Kernel extreme learning machine-based virtual extension method for leaked gas monitoring concentration data
A technology of a nuclear extreme learning machine and an expansion method, which is applied in the field of virtual expansion of the concentration data of dangerous chemical gas leakage monitoring, can solve the problems of low work efficiency and large workload, and achieves improved work efficiency, increased number of monitoring points, The effect of expanding the monitoring area
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[0011] In order to make the object, technical solution and advantages of the present invention clearer, the present invention is described below through specific embodiments shown in the accompanying drawings. It should be understood, however, that these descriptions are exemplary only and are not intended to limit the scope of the present invention. Also, in the following description, descriptions of well-known structures and techniques are omitted to avoid unnecessarily obscuring the concept of the present invention.
[0012] like figure 1 As shown, this specific embodiment adopts the following technical scheme: its expansion method is: first select the monitored space area S 1 The location point coordinates Xs, Ys and concentration data are used as the training sample set; where the coordinate value is the input value of the network, and the concentration data is used as the network output value, so that the network is constructed and trained; and then extrapolated or inte...
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