With the increase of construction waste (CW) in China, construction contractors begin to pay attention to the on-site CW management. The first step of on-site CW management is to estimate the quantity of CW that the whole project may produce. The existing methods mainly rely on the qualitative judgment of the managers' experience, which is inaccurate. The paper presents that the quantity of CW produced in the residential projects is affected by many factors. Through literature research and field investigation, the paper concludes that the main factors are building area, structure type, construction management level, and so on. Considering the complex nonlinear relationship between the factors and the quantity of CW, the paper presents a modified BP neural network model based on particle swarm optimization (PSO) algorithm for estimating the quantity of CW of residential projects. The example of the data from 20 projects of Shanghai shows that this model has high estimation accuracy.
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