Impact of cross-section centers estimation on the accuracy of the point cloud spatial expansion using robust M-estimation and Monte Carlo simulation

Dąbrowski, Paweł; Zienkiewicz, Marek Hubert

doi:10.1016/j.measurement.2021.110436

Cited by 10 publications

(3 citation statements)

References 18 publications

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“…The capacity of the estimator to endure disruptions is what is meant by the crucial estimation performance index robust [10]. The article suggests a robust M-estimate approach to optimize CLV based on sampling in order to solve this issue by improving the overall state estimation accuracy by correctly changing the robustness [11].…”

Section: Introductionmentioning

confidence: 99%

An boosting business intelligent to customer lifetime value with robust M-estimation

Elveny,

Y. Syah,

M. Nasution

2024

IJ-AI

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When a business concentrates too much on acquiring new clients rather than retaining old ones, mistakes are sometimes made. Each customer has a different value. Customer lifetime value (CLV) is a metric used to assess longterm customer value. Customer value is a key concern in any commercial endeavor. When there are variations in customer behavior, CLV forecasts the value of total customer income when the data distribution is not normal, and outliers are present. Robust M-estimation, a maximum likelihood type estimator, is used in this study to enhance CLV data. Through the minimization of the regression parameter from the residual value, robust Mestimation eliminates data outliers in customer metric data. With an accuracy of 94.15%, R-square is used to gauge model performance. This research shows that CLV optimization can be used as a marketing and sales strategy by companies.

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Section: Introductionmentioning

confidence: 99%

An boosting business intelligent to customer lifetime value with robust M-estimation

Elveny,

Y. Syah,

M. Nasution

2024

IJ-AI

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show abstract

“…In the process of surface fitting, the elimination of noise and outliers is very important. M-estimation, represented by the least square method, is the most commonly used method, which is suitable for noise with symmetrical distribution [50]. Msplit estimation is an advanced variant of M-estimation, which can independently estimate multiple subsets of a point cloud [51,52].…”

Section: Introductionmentioning

confidence: 99%

High-Precision Monitoring Method for Bridge Deformation Measurement and Error Analysis Based on Terrestrial Laser Scanning

Zhou,

Zhu,

Zhao

et al. 2024

Remote Sensing

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In bridge structure monitoring and evaluation, deformation data serve as a crucial basis for assessing structural conditions. Different from discrete monitoring points, spatially continuous deformation modes provide a comprehensive understanding of deformation and potential information. Terrestrial laser scanning (TLS) is a three-dimensional deformation monitoring technique that has gained wide attention in recent years, demonstrating its potential in capturing structural deformation models. In this study, a TLS-based bridge deformation mode monitoring method is proposed, and a deformation mode calculation method combining sliding windows and surface fitting is developed, which is called the SWSF method for short. On the basis of the general characteristics of bridge structures, a deformation error model is established for the SWSF method, with a detailed quantitative analysis of each error component. The analysis results show that the deformation monitoring error of the SWSF method consists of four parts, which are related to the selection of the fitting function, the density of point clouds, the noise of point clouds, and the registration accuracy of point clouds. The error caused by point cloud noise is the main error component. Under the condition that the noise level of point clouds is determined, the calculation error of the SWSF method can be significantly reduced by increasing the number of points of point clouds in the sliding window. Then, deformation testing experiments were conducted under different measurement distances, proving that the proposed SWSF method can achieve a deformation monitoring accuracy of up to 0.1 mm. Finally, the proposed deformation mode monitoring method based on TLS and SWSF was tested on a railway bridge with a span of 65 m. The test results showed that in comparison with the commonly used total station method, the proposed method does not require any preset reflective markers, thereby improving the deformation monitoring accuracy from millimeter level to submillimeter level and transforming the discrete measurement point data form into spatially continuous deformation modes. Overall, this study introduces a new method for accurate deformation monitoring of bridges, demonstrating the significant potential for its application in health monitoring and damage diagnosis of bridge structures.

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“…In the tachymetric measurement, the threedimensional coordinates of a point are calculated based on slope distance and horizontal and vertical angles. This solution enables the application of various adjustment methods, e.g., conditions-binded adjustment [32], the standard ordinary least squares (OLS) method, robust estimation with dumping functions [33][34][35][36], or the M-estimation [37,38].…”

Section: Introductionmentioning

confidence: 99%

Assessment of Adjustment of GNSS Railway Measurements with Parameter-Binding Conditions in a Stationary Scenario

Dąbrowski

Specht

et al. 2022

Applied Sciences

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The study aims to assess the applicability of the ordinary least squares method, robust estimation, and conditions-binded adjustment in processing the six synchronous coordinate pairs of global navigation satellite system (GNSS) receivers. The research is part of the research project InnoSatTrack, focused on the enhancement of the determination of geometrical parameters of railway tracks using GNSS, inertial, and other sensors. A fixed frame of installation of six receivers is used in the data processing. Due to the limited availability of railway routes for measurements, the stationary campaign was conducted to gather data for the adjustment procedures tests. Six GNSS receivers in the frame-restricted configuration were set up using the tachymetric method for recording 96,729 synchronous static observations. Post-processed coordinates of the receivers were adjusted according to the geometrical conditions of the survey frame. Analysis showed higher applicability of the conditions-binded method than other estimation methods by obtaining superior results in both the precision and the maintenance of the design conditions factors than in the OLS and robust estimators.

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Impact of cross-section centers estimation on the accuracy of the point cloud spatial expansion using robust M-estimation and Monte Carlo simulation

Cited by 10 publications

References 18 publications

An boosting business intelligent to customer lifetime value with robust M-estimation

An boosting business intelligent to customer lifetime value with robust M-estimation

High-Precision Monitoring Method for Bridge Deformation Measurement and Error Analysis Based on Terrestrial Laser Scanning

Assessment of Adjustment of GNSS Railway Measurements with Parameter-Binding Conditions in a Stationary Scenario

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