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@article{178130,
        author = {R. Guganesh and Mr. M. Asan Nainar and Dr. A. Samydurai},
        title = {Prediction of seed price using Machine Learning},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {12},
        pages = {2867-2872},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=178130},
        abstract = {The mainstay of the economy has always been agriculture, and the majority of tasks are still carried out without the use of modern technology. Currently, the ability of human intelligence to forecasting future seed price is used. Because it lacks a validation method, the existing seed prediction analysis is ineffective. Here, I tried to create a prediction model that uses machine learning algorithm to forecast seed price and uses instead of provides tools and structures for efficient data management, front-end UI/UX development, and Back-end API creation using JavaScript and JSON file. While algorithms used in the individual components of the MERN stack. For precise seed categorization, this model was created using MERN stack and trained using the seed dataset. While testing data in the algorithm’s predictive analytics, training data and validation data are used in categorized reasons. Thus, by examining the training accuracy of the convolution neural network (CNN), MERN stack and the prediction accuracy of the algorithm, the project’s primary goal is to develop the best method for the more accurate prediction of future seed price.},
        keywords = {Agriculture - Data Pre-processing - Data Implementation - Convolution Neural Network (CNN) - MERN stack - Prediction - Seed Price},
        month = {May},
        }