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In this paper, we research the application of mechanical strength experiment on emulsified asphalt cement- stabilized macadam based on neural network algorithm. Basing on the analysis on the early diseases of asphalt pavement which uses semi-rigid base, solving the problem of semi-rigid base asphalt pavement's reflection crack, this paper pro- poses the research approach that using modified semi-rigid base, appropriate pavement structure as the point of starting. Combining with the past emulsified asphalt-cement stabilized macadam material mixing methods, the construction tech- nologies of cement stabilized macadam and synchronous chip sealing, this paper has come up a new method for modifica- tion semi-rigid base. The unconfined compressive strength and splitting strength of the mixtures would decrease as the mixing amount of emulsified asphalt increases, and the reduction rate of compressive strength decreases as the curing age grows. The mixing amount of emulsified asphalt has almost no influence on the flexural-tensile strength at normal tem- perature, so it can be ignored. The experimental result shows that the emulsified asphalt cement stabilized macadam has food performance than traditional methods.

Research on the Mechanical Strength of Emulsified Asphalt-Cementstabilized Macadam Based on Neural Network Algorithm