A Machine Learning Study on Internal Force Characteristics of the Anti-Slide Pile Based on the DOFS-BOTDA Monitoring Technology.

Long-term monitoring of constructed anti-slide piles can help in understanding the processes by which anti-slide piles are subjected to the thrust of landslides. This paper examined the landslide control project of Badong No. 3 High School. The internal force of an anti-slide pile subjected to long-term action of landslide thrust was studied by Distributed Optical Fiber Sensing (DOFS) technology. The BP neural network was used for model training on the monitored strain values and the calculated bending moment values. The results show the following: (1) The monitoring results of the sensor fibers reflect the actual situation more accurately than steel rebar meters do and can locate the position of the sliding zone more accurately. (2) The bending moments distributed along the anti-slide pile have staged characteristics under the long-term action of landslide thrust. Three stages can be summarized according to the development trend of the bending moment values. These three stages can be divided into two change periods of landslide thrust. (3) The model produced by the BP neural network training can predict the bending moment values. In this paper, the sensing fibers monitoring over a long time interval provides a basis for long-term performance analysis of anti-slide piles and stability evaluation of landslides. Using the BP neural network for training relevant data can provide directions for future engineering monitoring. More novel methods can be devised and utilized that will be both accurate and convenient.

Water pollution and degradation in Pearl River Delta, South China.

The Pearl River Delta Economic Zone is the most dynamic economic area in South China. One of the major problems in the region is the sustainable utilization of the water resources. On the basis of analysis of the water environment status and pollution sources, it is suggested that domestic sewage is the primary cause of pollution. Two new concepts "degradation coefficient" and "degradation volume" of water resources, due to pollution, which may be used to assess macroscopically the carrying capacity of the water resources and sustainability of the water environment, are proposed by the authors. The results calculated indicate that the volumes of degraded water resources will be up to 204, 352, and 537 million m3 in 2002, 2010, and 2020. It is suggested that water for daily consumption and domestic sewage must be controlled more effectively and there should be cross-regional coordination in tackling problems of water environment.