A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm
Accurate analytical solution for the crosstalk of random cable bundle is difficult to obtain, but the limit of the crosstalk can be predicted. This paper proposes a method to predict the crosstalk of random cable bundle. Based on the idea of cascade method, the model takes into account the random ro...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2020-01-01
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| Series: | IEEE Access |
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| Online Access: | https://ieeexplore.ieee.org/document/8968408/ |
| _version_ | 1818618357619884032 |
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| author | Chao Huang Yang Zhao Wei Yan Qiangqiang Liu Jianming Zhou |
| author_facet | Chao Huang Yang Zhao Wei Yan Qiangqiang Liu Jianming Zhou |
| author_sort | Chao Huang |
| collection | DOAJ |
| description | Accurate analytical solution for the crosstalk of random cable bundle is difficult to obtain, but the limit of the crosstalk can be predicted. This paper proposes a method to predict the crosstalk of random cable bundle. Based on the idea of cascade method, the model takes into account the random rotation of the cross-section and the random transposition of the core. A neural network algorithm based on back propagation optimized by the beetle antennae search method (BAS-BPNN) is introduced to mathematically describe the random rotation of the cross-section. The elementary row-to-column transformation of the unit length RLCG parameter matrix is used to deal with the random transposition of the core. The discontinuity between segments generated by transposition is solved by introducing transition probability parameters. Finally, combined with the finite-difference time-domain (FDTD) algorithm, the crosstalk of the random cable bundle is obtained. The numerical experimental results show that the new method can reduce a lot of experimental work in the crosstalk problem of random cable bundle, and has higher accuracy and a wider frequency range. |
| first_indexed | 2024-12-16T17:20:18Z |
| format | Article |
| id | doaj.art-044734ac6e8944b680b5bed985291d3a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-16T17:20:18Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-044734ac6e8944b680b5bed985291d3a2022-12-21T22:23:10ZengIEEEIEEE Access2169-35362020-01-018202242023210.1109/ACCESS.2020.29692218968408A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network AlgorithmChao Huang0https://orcid.org/0000-0002-7802-5342Yang Zhao1https://orcid.org/0000-0001-9213-3342Wei Yan2https://orcid.org/0000-0002-5981-5138Qiangqiang Liu3https://orcid.org/0000-0001-9017-8635Jianming Zhou4https://orcid.org/0000-0002-4136-5642School of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, ChinaSchool of Electrical and Automation Engineering, Nanjing Normal University, Nanjing, ChinaAccurate analytical solution for the crosstalk of random cable bundle is difficult to obtain, but the limit of the crosstalk can be predicted. This paper proposes a method to predict the crosstalk of random cable bundle. Based on the idea of cascade method, the model takes into account the random rotation of the cross-section and the random transposition of the core. A neural network algorithm based on back propagation optimized by the beetle antennae search method (BAS-BPNN) is introduced to mathematically describe the random rotation of the cross-section. The elementary row-to-column transformation of the unit length RLCG parameter matrix is used to deal with the random transposition of the core. The discontinuity between segments generated by transposition is solved by introducing transition probability parameters. Finally, combined with the finite-difference time-domain (FDTD) algorithm, the crosstalk of the random cable bundle is obtained. The numerical experimental results show that the new method can reduce a lot of experimental work in the crosstalk problem of random cable bundle, and has higher accuracy and a wider frequency range.https://ieeexplore.ieee.org/document/8968408/Crosstalkrandom cable bundlebeetle antennae search (BAS) algorithmback propagation neural network (BPNN) algorithmfinite-difference time-domain (FDTD)multi-conductor transmission lines (MTLs) |
| spellingShingle | Chao Huang Yang Zhao Wei Yan Qiangqiang Liu Jianming Zhou A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm IEEE Access Crosstalk random cable bundle beetle antennae search (BAS) algorithm back propagation neural network (BPNN) algorithm finite-difference time-domain (FDTD) multi-conductor transmission lines (MTLs) |
| title | A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm |
| title_full | A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm |
| title_fullStr | A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm |
| title_full_unstemmed | A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm |
| title_short | A New Method for Predicting Crosstalk of Random Cable Bundle Based on BAS-BP Neural Network Algorithm |
| title_sort | new method for predicting crosstalk of random cable bundle based on bas bp neural network algorithm |
| topic | Crosstalk random cable bundle beetle antennae search (BAS) algorithm back propagation neural network (BPNN) algorithm finite-difference time-domain (FDTD) multi-conductor transmission lines (MTLs) |
| url | https://ieeexplore.ieee.org/document/8968408/ |
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