AN EFFICIENT FEATURE SELECTION AND CLASSIFICATION FOR THE CROP FIELD IDENTIFICATION: A HYBRIDIZED WRAPPER BASED APPROACH
Main Article Content
Abstract
Agricultural stakeholders are concerned about the anticipated crop production
before the harvest. Many countries throughout the world employ computational technique's
for predicting yield ahead of harvest to assess a country's food security and issue warnings
about impending food shortages. This is a common method that aids strategy planners and
decision-makers, particularly in rural economies. Crop statistical models have been used to
track crop development and forecast production. The only inputs available at the field level
will yield a prediction for a narrow region; remote sensing observations cover a broad area.
They may be repeated at regular intervals, allowing for large-scale crop modelling. Crop
yield prediction study necessitates a variety of production parameters and algorithms. Some
algorithms are used to determine the optimum feature subset for improved prediction, while
others are used to determine prediction. The proposed Correlation based Sequential Forward
Feature Selection (CSFFS) is compared with the existing feature selection approaches. The
classification with proposed feature selection attains effective accuracy in crop prediction.
Downloads
Metrics
Article Details
Licensing
TURCOMAT publishes articles under the Creative Commons Attribution 4.0 International License (CC BY 4.0). This licensing allows for any use of the work, provided the original author(s) and source are credited, thereby facilitating the free exchange and use of research for the advancement of knowledge.
Detailed Licensing Terms
Attribution (BY): Users must give appropriate credit, provide a link to the license, and indicate if changes were made. Users may do so in any reasonable manner, but not in any way that suggests the licensor endorses them or their use.
No Additional Restrictions: Users may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.