融合机器学习算法的煤矿井下信道建模研究

TD166%TN929.4; 由于矿井复杂多变的环境特征,传统射线跟踪法的井下无线信道建模误差较大,本文通过对机器学习算法及其搭配使用的特征进行分析评估,从而选择最优的信道建模方法.引入机器学习算法对场景特征进行学习进而实现较为精确的建模,研究了BP神经网络、遗传算法、支持向量机在井下信道建模方向上的应用.构建了射线跟踪法与GA_BP相结合的场强预测模型,同时使用最小二乘支持向量机方法建立预测模型.以地下巷道的实测数据作为算法的训练样本,对场强进行预测,试验本文各类算法的特征以及算法中参数对预测结果的影响.得到场强预测结果与实测数据的误差为-1.206 dbm,本文混合模型提升了井下场强预测精...

Full description

Saved in:
Bibliographic Details
Published in中国矿业 Vol. 30; no. 11; pp. 68 - 74
Main Authors 崔丽珍, 曹坚, 李丹阳, 杨勇, 史明泉
Format Magazine Article
LanguageChinese
Published 内蒙古科技大学信息工程学院,内蒙古包头014010 01.11.2021
Subjects
煤矿井下;场强预测;混合模型;射线跟踪;GA_BP;LS-SVM
Online AccessGet full text
ISSN1004-4051
DOI10.12075/j.issn.1004-4051.2021.11.014

