Improve Spatiotemporal Kriging with Magnitude and Direction Information in Variogram Construction

Chen, Dingxin; Liu, Daizhi; Li, Yihong; Meng, Liang; Yang, Xiaojun

doi:10.1049/cje.2016.05.019

Cited by 6 publications

(3 citation statements)

References 21 publications

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“…Based on Equation (20), the polynomial function is adopted for the armature stroke, l, ΔG and f(x1, x2…xq). This function is written as follows: ( , ... ) ( , ... )…”

Section: δG P P X P Y P X P Xymentioning

confidence: 99%

“…With the increasing levels of computational technology and theoretical analysis for the DPM, the kriging model, whose inputs affect its outputs, plays an important role in engineering design and error correction [16][17][18][19][20][21]. The calculation accuracy of air leakage permeance and the soft magnetic resistance has an effect on the electromagnetic force calculation accuracy of solenoid valves.…”

Section: Introductionmentioning

confidence: 99%

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Improved Method for Distributed Parameter Model of Solenoid Valve Based on Kriging Basis Function Predictive Identification Program

et al. 2021

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In this paper, a method for the improvement of the calculation accuracy of the distributed parameter model (DPM) of electromagnetic devices is proposed based on the kriging basis function predictive identification program (PIP). Kriging is mainly an optimal interpolation method which uses spatial self-covariance, and takes a polynomial as the basis function. The accuracy of the kriging-based surrogate model can be improved by adjusting the related functions and hyperparameters. Based on the DPM of a solenoid valve, there exist certain errors in the estimation. They can be summarized as follows: Firstly, the estimation error of magnetic flux leakage (MFL) permeance is caused directly by the deviation of the magnetic flux tube due to the segmented magnetic field line. Secondly, the estimation error of soft magnetic resistance because of the nonlinearity of the permeability of soft magnetic material leads to the change of soft magnetic resistance alongside the magnetic flux. In this paper, an improved kriging error correction method is applied to modify the leak permeance and soft magnetic resistance calculation. The kriging basis function is adjusted to adapt to the data curve of the MFL permeance error data. The calculated MFL permeance data are compared with the error variation data to select the appropriate basis function. To improve the computational efficiency, the PIP is proposed to select the appropriate basis function. The modified MFL permeance data and soft magnetic resistance are substituted into the DPM for improving the computational accuracy and efficiency of the solenoid valve.

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“…Based on Equation (20), the polynomial function is adopted for the armature stroke, l, ΔG and f(x1, x2…xq). This function is written as follows: ( , ... ) ( , ... )…”

Section: δG P P X P Y P X P Xymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Improved Method for Distributed Parameter Model of Solenoid Valve Based on Kriging Basis Function Predictive Identification Program

et al. 2021

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“…In [8], an explanation of the mathematical development of kriging and cokriging based on substitution models within the framework of optimization is made, [9] and they propose to improve the construction of the variogram using information of magnitude and direction applied to data of the National Network of the Geomagnetic Observatories of China.…”

Section: Related Workmentioning

confidence: 99%

Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador

Padilla¹,

García²

2018

Computational Intelligence and Neuroscience

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This work proposes a methodology that reduces the error of future estimations in commercialization based on multivariate spatial prediction techniques (cokriging) considering the products with strong associations. It is based on the Apriori algorithm to find association rules in sales of agricultural products of local markets. Results show the improvement in spatial prediction accuracy after using the best association rules.

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Improving Forecasting Using Information Fusion in Local Agricultural Markets

Padilla¹,

García

Molina

2018

Lecture Notes in Computer Science

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Improve Spatiotemporal Kriging with Magnitude and Direction Information in Variogram Construction

Cited by 6 publications

References 21 publications

Improved Method for Distributed Parameter Model of Solenoid Valve Based on Kriging Basis Function Predictive Identification Program

Improved Method for Distributed Parameter Model of Solenoid Valve Based on Kriging Basis Function Predictive Identification Program

Data Association Methodology to Improve Spatial Predictions in Alternative Marketing Circuits in Ecuador

Improving Forecasting Using Information Fusion in Local Agricultural Markets

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