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A distributed EEMDN-SABiGRU model on Spark for passenger hotspot prediction
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作者 Dawen XIA Jian GENG +4 位作者 Ruixi HUANG Bingqi SHEN Yang HU Yantao LI Huaqing LI 《Frontiers of Information Technology & Electronic Engineering》 SCIE EI CSCD 2023年第9期1316-1331,共16页
To address the imbalance problem between supply and demand for taxis and passengers,this paper proposes a distributed ensemble empirical mode decomposition with normalization of spatial attention mechanism based bi-di... To address the imbalance problem between supply and demand for taxis and passengers,this paper proposes a distributed ensemble empirical mode decomposition with normalization of spatial attention mechanism based bi-directional gated recurrent unit(EEMDN-SABiGRU)model on Spark for accurate passenger hotspot prediction.It focuses on reducing blind cruising costs,improving carrying efficiency,and maximizing incomes.Specifically,the EEMDN method is put forward to process the passenger hotspot data in the grid to solve the problems of non-smooth sequences and the degradation of prediction accuracy caused by excessive numerical differences,while dealing with the eigenmodal EMD.Next,a spatial attention mechanism is constructed to capture the characteristics of passenger hotspots in each grid,taking passenger boarding and alighting hotspots as weights and emphasizing the spatial regularity of passengers in the grid.Furthermore,the bi-directional GRU algorithm is merged to deal with the problem that GRU can obtain only the forward information but ignores the backward information,to improve the accuracy of feature extraction.Finally,the accurate prediction of passenger hotspots is achieved based on the EEMDN-SABiGRU model using real-world taxi GPS trajectory data in the Spark parallel computing framework.The experimental results demonstrate that based on the four datasets in the 00-grid,compared with LSTM,EMDLSTM,EEMD-LSTM,GRU,EMD-GRU,EEMD-GRU,EMDN-GRU,CNN,and BP,the mean absolute percentage error,mean absolute error,root mean square error,and maximum error values of EEMDN-SABiGRU decrease by at least 43.18%,44.91%,55.04%,and 39.33%,respectively. 展开更多
关键词 Passenger hotspot prediction Ensemble empirical mode decomposition(EEMD) Spatial attention mechanism Bi-directional gated recurrent unit(BiGRU) GPS trajectory SPARK
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Global Research Progress on Municipal Waste and Future Prospect Based on the Cross-national Comparisons
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作者 ZHANG Yuxin LIU Xiaoqian +2 位作者 YAN Xiaoxia MA Sike MAO Weiyun 《Chinese Geographical Science》 SCIE CSCD 2024年第2期250-264,共15页
Due to the acceleration of urbanization,the municipal waste(MW)problem has transformed into a global challenge for urb-an sustainability.To elucidate historical trends,current focal points,and future directions in MW ... Due to the acceleration of urbanization,the municipal waste(MW)problem has transformed into a global challenge for urb-an sustainability.To elucidate historical trends,current focal points,and future directions in MW research,we conducted a bibliometric analysis and employed knowledge graph visualization to scrutinize a total of 34212 articles,which were published between 1991 and 2021 in the Web of Science(WoS)core database.The results indicated that current major research themes encompass waste classifica-tion and recycling,waste management and public behavior,waste disposal methods and technologies,as well as environmental impact and evaluation.There has been a shift in the research focus from the environmental impacts of waste incineration to sustainable manage-ment related issues.A comparison of research from six typical countries revealed the differences in research priorities and techniques advantages.Scholars from the USA and Britain initiated MW research earlier than other countries and investigated management issues in depth,such as public behavior and willingness to pay.Meanwhile,Japanese,German,and Swedish scholars conducted extensive studies on advanced waste treatment technologies,such as disposal and recycling,risk assessment,and waste-to-energy techniques.Chinese scholars placed particular emphasis on end-of-pipe treatments and their associated environmental impacts.Hotspots and poten-tial future frontiers were identified by burst detection analysis.Keywords with high value of burst index(BI)worldwide are food waste and circular economy.Chinese scholars have put great efforts on waste environmental impact and its recycling technologies,while we’re expecting to further investigating vulnerable population.Furthermore,this study contributes to bridging the regional gap of scientific research among different countries and fostering international collaboration. 展开更多
关键词 BIBLIOMETRICS municipal waste(MW) CiteSpace hotspot prediction burst index(BI) SUSTAINABILITY cross-national comparison Web of Science(WoS)
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A bibliometrics visualization analysis and hotspots prediction for natural product on osteoporosis research from 2000 to 2021 被引量:3
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作者 Ajiao Hou Lin Yang +3 位作者 Jiahao Lü Liu Yang Haixue Kuang Hai Jiang 《Journal of Future Foods》 2022年第4期326-337,共12页
Aim The purpose of this study was to explore the application status of natural products in osteoporosis research and explore its research hotspots and future research directions by analyzing the literature in the fiel... Aim The purpose of this study was to explore the application status of natural products in osteoporosis research and explore its research hotspots and future research directions by analyzing the literature in the field of natural products therapy for osteoporosis from 2000 to 2021.Method Publications on natural products in osteoporosis research were extracted from the Web of Science core collection database.Bibliometrics package in R language,VOSviewer and CiteSpace software were used for visualization analysis.Result From 2000 to 2021,the number of articles on natural products in osteoporosis research was 1596,and the total number of articles increased rapidly.China was the driving force in this field,and the top-contributing institution was Guangzhou University of Chinese Medicine.Most publications were published in the Journal of Ethnopharmacology.While J.K.Xu and Y.Zhang were the most cited and co-cited author.Countries,research institutions and authors in different regions cooperate closely.The hot topics included osteoporosis,differentiation,expression,in vitro,cell,osteogenesis and osteogenesis were the research frontiers in recent years.Conclusion This study conducted a bibliometric visualization analysis on the research status,research hotspots and development trend of natural products in osteoporosis for the first time.In addition,this paper also puts forward suggestions and prospects for the future development of this field,which will help researchers to open up new directions for future research in this field. 展开更多
关键词 Bibliometrics visualization analysis Natural products OSTEOPOROSIS hotspots prediction
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