On the public citation graph

Regression Based ICT Model for Crop Yield Estimation

https://doi.org/10.2139/ssrn.3349660
0 signed · 4 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.
Claim with ORCID
Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.
See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1109/icstm.2015.7225403openalex-extracted
Crop Selection Method to maximize crop yield rate using machine learning technique
inferredcites →https://doi.org/10.15623/ijret.2015.0401071openalex-extracted
ANALYSIS OF CROP YIELD PREDICTION USING DATA MINING TECHNIQUES
inferredcites →https://doi.org/10.17485/ijst/2016/v9i38/91714openalex-extracted
Prediction of Crop Yield using Regression Analysis

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1109/ic2e357697.2023.10262476openalex-snapshot
AGROFERDURE: Intelligent Crop Recommendation System For Agriculture Crop Productivity Using Machine Learning Algorithm
Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.