Author
Harshini, N.
Agriculture Data Feature Extraction Using Sequential Pattern Mining and Random Forest (SPM-RF) Data Mining Method
Feature extraction assumes a critical part in analyzing agricultural datasets and acquiring experiences for decision-making. In this paper we propose a methodology that consolidates Sequential Pattern Mining (SPM) and Random Forest (RF) techniques for…
Crop Yield Prediction Using With the Simulated Annealing Convolutional Neural Networks (SACNNS) Optimization Algorithm
This paper introduces an innovative approach for precise crop yield prediction in Tamil Nadu, India, a region with diverse agricultural conditions. The Simulated Annealing Convolutional Neural Networks (SACNNs) optimization algorithm is employed to enhance…
Data Preprocessing Using Enhanced Principal Component Analysis (EPCA) for Agricultural Datasets
Data pre-processing is considered as the core stage in core and data mining. Standardization, discretization, and dimensionality decrease are notable strategies in data pre-processing. In this paper proposed Enhanced Principal component Analysis (EPCA) the…
A Review on Datamining in Agriculture
In this paper the makers present irrefutably the most used data mining strategies in the field of agriculture. A bit of these strategies, for example, the k-means, the k nearest neighbor, artificial neural networks…
A Survey on Datamining in Agriculture
Agriculture assumes an essential part in the life of an economy. It is the backbone for creating nations like India as over 70% of populace relies upon agriculture. To expand crop production numerous components…
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