Cover

Abstract TD166%TN929.4; 由于矿井复杂多变的环境特征,传统射线跟踪法的井下无线信道建模误差较大,本文通过对机器学习算法及其搭配使用的特征进行分析评估,从而选择最优的信道建模方法.引入机器学习算法对场景特征进行学习进而实现较为精确的建模,研究了BP神经网络、遗传算法、支持向量机在井下信道建模方向上的应用.构建了射线跟踪法与GA_BP相结合的场强预测模型,同时使用最小二乘支持向量机方法建立预测模型.以地下巷道的实测数据作为算法的训练样本,对场强进行预测,试验本文各类算法的特征以及算法中参数对预测结果的影响.得到场强预测结果与实测数据的误差为-1.206 dbm,本文混合模型提升了井下场强预测精度.
AbstractList TD166%TN929.4; 由于矿井复杂多变的环境特征,传统射线跟踪法的井下无线信道建模误差较大,本文通过对机器学习算法及其搭配使用的特征进行分析评估,从而选择最优的信道建模方法.引入机器学习算法对场景特征进行学习进而实现较为精确的建模,研究了BP神经网络、遗传算法、支持向量机在井下信道建模方向上的应用.构建了射线跟踪法与GA_BP相结合的场强预测模型,同时使用最小二乘支持向量机方法建立预测模型.以地下巷道的实测数据作为算法的训练样本,对场强进行预测,试验本文各类算法的特征以及算法中参数对预测结果的影响.得到场强预测结果与实测数据的误差为-1.206 dbm,本文混合模型提升了井下场强预测精度.
Author 史明泉
崔丽珍
杨勇
李丹阳
曹坚
AuthorAffiliation 内蒙古科技大学信息工程学院,内蒙古包头014010
AuthorAffiliation_xml – name: 内蒙古科技大学信息工程学院,内蒙古包头014010
Author_FL CUI Lizhen
SHI Mingquan
CAO Jian
LI Danyang
YANG Yong
Author_FL_xml – sequence: 1
  fullname: CUI Lizhen
– sequence: 2
  fullname: CAO Jian
– sequence: 3
  fullname: LI Danyang
– sequence: 4
  fullname: YANG Yong
– sequence: 5
  fullname: SHI Mingquan
Author_xml – sequence: 1
  fullname: 崔丽珍
– sequence: 2
  fullname: 曹坚
– sequence: 3
  fullname: 李丹阳
– sequence: 4
  fullname: 杨勇
– sequence: 5
  fullname: 史明泉
BookMark eNo9j81Kw0AURmdRwVr7GF1mvHcyyaRLKf5BwY2uy6SZKa2SgoOI7gQFQQRBS1FEWxCpC90IonHRl0ky-hZGFFcfnMV3OHOkFPdjRUgNgSID4S30aNeYmCIAdzh4SBkwpIgUkJdI-Z_Pkqox3RAAmMCClkn98_YsOz_Jb5LsapI9PaTvI_s8zF8G9vrIHt_bu2maDNK303Q6_jq8yD6SfDK2o0v7-DpPZrTcNqr6txWyuby00Vh1musra43FpmMQmOtgPZKekBFoJUXkg8bQlzwADiEqDAMtdOhzEWilRdTmXCiQvM0jD5kQXDK3Qmq_v3sy1jLutHr93Z24MLYOOlv7P6FFCbruN6NfYVk
ClassificationCodes TD166%TN929.4
ContentType Magazine Article
Copyright Copyright © Wanfang Data Co. Ltd. All Rights Reserved.
Copyright_xml – notice: Copyright © Wanfang Data Co. Ltd. All Rights Reserved.
DBID 2B.
4A8
92I
93N
PSX
TCJ
DOI 10.12075/j.issn.1004-4051.2021.11.014
DatabaseName Wanfang Data Journals - Hong Kong
WANFANG Data Centre
Wanfang Data Journals
万方数据期刊 - 香港版
China Online Journals (COJ)
China Online Journals (COJ)
DatabaseTitleList
DeliveryMethod fulltext_linktorsrc
DocumentTitle_FL Research on the channel modeling in coal mine based on machine learning algorithm
EndPage 74
ExternalDocumentID zgky202111013
GrantInformation_xml – fundername: (国家自然科学基金项目资助); (内蒙古自治区科技计划项目资助); (内蒙古自然科学基金项目资助)
  funderid: (国家自然科学基金项目资助); (内蒙古自治区科技计划项目资助); (内蒙古自然科学基金项目资助)
GroupedDBID -02
2B.
4A8
92I
93N
ALMA_UNASSIGNED_HOLDINGS
CCEZO
CDRFL
GROUPED_DOAJ
PSX
TCJ
ID FETCH-LOGICAL-s1023-19da57ad0fea7d60f1b6a48040b1e1b8f7fb6478fef7dc447e0a4c4d512774a23
ISSN 1004-4051
IngestDate Thu May 29 04:07:01 EDT 2025
IsPeerReviewed false
IsScholarly true
Issue 11
Keywords 煤矿井下;场强预测;混合模型;射线跟踪;GA_BP;LS-SVM
Language Chinese
LinkModel OpenURL
MergedId FETCHMERGED-LOGICAL-s1023-19da57ad0fea7d60f1b6a48040b1e1b8f7fb6478fef7dc447e0a4c4d512774a23
