Study On The Application Of Quantum Genetic Algorithm In Broadcast Television Monitoring

Broadcast Television monitoring, an important and indispensable part of ChinaBroadcast Television career, provides scientific evidence for the improvement of thetransmission of radio and television and broadcast quality, verification of radio and TVcoverage effect and the development and modification of the coverage network planning, andplays a very important role in the order maintenance of the aerial radio wave of radio andtelevision, the strict protection and effective utilization of spectrum resources and thehigh-quality listening effect of the public. This paper mainly studies on the effect of chaoticneural network in the complicated optimizing problems with the method of quantum geneticalgorithm to cope with the selection speed and accuracy problems of optimal coveragetransmitter in the simulation process of coverage of medium wave and shortwave radio.At first, this article introduces the professional knowledge of monitoring work of radioand TV and radio propagation, analyzes the research of chaotic neural network at home andabroad and the application direction in radio and TV monitoring, and then shows the theorybasis, characteristics and deficiency of quantum genetic algorithm. For the coverage problemsof medium wave and shortwave radio and traditional quantum genetic algorithm, the authorputs forward three improved ways: adjusting gene initialization dynamically, keeping optimalresults and introducing part population catastrophe mechanism. Finally, the author designs thetransmitter procedure of coverage selection of medium wave and short wave based onquantum genetic algorithm, makes the comparison test and analyses the experimental results.Through the comparative analysis of the improved fore-and-aft quantum geneticalgorithm, the experimental results show that using the improved quantum genetic algorithmas the core algorithm in the speed and effects of optimization has obvious advantages in theprocess of transmitter selection of medium wave and shortwave radio coverage. TheImproved quantum genetic algorithm has better balance in both research effect and speedwhen solving com-binatorial optimization problems. The research and implementationimprove the performance of traditional quantum genetic algorithm and broaden theapplication field. The experimental results show that the improved quantum genetic algorithmis superior to the traditional, with faster convergence speed, very strong power divorced from the local extreme points, the global optimization capability to avoid premature convergence,higher search ability of optimization and usability.