Synchronous Optimization Method of Electronic Nose Parameters Based on Improved Quantum Particle Swarm Optimization Algorithm

Abstract

The invention discloses an electronic nose parameter synchronization optimization method based on an improved quantum particle swarm algorithm. First, the acquired original electronic nose data is subjected to wavelet transformation, then the wavelet coefficients are weighted, and then a calculation method based on a novel local attractor is adopted. An improved quantum particle swarm algorithm based on Quantum Particle Swarm Algorithm, finds the corresponding weighting coefficient and classifier parameters when the pattern recognition rate of the electronic nose is at its highest, so as to obtain the characteristic matrix of the electronic nose signal, and then input the obtained characteristic matrix into the classifier for pattern recognition. The beneficial effects are as follows: the ergodicity of the particles in the early stage and the local optimization ability in the later stage are increased, the ability of the quantum particle swarm to find the global optimal value is improved, and especially for wound infection detection, the recognition rate of the electronic nose is improved, so as to provide medical services for doctors. The selection of appropriate treatment methods to promote rapid wound recovery provides useful guidance.

Description

technical field [0001] The invention relates to the technical field of signal and information processing, in particular to an electronic nose parameter synchronous optimization method 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 includes fe...

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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