Research On Comprehensive Evaluation Of The Green Building Based On BP Neural Network

With the attention of the importance of environmental protection, green building industry begins to rise. Assessment standard for green building is a prerequisite for successful implementation of green building project, while the economic evaluation of the life cycle plays a very important role in green building assessment system. Economic evaluation directly affects the quality of green building, life cycle cost and strength and weakness of environmental benefits. Therefore, how to establish a scientific assessment system and evaluate green building with a reasonable appraising method becomes an urgently problem, which needs studying.Firstly, this thesis starts from green building assessment system and the concept of green building cost benefit. Then it expounds concisely about the the characteristics, the index analysis of green building cost-benefit, the content of green building assessment and related theories. Secondly, it analyses the principle and thought of establishing green building appraising index and something about its quantification. Then according to such principle and thought, it establishes a reasonable comprehensive evaluation index system and has successfully carried on the quantification to the evaluating indicator system. Thirdly, it designs BP neural network model according to the established index system and neural network’s characteristics and has passed the studying and test. Besides, it successfully presents a simulation to the established BP neural network by using MATLAB software. Fourthly, it gives a green evaluation to practical cases by using the established index system and BP neural network model. And the results of evaluation show that this building belongs to good grades in green level grades, so it maches with the actual situation of this building in the level of domestic green building. Finally, the thesis gives systematically summary to the whole work as well as prospect to the future research work, and also points out several main research directions for the future.