Reservoir level process smoothing method
A reservoir water level and smoothing technology, which is applied in image data processing, instruments, calculations, etc., can solve unsatisfactory problems, achieve the effects of saving construction management costs, improving calculation accuracy, and having versatility
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Embodiment 1
[0035] This embodiment is a method for smoothing the reservoir water level process. The idea of the method is as follows:
[0036] The original water level data collected by the reservoir is assumed to be a discrete random signal. Due to the existence of random interference, the process drawn by the random signal is mostly in the shape of a broken line, indicating that the sampling data has the characteristics of a non-stationary random process. In order to eliminate or weaken the influence of disturbance, the water level process data need to be smoothed. The principle of smoothing is not only to eliminate the interference components in the data, but also to keep the original basic shape of the water level process unchanged. The smoothing method uses the five-point cubic method and the moving average method, and its principle is as follows:
[0037] set 2 n +1 equidistant nodes X -n , X -n+1 ..., X -1 , X 0 , X 1 ,... X n-1 , X n The experimental data on the...
Embodiment 2
[0077]This embodiment is an improvement of the first embodiment, and it is about the parameters of the first embodiment K detailed description. The parameters described in this example K The value range of is 1.0~0.0. The water level process of the output smoothing process also follows the K The value tends to be gentler from large to small, according to the formula It can be seen that:
[0078] If take K =1.0, then the output smoothing result is the processing result of the five-point cubic smoothing method, and its process is closest to the original process shape; if K =0.0, the output smoothing process is the processing result of the moving average method, and the smoothness of the process is strong; if K =0.5, the smoothness of the output process is in the middle of the processing results of the five-point cubic smoothing method and the moving average method. In general, the smoothness of the output process after the sliding average method is stronger than that of ...
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