Withdrawn

Abstract

Construction of housing with levels of popularity on energy saving is the most significant tasks. Lessening the thermal raise during the rooftop and divider boards is the most ideal advance to manage declining energy usage and to giving thermal help to the customers of private or business structures. Thermal insulation of buildings assumes a vital function in upgrading the comfort level of tenants by lessening the temperature of the building. In this investigation, we focused to reduce the thermal qualities in building by protecting polystyrene material in roof ceilings and wall panels. Here, we investigate the temperature among two climatic conditions i.e. summer and winter. The temperature is noted for 3 hours with 10 minutes interval for totally 40 specimens. Different types of specimens are used i.e. Reinforced Cement concrete (RCC) and Fiber Reinforced Concrete (FRC) specimens based on treated and untreated with insulating materials. The experimental results are validated by using training based Optimal Neural Network (ONN); here the ONN structure is trained with the help of Levenberg- Marquardt (LM) algorithm. The optimization predicted temperature for each specimen with Minimum Error Rate (MSE) compared to existing approaches.