Optimization of energy consumption of a green building using PSO-SVM algorithm

Abstract

In this paper, the new novel optimization algorithm on the energy consumption of the represented green building with novel material is represented. The introduced green building is 320 square meters and takes advantage of a novel lay-up of composite material with the common materials. For this purpose, the supporting vector machine is firstly proposed to classify the properties of the building based on the energy consumption with high accuracy. As a matter of fact, the hyperparameters are optimized using the Particle Swarm Optimization method (PSO). Energy consumption of the building with a common material is calculated based on a fixed price with 99.98% accuracy. In fact, the highest demand for consumption from the administrative and residential sectors is close to 40% will be optimized for the first time. Based on the represented novel model, the layers of the novel represented composite are optimized for decreasing electricity usage as well as biogas. The results show a significant reduction in the amount of green building energy consumption by 28% for electricity and 42.44% for biogas compared to the common building. Furthermore, the remarkable decreasing cost of the green building with composite material to a value of 50% with compare to the common building proves the need to invest obviously in the construction of green buildings and the use of renewable resources in the world.