Hybrid PSO-ASVR-based method for data fitting in the calibration of infrared radiometer

Yang, Sen; Li, Chengwei

doi:10.1063/1.4953375

Cited by 3 publications

(5 citation statements)

References 27 publications

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“…In Equation ( 16), let Ω symbolize the rotation of the Earth. By considering various forces acting on the air parcel including the Coriolis force, gravitational force, frictional force, and pressure gradient, we can substitute Equations ( 11), ( 14)-( 16) into the right-hand side of Equation (12) to obtain the expression.…”

Section: Methods For Establishing Physical Models and Updating Air Unitsmentioning

confidence: 99%

“…The parameter u cur represents the current velocity value, indicating the velocity for the present iteration. Equation ( 21) is obtained by substituting the value of variable w into Equation (12).…”

Section: Methods For Establishing Physical Models and Updating Air Unitsmentioning

confidence: 99%

“…The particle swarm optimization (PSO) algorithm was developed by American academics to emulate the foraging behavior observed in birds and other animals [11][12][13]. In the wild, birds often demonstrate both interpersonal and group cooperation during foraging.…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

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Evaluation and Analysis of Heuristic Intelligent Optimization Algorithms for PSO, WDO, GWO and OOBO

Huang,

Xu,

et al. 2023

Mathematics

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In order to comprehensively evaluate and analyze the effectiveness of various heuristic intelligent optimization algorithms, this research employed particle swarm optimization, wind driven optimization, grey wolf optimization, and one-to-one-based optimizer as the basis. It applied 22 benchmark test functions to conduct a comparison and analysis of performance for these algorithms, considering descriptive statistics such as convergence speed, accuracy, and stability. Additionally, time and space complexity calculations were employed, alongside the nonparametric Friedman test, to further assess the algorithms. Furthermore, an investigation into the impact of control parameters on the algorithms’ output was conducted to compare and analyze the test results under different algorithms. The experimental findings demonstrate the efficacy of the aforementioned approaches in comprehensively analyzing and comparing the performance on different types of intelligent optimization algorithms. These results illustrate that algorithm performance can vary across different test functions. The one-to-one-based optimizer algorithm exhibited superior accuracy, stability, and relatively lower complexity.

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Section: Methods For Establishing Physical Models and Updating Air Unitsmentioning

confidence: 99%

Section: Methods For Establishing Physical Models and Updating Air Unitsmentioning

confidence: 99%

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Evaluation and Analysis of Heuristic Intelligent Optimization Algorithms for PSO, WDO, GWO and OOBO

Huang,

Xu,

et al. 2023

Mathematics

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“…Table 2 shows the model training time for different calibration methods. Here, the optional fitting methods are the least-squares (LS) method, the partial LS (PLS) method and the particle swarm optimization-adaptive preprocessingsupport vector regression (PSO-ASVR) method (Yang and Li, 2016). The data points used for modeling were 15, and the number of iterations in the PSO was 100.…”

Section: Analysis Of Computational Complexitymentioning

confidence: 99%

“…The quantitative calibration accuracy, which depends on the used fitting method, affects the accuracy of the assessment of the road conditions (Yang and Li, 2016). Generally, the quantitative calibration of an RCS is performed using one fixed data fitting method.…”

Section: Introductionmentioning

confidence: 99%

New method for the calibration of a road condition sensor

Yang

2022

Self Cite

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Purpose This study aims to improve the calibration accquracy of the road condition sensor. A road condition sensor is widely used to detect water or ice deposits on the road to assess associated driving risks. Its quantitative calibration is central to the thickness measurement accuracy and conventionally performed using the single fitting method-based calibration method. One existing limitation is that the distribution characteristics of calibration data of different road conditions are diversified, which leads to the fitting error can not be minimized when using the conventional calibration method. Thus, the multiple fitting methods-based calibration method is developed to realize an optimal calibration for the road condition sensor. Design/methodology/approach A fitting method assignment for the calibration data of different road conditions was introduced to realize an optimal combination for fitting method and calibration data. In the experiments, the calibration methods were tested in the absence of measurement errors, then tested with calibration data, and finally, in the covering thickness measurement. Findings The comparison results indicate that compared with the conventional calibration method, the multiple fitting methods-based calibration method cuts the fitting error in the quantitative calibration by 13.3% and contributes to reducing the thickness measurement error by 8.11% for different road conditions. Originality/value The multiple fitting methods-based calibration method has been successfully applied for quantitative calibration and shown to reduce calibration errors. The comparison between different calibration methods demonstrates the superior performance of the new calibration method.

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Notice of Removal: Investigation on Sound Absorbing Performance of the Polyester Fiber for Noise Reduction in Large-Scale Equipment

Bai¹,

Yang²,

Shen³

et al. 2017

2017 5th International Conference on Mechanical, Automotive and Materials Engineering (CMAME)

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Hybrid PSO-ASVR-based method for data fitting in the calibration of infrared radiometer

Cited by 3 publications

References 27 publications

Evaluation and Analysis of Heuristic Intelligent Optimization Algorithms for PSO, WDO, GWO and OOBO

Evaluation and Analysis of Heuristic Intelligent Optimization Algorithms for PSO, WDO, GWO and OOBO

New method for the calibration of a road condition sensor

Notice of Removal: Investigation on Sound Absorbing Performance of the Polyester Fiber for Noise Reduction in Large-Scale Equipment

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