PageCount 7
ParticipantIDs wanfang_journals_zgky202111013
PublicationCentury 2000
PublicationDate 2021-11-01
PublicationDateYYYYMMDD 2021-11-01
PublicationDate_xml – month: 11
  year: 2021
  text: 2021-11-01
  day: 01
PublicationDecade 2020
PublicationTitle 中国矿业
PublicationTitle_FL China Mining Magazine
PublicationYear 2021
Publisher 内蒙古科技大学信息工程学院,内蒙古包头014010
Publisher_xml – name: 内蒙古科技大学信息工程学院,内蒙古包头014010
SSID ssib000271100
ssj0002923792
ssib001104777
ssib036435255
ssib051369032
Score 1.3745825
Snippet TD166%TN929.4;...
SourceID wanfang
SourceType Aggregation Database
StartPage 68
Title 融合机器学习算法的煤矿井下信道建模研究
URI https://d.wanfangdata.com.cn/periodical/zgky202111013
Volume 30
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
link http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1LaxRBEB5iBPGkouIz5GAfZ52e6enHsWd3hiDoKYHcwjwjCCuYzSF7ExQEFQQNoogmIBIPehFE10P-zD70X1jVM7s7GyU-LkNRU13VXTWz9fVsV7dlXcld4bM8pbbKHGkzylw7Tqi086LwlJemKTfHAV2_wZdW2LVVf3XuyKPaqqXNTtJIu7-tK_mfqAIP4opVsv8Q2YlSYAAN8YUrRBiufxVjEkqiQiJbJPSJcoiUJORENUmgDUcRLZHQLaI5CRkJgOOQUBAdEiVQOPCI8pGjNJEMCQnyhlARCSLTShsZICSRgSEioikJFeBQojw0EQTGKEeLeEugIWX0aEUCXgfBlSpddhsatmbNwaAmz5XRzYwmc6eUlREMeirCjRZl1LVmGnNkyHDcWGGfFRDeAZHSTzC4Ki9X30FcWhUEjp9cI8XRR-h6F12MnKhymYZhUFQpNS4hCY0rgTkTg9J3HH2nIzM-aGhioEv_ToSVCaELr8GhdoFomlvGXMDMdNappRtcBgSQmdbzkefU3ztayy7lAUQVTikPN_olA7qAAU0KRAONiYEGuqyB-9WWNbsHNhnvrt_aQgkAg3gE9FFXwDS_9oGi-o8a9xecgm3c5WNaxewBtvXdaZWzTz2unKpqGXGRC3MJocrlB1Wvjllk3Oerh_XYVNS1i7i9XgN_yyetE-Nd2Bd1-Q6esua6N09b6vvrx4MnD4aveoMXe4MP7_pfd0Yfnw8_bY9e3hvdfzt6s9_vbfe_POzv7_64-3TwrTfc2x3tPBu9_3zGWonC5eaSXR1FYm_g3iY2VVnsizhzijwWGXcKmvCYSciACc1pIgtRJFi1XeSFyFLGRO7ELGUZwGmYX8Wud9aab99u5-esRSEw08kkVqDBl6kE8JhlgArTwsvcTJy3FqqxrlU_NRtrM-G58CeBi9bx6QtyyZrv3NnMLwN07iQLJqI_AcfRjj8
linkProvider Directory of Open Access Journals
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=%E8%9E%8D%E5%90%88%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E7%AE%97%E6%B3%95%E7%9A%84%E7%85%A4%E7%9F%BF%E4%BA%95%E4%B8%8B%E4%BF%A1%E9%81%93%E5%BB%BA%E6%A8%A1%E7%A0%94%E7%A9%B6&rft.jtitle=%E4%B8%AD%E5%9B%BD%E7%9F%BF%E4%B8%9A&rft.au=%E5%B4%94%E4%B8%BD%E7%8F%8D&rft.au=%E6%9B%B9%E5%9D%9A&rft.au=%E6%9D%8E%E4%B8%B9%E9%98%B3&rft.au=%E6%9D%A8%E5%8B%87&rft.date=2021-11-01&rft.pub=%E5%86%85%E8%92%99%E5%8F%A4%E7%A7%91%E6%8A%80%E5%A4%A7%E5%AD%A6%E4%BF%A1%E6%81%AF%E5%B7%A5%E7%A8%8B%E5%AD%A6%E9%99%A2%2C%E5%86%85%E8%92%99%E5%8F%A4%E5%8C%85%E5%A4%B4014010&rft.issn=1004-4051&rft.volume=30&rft.issue=11&rft.spage=68&rft.epage=74&rft_id=info:doi/10.12075%2Fj.issn.1004-4051.2021.11.014&rft.externalDocID=zgky202111013
thumbnail_s http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=http%3A%2F%2Fwww.wanfangdata.com.cn%2Fimages%2FPeriodicalImages%2Fzgky%2Fzgky.jpg