InteliCrop: An Ensemble Model to Predict Crop using Machine Learning Algorithms Python IEEE Project
InteliCrop: An Ensemble Model to Predict Crop using Machine Learning Algorithms | Python IEEE Final Year Project 2023.
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📌Project Title: InteliCrop: An Ensemble Model to Predict Crop using Machine Learning Algorithms.
💡Implementation Code: Python.
🔬AAlgorithm / Model Used: Ensemble Model (VotingClassifier). Used three algorithm 1) Random Forest Classifier, 2) Logistic Regression, 3) Gradient Boosting Classifier.
🌐Web Framework: Flask.
🖥️Frontend: HTML, CSS, JavaScript.
💰Cost (In Indian Rupees): Rs.3000/.
IEEE Base paper Abstract:
The agricultural sector is the prime occupation of India. Researchers are developed various scientific technology in the agriculture field for better yield. In this paper, we try to form an ensemble model using various machine learning algorithms for better rice production. Crop production prediction utilizing AI Strategies aims to deliver improved outcomes, but the ensemble model provides better predictive results compared to the individual algorithm. We tried to use a combination of symmetric machine learning algorithms to form an ensemble model for better prediction. Here symmetric algorithms such as random forest, Gradient Boosting, and Logistic Regression are individually used for the prediction of the yield of rice. While combining all the aforesaid algorithms to form an ensemble model of ers a better result (99.54%).
REFERENCE:
Muppala Sunny Chowdhary, Jacob Jasper Roy Paga, Meera Gandhi, Sasmita S. Choudhury and SachiNandan Mohanty, “InteliCrop: An Ensemble Model to Predict Crop using Machine Learning Algorithms”, IEEE Conference, 2022.
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