## 1 Introduction
The sound power level of each sub-sound source is given by an empirical formula based on the differences in train operating speed and track type. The Chinese model proposed two prediction models based on different acoustic parameters according to the train running speed but did not provide a method of determining the reference source intensity at speeds below 200 km/h or above 350 km/h. Research on the environmental noise prediction of high-speed railways is of great significance for proposing and improving environmental noise prediction models for high-speed Maglev trains. In 2012, the Federal Railroad Administration of the UnitedStates Department of Transportation revised the environmental noise prediction model for high-speed Maglev trains, which was similar to the railway noise prediction model. This prediction method is relatively mature and has high operability [10]. The research object of this prediction model is a TR08 Maglev train, which has a maximum operating speed of 480 km/h. The basic physical quantity of noise evaluation adopted by the American model is the SEL [13], and the reference position is 15.2 m from the centerline of the track. The environmental noise prediction model of high-speed Maglev trains proposed by the United States of America does not require any real vehicle test data, and the calculation process and physical meaning are clear. However, some limitations exist: this model does not consider the air absorption attenuation, and the sound barrier attenuation does not consider the noise frequency characteristics. As the number of commercial high-speed Maglev trains worldwide is very limited, few studies have been conducted on their environmental noise prediction models. Therefore, in this study, the existing environmental noise prediction models [14,15] of high-speed Maglev trains and high-speed wheel-rail trains in various countries are combined using sound radiation theory, numerical simulation of the flow field, and real train online test data. An environmental noise prediction model is established; it can quickly predict the equivalent continuous SPL at different noise monitoring points outside the train when a Maglev train passes, predict and evaluate the impact of a high-speed Maglev train on the environment through noise before the construction of the line, enable these impacts to be treated and prevented in advance, and enable noise pollution to be avoided after the completion of the track line, affecting the ecology and living conditions in the area. Considering the model development and validation procedure that constitute the central focus of this study, the remainder of the paper is organized as follows: Section 2 describes the noise source distribution of high-speed Maglev trains, details the noise time-domain characteristics and noise source distribution, and determines the five-part line source. In Section 3, the model and parameters of the noise source are constructed, and the intensity of the noise source at other speeds is fitted using the measured data. In Section 4, the validity of the model is verified by comparing the measured and predicted time-domain curves and equivalent continuous A-weighted sound level. Finally, Section 5 provides the conclusions of this study.