Abstract. In order to measure the weight of yak more conveniently and effectively, based on BP neural network, this paper provides a portable dynamic weighing System for yak. The wireless transmission mode is adopted between the acquisition module and the instrument in this system and weighing platform is added a handle and a small roller table, which overcome the shortcomings of traditional weighing station that cannot move. In order to further improve the problem of traditional weighing station's low accuracy, using the smoothing mean filter to denoise the original data and according to the output of the shear beam type weighing sensor and the speed of yak, the BP neural model is established, thus the static weight of yak being obtained. By many experiments in matlab, the results show that this system achieves the measurement accuracy of dynamic weighing system and ensures that it can be achieved technically, which has good practical value.

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Abstract-Key areas risk forecasting plays an important roles in safety management in high-speed railway transport hub. In this paper, a temporal-based risk forecasting approach was considered for key areas on surveillance sensor networks. Computational experiments on a specific key area in high-speed railway transport hub were conducted to illustrate the proposed approach. The results showed the temporal-based forecasting approach is effective and efficient for key areas risk forecasting in high-speed railway transport hub.

Based on the current situation of passenger flow in Guangzhou Metro, this paper summarizes the shortcomings and possible risks of passenger transport organization. And after analyzing the current main methods of monitoring crowd density, and the crowd density detection algorithm in video surveillance and subsequent video processing, this paper proposes a crowd density classification method based on frame difference method with its application direction, which optimizes the existing subway station crowd control measures as well as helps subway station operators accurately identify the stage of crowd density in real time and take crowd control measures in time.