Research on POI quality prediction based on KPCA-GA-BP neural network
At present, in network optimization, network quality evaluation and prediction are generally based on communities, and a flexible evaluation system for POI network quality was proposed following the research idea of “research on dimensionality increase and implementation of dimensionality reduction”...
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Format: | Article |
Language: | zho |
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Beijing Xintong Media Co., Ltd
2023-01-01
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Series: | Dianxin kexue |
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Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023004/ |
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author | Lu LIU Dan YANG Ruijie CHEN Jia LI Xi ZHOU |
author_facet | Lu LIU Dan YANG Ruijie CHEN Jia LI Xi ZHOU |
author_sort | Lu LIU |
collection | DOAJ |
description | At present, in network optimization, network quality evaluation and prediction are generally based on communities, and a flexible evaluation system for POI network quality was proposed following the research idea of “research on dimensionality increase and implementation of dimensionality reduction”.However, it involves many network KPI, resulting in a relatively complex evaluation system for POI network comprehensive quality and low prediction accuracy.In order to improve the prediction accuracy of POI network quality, KPCA was used to compress the correlation of input variables of BP neural network, the structure of BP neural network was simplified, and then the connection weights and threshold parameters of BP neural network were optimized through GA.Compared with the prediction results of traditional BP neural network, the prediction accuracy is improved by 10.9%, and the mean square error performance is significantly reduced, it can play a better supporting role in the prediction of POI network quality. |
format | Article |
id | doaj-art-66b889da2704419d9eafeb8284738c33 |
institution | Kabale University |
issn | 1000-0801 |
language | zho |
publishDate | 2023-01-01 |
publisher | Beijing Xintong Media Co., Ltd |
record_format | Article |
series | Dianxin kexue |
spelling | doaj-art-66b889da2704419d9eafeb8284738c332025-01-15T02:59:13ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012023-01-013910811659571710Research on POI quality prediction based on KPCA-GA-BP neural networkLu LIUDan YANGRuijie CHENJia LIXi ZHOUAt present, in network optimization, network quality evaluation and prediction are generally based on communities, and a flexible evaluation system for POI network quality was proposed following the research idea of “research on dimensionality increase and implementation of dimensionality reduction”.However, it involves many network KPI, resulting in a relatively complex evaluation system for POI network comprehensive quality and low prediction accuracy.In order to improve the prediction accuracy of POI network quality, KPCA was used to compress the correlation of input variables of BP neural network, the structure of BP neural network was simplified, and then the connection weights and threshold parameters of BP neural network were optimized through GA.Compared with the prediction results of traditional BP neural network, the prediction accuracy is improved by 10.9%, and the mean square error performance is significantly reduced, it can play a better supporting role in the prediction of POI network quality.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023004/POI flexibility evaluation systemkernel principal component analysisgenetic algorithmBP neural networkPOI quality prediction |
spellingShingle | Lu LIU Dan YANG Ruijie CHEN Jia LI Xi ZHOU Research on POI quality prediction based on KPCA-GA-BP neural network Dianxin kexue POI flexibility evaluation system kernel principal component analysis genetic algorithm BP neural network POI quality prediction |
title | Research on POI quality prediction based on KPCA-GA-BP neural network |
title_full | Research on POI quality prediction based on KPCA-GA-BP neural network |
title_fullStr | Research on POI quality prediction based on KPCA-GA-BP neural network |
title_full_unstemmed | Research on POI quality prediction based on KPCA-GA-BP neural network |
title_short | Research on POI quality prediction based on KPCA-GA-BP neural network |
title_sort | research on poi quality prediction based on kpca ga bp neural network |
topic | POI flexibility evaluation system kernel principal component analysis genetic algorithm BP neural network POI quality prediction |
url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2023004/ |
work_keys_str_mv | AT luliu researchonpoiqualitypredictionbasedonkpcagabpneuralnetwork AT danyang researchonpoiqualitypredictionbasedonkpcagabpneuralnetwork AT ruijiechen researchonpoiqualitypredictionbasedonkpcagabpneuralnetwork AT jiali researchonpoiqualitypredictionbasedonkpcagabpneuralnetwork AT xizhou researchonpoiqualitypredictionbasedonkpcagabpneuralnetwork |