Intelligent Diagnosis Research of Short-wave Receiving Antenna Based on Improved LSSVM
XIANG Yixue
CHEN Bin
LUO Yong
Abstract：For a long time,the short wave receiving antenna system has been lack of intelligent automatic monitoring technolo?gy and means,and it is difficult to realize real-time evaluation and early warning of the receiving effect of the equipment. In order to reduce the burden of the basic communication security personnel and provide reliable data support and technical support for the analysis and evaluation of the health condition of short wave receiving antennas and the maintenance and guarantee of the equip?ment,in this paper,a least squares support vector machine classifier based on fruit fly optimization algorithm is established,and the intelligent diagnosis of short wave receiving antenna is realized. To solve the sparseness of the least squares support vector ma?chines,considering the two aspects of the representative samples and the boundary samples,a LSSVM training algorithm based on KFCM clustering algorithm is proposed. The UCI experimental results show that this method takes advantages of KFCM clustering to extract samples with more abundant heuristic information and remove redundant information effectively,a classifier with better per?formance is achieved.
Keywords：intelligent diagnosiskernel fuzzy C-means clusteringleast square support vector machinefruit fly optimiza?tion algorithm
Publication Date：2019-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：7( 1331-1337 )