenAlex record for this paper.

Why it matters

OpenAlex reports 28 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

A contribution statement is not available in the OpenAlex record.

Method / approach

Method details are not available in the OpenAlex metadata.

Main findings

Findings are not separately available in the OpenAlex metadata.

Limitations

Limitations are not available in the OpenAlex metadata.

Applications

Application details are not available in the OpenAlex metadata.

Key concepts: Convolvulus, Galium, Weed, Biology, Agronomy, Noxious weed

Back to paper search Browse research topics Original source

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 — Research Paper | ScholarLens