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Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
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Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
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Sensors and Materials
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is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.
Instructions to authors
English 日本語
Instructions for manuscript preparation
English 日本語
Template
English
Publisher
MYU K.K.
Sensors and Materials
1-23-3-303 Sendagi,
Bunkyo-ku, Tokyo 113-0022, Japan
Tel: 81-3-3827-8549
Fax: 81-3-3827-8547
MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.
MYU Research
(proofreading and recording)
MYU K.K.
(translation service)
The Art of Writing Scientific Papers
(How to write scientific papers)
(Japanese Only)
Sensors and Materials, Volume 38, Number 7(1) (2026)
Copyright(C) MYU K.K.
Copyright(C) MYU K.K.
|
pp. 3737-3746
S&M4532 Research paper https://doi.org/10.18494/SAM5351 Published: July 10, 2026 Optimization of Measurement Station Placement for Large-scale 3D Control Network Based on Collision Model and Simplex Algorithm [PDF] Tingting Jin, Keliang Ding, Xuece Miao, and Xinle Zhang (Received August 29, 2024; Accepted October 24, 2025) Keywords: large 3D control network, linear collision model, simplex algorithm
Large-scale 3D control networks, which are essential for the precise measurement of large scientific facilities, have traditionally relied on empirical models. However, such approaches constrain the accuracy of measurement station placement and lack systematic optimization strategies. In this study, we systematically investigate the optimization of measurement station placement in complex environments and propose a method that integrates a collision model with the simplex algorithm. Simulation results indicate that, relative to conventional empirical model layouts, the proposed approach reduces station redundancy and deployment time, increases the number of effective measuring points by 8%, enhances single-point accuracy by 66%, and significantly improves the overall accuracy of the control network.
Corresponding author: Xuece Miao  This work is licensed under a Creative Commons Attribution 4.0 International License. Cite this article Tingting Jin, Keliang Ding, Xuece Miao, and Xinle Zhang, Optimization of Measurement Station Placement for Large-scale 3D Control Network Based on Collision Model and Simplex Algorithm, Sens. Mater., Vol. 38, No. 7, 2026, p. 3737-3746. |
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