(untitled) (Journal of Advances and Scholarly Researches in Allied Education, 2023)
The critical problem in the construction industry is that building projects are completed at costmuch higher than estimated project cost, hence it is essential to develop a cost prediction model thatimprison all factors affecting the project cost using regression analysis . Construction prices are alwaysprone to fluctuations, with a long-term pattern of increasing, making the pricing process a difficult task.Fluctuations in the cost of building materials have a significant impact on predicting the value of a projectand, as a result, on the project’s good conclusion. The price difference has an impact on projectexecution costs and, as a result, on the projects’ ability to be completed. Cement and steel priceprediction is taken as one objective of this research. For this, relevant resource data between 2015 and2020 was collected The price volatility of cement and other construction materials during the projectperiod is one of the primary elements affecting the construction industry’s performance. They arecompared in terms of performance cross the country. Multiple regression analysis, trend analysis, andartificial neural networks prediction approaches used in the construction sector are used to predict thematerial price. In this Paper also awareness regarding predication model for predication cost inconstruction industry also examine.