Online recognition and inhibition method based on non-target interference smell in electronic nose of artificial intelligent learning machine
A technology of artificial intelligence and identification method, which is applied in the field of online identification and suppression of non-target interfering odors, and can solve the problems of wrong prediction of target gas concentration, false alarms of electronic nose detectors, and inability to suppress non-target interfering odors.
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[0070] The indoor target pollution gases involved in the present invention include six types: formaldehyde, benzene, toluene, carbon monoxide, nitrogen dioxide and ammonia. The common sources of interference odors indoors are alcohol, perfume, toilet water and fruit aromas (oranges, oranges). ). In the atmospheric environment, there may be numerous interference sources. It can be understood that all non-target odors except the target gas are interference odors, so it is impossible to obtain each interference odor mode. Therefore, the present invention only needs to set the mode invariant, that is, all modes except the target gas mode are regarded as interference.
[0071] In addition, in the embodiment, the artificial intelligence learning machine of the present invention adopts a multilayer perceptron neural network method. Similarly, professional and technical personnel can also use self-organizing neural networks, support vector machines, linear / non-linear decision analysis, ...
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