Intelligent Building Optimization Design Based on Artificial Neural Network with Tasmanian Devil Optimization

According to recent economic conditions, construction industry is experiencing a major shift and raising to intelligent building model. Thus, the incorporation of analyzing construction industry requirements as well as introduced a development mode for construction model. However, the building model constructed based on the needs consumes more energy and less effective. To overcome this limitation, an Artificial Neural Network with Tasmanian Devil Optimization (ANN-TDO) algorithm is proposed to predict and evaluate the intelligent building optimization design. The combination of ANN and TDO provide accurate energy demand predictions, and optimize the system based on those predictions, leading to more effective and adaptive energy-saving solutions. Initially, the data are considered the properties of building like energy consumption, temperature, weather condition and so on. Then, a building model is designed using wireless sensor network and those parameters fed to proposed business model. The experimental results of proposed method achieved accuracy of 95.8% which is higher than the existing methods such as Non-Sorted Adaptive Genetic Algorithm-III (NSGA-III).