Application of machine learning in cement price prediction through a web-based system
نویسندگان
چکیده
Cement is one of the most common building materials in construction industry. Simultaneously, its price fluctuation can affect success or failure project's performance. The study aimed to develop a web-based platform that uses machine learning algorithms on historical data cement prices, petrol diesel interest rate, and exchange rate predict future prices products. was developed using hypertext markup language (HTML), cascading style sheet (CSS), MySQL, preprocessor (PHP). For reliable model, python used train system. front end, back model were integrated with flask framework. A system block diagram designed show platform's interfaces. implementation led login page, home database analytics interface. In training make predictions, obtained an 80% fitted linear regression. able cement. rationale behind prediction shown by scatter plot revealed increases 250 naira biannually.
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ژورنال
عنوان ژورنال: International Journal of Power Electronics and Drive Systems
سال: 2022
ISSN: ['2722-2578', '2722-256X']
DOI: https://doi.org/10.11591/ijece.v12i5.pp5214-5225