2009
DOI: 10.1117/1.3081546
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Retrieve the evaporation duct height by least-squares support vector machine algorithm

Abstract: International audienc

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Cited by 13 publications
(5 citation statements)
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“…Zhang [10] employed a particle swarm optimization (PSO) algorithm to invert a range direction inhomogeneous SBD M-profile. Moreover, a large number of researchers have used machine learning methods in the application of atmospheric ducts and achieved excellent inversion results [11][12][13][14][15][16]. However, both GA, PSO, SVM, and MLP algorithms require repeatedly using parabolic equations of the atmospheric ducts, which is timeconsuming.…”
Section: Introductionmentioning
confidence: 99%
“…Zhang [10] employed a particle swarm optimization (PSO) algorithm to invert a range direction inhomogeneous SBD M-profile. Moreover, a large number of researchers have used machine learning methods in the application of atmospheric ducts and achieved excellent inversion results [11][12][13][14][15][16]. However, both GA, PSO, SVM, and MLP algorithms require repeatedly using parabolic equations of the atmospheric ducts, which is timeconsuming.…”
Section: Introductionmentioning
confidence: 99%
“…Currently, machine learning has been widely used in many research fields, including artificial intelligence, financial industry, network security and so on, which has a significant impact on social productivity and economy. For atmospheric duct, machine learning prediction method is a new technology for EDH prediction with high efficiency and accuracy, which possesses great application value and achieved some results [33][34][35][36][37]. However, these researchers mainly use support vector machine (SVM) and feedforward neural network.…”
Section: Introductionmentioning
confidence: 99%
“…Machine learning is a kind of algorithm for data analysis, which can quickly mine the correlation and hidden laws in a large number of data and be used for regression prediction or classification [24, 25]. At present, a large number of researchers have used machine learning methods on atmospheric ducts and achieved good results [26–30]. Among them, a support vector machine (SVM) is widely used.…”
Section: Introductionmentioning
confidence: 99%