Intelligent monitoring method for monitoring abnormal conditions of fire-fighting engineering
An abnormal state and intelligent monitoring technology, applied in data processing applications, instruments, complex mathematical operations, etc., can solve the problems of reducing the risk prediction accuracy of process abnormal state, model convergence speed, increasing model computing resource occupation, etc., to improve dynamic abnormality The effect of identifying, improving training speed, and simplifying the solution process
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[0040] Such as figure 1 As shown, the present embodiment provides an intelligent monitoring method for fire engineering abnormal state monitoring, which includes the following steps:
[0041] 1. Acquisition of dynamic data streams;
[0042] 2. Use the principal component analysis method PCA to perform cluster analysis on the existing historical experience data, and establish a multi-classifier model;
[0043] 3. Perform the least squares support vector machine algorithm LSSVM on the principal metadata factors to obtain the optimal decision function equation;
[0044] 4. Use different decision function equations of different principal metadata factors to process the collected dynamic data flow, and realize abnormal mode state recognition in the process.
[0045] In step 2, first analyze and extract the data distribution of different basic state modes, and use the principal component analysis method to convert the sample data with similar principal component characteristics in...
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