Electronic nose parameter synchronous optimization algorithm based on improved quantum particle swarm optimization algorithm

Abstract

The invention discloses an electronic nose parameter synchronous optimization algorithm based on an improved quantum particle swarm optimization algorithm. The method comprises performing wavelet transformation on obtained original electronic nose data; then performing weighting treatment of wavelet coefficients; through the improved quantum particle swarm optimization algorithm based on a novel local attractor computing manner, finding out a weighting coefficient corresponding to the highest electronic nose identifying rate, and classifier parameters to obtain a characteristic matrix of electronic nose signals; inputting the characteristic matrix into a classifier for mode identification. The electronic nose parameter synchronous optimization algorithm based on the improved quantum particle swarm optimization algorithm has the advantages of enhancing early-stage ergodicity and later-stage local optimizing capacity of particles, improving the capacity of quantum particle swarms in searching for global optimal values, and especially for wound infection detection, improving the identification rate of an electronic nose, thereby selecting appropriate treatment methods for doctors and providing beneficial guidance for promoting quick recovery of wounds.

Description

technical field [0001] The invention relates to the technical field of signal and information processing, in particular to an electronic nose parameter synchronization optimization algorithm based on an improved quantum particle swarm algorithm. Background technique [0002] An electronic nose is an electronic system that uses the response map of a gas sensor array to identify odors, and it can continuously and real-time monitor the odor status of a specific location within hours, days or even months. [0003] Medical electronic nose is a special electronic nose system, which can realize the diagnosis of disease or wound infection by detecting the gas exhaled by the patient or the gas in the head space of the wound. It has short response time, fast detection speed, low cost, simple and convenient operation, and has the advantages of artificial intelligence, so it has gained wide attention and application. [0004] The intelligent algorithm system of the electronic nose incl...

AI Technical Summary

Problems solved by technology

However, the standard quantum particle swarm still has the following problems: in the actual application of quantum particle swarm optimization, the standard quantum particle swarm cannot guarantee to find the global optimum in each run within a limited number of iterations; When the particle distribution is ergodic, all the particles are concentrated towards a certain position prematurely. In the later stage of the iteration, the particles that are already very close to the global optimal position will jump to a position far away from the global optimal position in the next iteration.

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