Name
Title | ||
|---|---|---|
Prediction of Land Suitability for Crop Cultivation Based on Soil and Environmental Characteristics Using Modified Recursive Feature Elimination Technique With Various Classifiers |
Abstract | ||
|---|---|---|
Crop cultivation prediction is an integral part of agriculture and is primarily based on factors such as soil, environmental features like rainfall and temperature, and the quantum of fertilizer used, particularly nitrogen and phosphorus. These factors, however, vary from region to region: consequently, farmers are unable to cultivate similar crops in every region. This is where machine learning (... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TCSS.2021.3074534 | IEEE Transactions on Computational Social Systems |
Keywords | DocType | Volume |
Agriculture,Radio frequency,Soil,Predictive models,Vegetation,Feature extraction,Support vector machines | Journal | 8 |
Issue | ISSN | Citations |
5 | 2329-924X | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| G. Mariammal | 1 | 0 | 0.34 |
| A. Suruliandi | 2 | 7 | 5.50 |
| S. P. Raja | 3 | 12 | 6.67 |
| Poongothai Elango | 4 | 0 | 1.01 |