Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM

With the rapid development of vehicle-mounted communication technology, GPS data is an effective method to predict the current road vehicle track based on vehicle-mounted data. GPS-oriented vehicle-mounted data position prediction method is currently a hot research work and an effective method to re...

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Main Authors: Zhen Yang, Zengwu Sun
Format: Article
Language:English
Published: Frontiers Media S.A. 2020-07-01
Series:Frontiers in Physics
Subjects:
GPS
ELM
Online Access:https://www.frontiersin.org/article/10.3389/fphy.2020.00259/full
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spelling doaj-f8549d620abd4beb8b9c29d85db1f46f2020-11-25T03:05:51ZengFrontiers Media S.A.Frontiers in Physics2296-424X2020-07-01810.3389/fphy.2020.00259551976Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELMZhen Yang0Zengwu Sun1Chongqing Key Laboratory of Spatial Data Mining and Big Data Integration for Ecology and Environment, Rongzhi College of Chongqing Technology and Business University, Chongqing, ChinaCollege of Medical Information Engineering, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, ChinaWith the rapid development of vehicle-mounted communication technology, GPS data is an effective method to predict the current road vehicle track based on vehicle-mounted data. GPS-oriented vehicle-mounted data position prediction method is currently a hot research work and an effective method to realize intelligent transportation. In this paper, an improvement scheme is proposed based on the problem of falling into local optimization existing in the basic algorithm of teaching and learning optimization algorithm. An interference operator is used to disturb teachers to enhance the kinetic energy of the population to jump out of local optimization. By comparing the performance of GA, PSO, TLBO, and ITLBO algorithms with four test functions, the results show that ITLBO has efficient optimization effect and generalization ability. Finally, the ITLBO-ELM algorithm has the best prediction effect by comparing the vehicle GPS data and comparing the experimental algorithms.https://www.frontiersin.org/article/10.3389/fphy.2020.00259/fullGPSlearning optimization algorithmITLBO algorithmsELMprediction method
collection DOAJ
language English
format Article
sources DOAJ
author Zhen Yang
Zengwu Sun
spellingShingle Zhen Yang
Zengwu Sun
Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM
Frontiers in Physics
GPS
learning optimization algorithm
ITLBO algorithms
ELM
prediction method
author_facet Zhen Yang
Zengwu Sun
author_sort Zhen Yang
title Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM
title_short Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM
title_full Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM
title_fullStr Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM
title_full_unstemmed Research on Geographic Location Prediction Algorithm Based on Improved Teaching and Learning Optimization ELM
title_sort research on geographic location prediction algorithm based on improved teaching and learning optimization elm
publisher Frontiers Media S.A.
series Frontiers in Physics
issn 2296-424X
publishDate 2020-07-01
description With the rapid development of vehicle-mounted communication technology, GPS data is an effective method to predict the current road vehicle track based on vehicle-mounted data. GPS-oriented vehicle-mounted data position prediction method is currently a hot research work and an effective method to realize intelligent transportation. In this paper, an improvement scheme is proposed based on the problem of falling into local optimization existing in the basic algorithm of teaching and learning optimization algorithm. An interference operator is used to disturb teachers to enhance the kinetic energy of the population to jump out of local optimization. By comparing the performance of GA, PSO, TLBO, and ITLBO algorithms with four test functions, the results show that ITLBO has efficient optimization effect and generalization ability. Finally, the ITLBO-ELM algorithm has the best prediction effect by comparing the vehicle GPS data and comparing the experimental algorithms.
topic GPS
learning optimization algorithm
ITLBO algorithms
ELM
prediction method
url https://www.frontiersin.org/article/10.3389/fphy.2020.00259/full
work_keys_str_mv AT zhenyang researchongeographiclocationpredictionalgorithmbasedonimprovedteachingandlearningoptimizationelm
AT zengwusun researchongeographiclocationpredictionalgorithmbasedonimprovedteachingandlearningoptimizationelm
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