Distributed principal component analysis neural network modeling method for chemical exothermic reaction
A neural network modeling and exothermic reaction technology, which is applied in the field of distributed principal element analysis neural network modeling of chemical exothermic reactions, and can solve problems such as the difficulty of modeling the catalytic rod object.
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[0070] The present invention will be further described below in conjunction with embodiments.
[0071] The catalytic rod is the object of the actual process.
[0072] Step 1. Collect real-time operating data of the catalytic rod process and establish a distributed parameter model of the catalytic rod object.
[0073] 1.1 to Spatio-temporal data input for the catalytic rod, The output data collected for the catalytic rod and the corresponding state variables of the catalytic rod Where t is the time series, L is the length of the time series, z i Is the spatial location of the collected output data of the i-th catalytic rod, and N is the total number of collected output data.
[0074] 1.2 The space-time variable X(z,t) in the catalytic rod can be obtained by Fourier transform:
[0075]
[0076] According to the actual situation, it can be converted into a limited space:
[0077]
[0078] among them Is an approximation of n times, Is the orthogonal basis function obtained by Fourier tr...
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