According to the characteristics of green construction, this paper defines the key indexes in green construction assessment system which includes resources utilization, environmental protection and construction management. It also builds up green construction assessment model in which relationships among indexes are established. Back Propagation Neural Network (BPNN) optimized by genetic algorithm (GA) is used to assess green construction alternatives. And a case study has been conducted in order to verify the adaptability of the model.
Most environmental problems of buildings emerge during the construction phase of a project. Although the duration of the construction phase is a short part in the project lifecycle, the impact on the surrounding environment is paroxysmal. Moreover, the consumption of global resources and energy is mass. Therefore, green construction alternatives need to be applied in order to reduce the environmental problems and resources consumption to achieve the goal of sustainable development. In addition, complicated green construction alternatives need to be analyzed considering both the social and the economic benefit. The main objective of this paper is to introduce the value engineering theory and the improved AHP method to assess the green construction alternatives. Firstly, a set of indicators for comprehensive assessment system is created. Secondly, the improved AHP method is used to determine the weight for different indicators. Finally, the authors put forward an assessment model of construction alternatives by means of value engineering. .
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