Method for modeling neural network of optimum working parameters of intelligent road roller

The invention discloses a method for modeling a neural network of optimum working parameters of an intelligent road roller. The method is characterized by comprising the following steps of: firstly, by aiming at different compaction materials, performing compaction operation by the road roller at different working parameters, and thus obtaining a corresponding compaction effect in real time; secondly, finding a group of working parameters, which correspond to an expected compaction effect, of the road roller; and finally, training to obtain a neural network model which is used for providing working parameters such as optimum vibration efficiency, amplitude and driving speed, achieving the expected compaction effect, of the intelligent road roller. The method has the advantages that: after the water content, maximum dry density, grain composition and an expected target compaction value of the current compaction material are input, a group of optimum working parameters can be quickly and accurately obtained, and the expected compaction effect is achieved.