Everyone interested in this topic is welcomed to join us. the following is the abstract for this week\u2019s paper.<\/p>\n\n\n\n

\n\t

\n\t\tA multi-pattern deep fusion model for short-term bus passenger flow<\/span>\n\t<\/p>\n\t

\n\t\tYun Bai, Zhenzhong Sun, Bo Zeng, Jun Deng, Chuan Li<\/span>\n\t<\/p>\n\t

\n\t\tAbstract<\/span>\n\t<\/p>\n\t

\n\t\tShort-term passenger flow forecasting\nis one of the crucial components in transportation systems with data support\nfor transportation planning and management. For forecasting bus passenger flow,\nthis paper proposes a multi-pattern deep fusion (MPDF) approach that is\nconstructed by fusing deep belief networks(DBNs) corresponding to multiple\npatterns. The dataset of the short-term bus passenger flow is first segmented\ninto different clusters by an affinity propagation algorithm. The passenger flow distribution of these clusters is subsequently analyzed for identifying different patterns. In each pattern, a DBN is developed as a deep representation for the passenger flow. The outputs of the DBNs are finally\nfused by chronological order rearrangement. Taking a bus line in Guangzhou city\nof China as an example, the present MPDF approach is modeled. Five approaches,\nnon-parametric and parametric models, are applied to the same case for\ncomparison. The results show that, the proposed model overwhelms all the peer\nmethods in terms of mean absolute percentage error, root-mean-square error, and\ndetermination coefficient criteria. In addition, there exists significant\ndifference between the addressed model and the comparison models. It is recommended\nfrom the present study that the deep learning technique incorporating the\npattern analysis is promising in forecasting the short-term passenger flow.<\/span>\n\t<\/p>\n<\/div>\n\n\n\n

A multi-pattern deep fusion model for short-term bus passenger flow<\/a>\u4e0b\u8f7d<\/a><\/div>\n\n\n\n\n\n\n\n

NLPIR SEMINAR 25th ISSUE COMPLETED<\/strong><\/h2>\n\n\n\n
Last Monday, Nihad<\/strong> gave a presentation about the paper, A multi-pattern deep fusion model for short-term bus passenger flow forecasting<\/strong>, and shared some opinion on it.<\/p>\n\n\n\n
$\"\"$ <\/figure>\n\n\n\n
In this paper, a multi-pattern deep fusion approach (MPDF),combining the AP algorithm for identifying the passenger flow pattern and the DBN framework for learning sophisticated flow features, has been reported to forecast the short-term bus passenger flow. The MPDF could generate as the fused final forecasts with three steps. <\/p>\n\n\n\n
The results also cmpared with the non-parametric model (the DBN, the AE, the AP-based AE,and feed forward neural network (FFNN)) and the parametric model(the ARIMA).<\/p>\n","protected":false},"excerpt":{"rendered":"
NLPIR SEMINAR Y2019#12 INTRO In the new … \u7ee7\u7eed\u9605\u8bfb →<\/span><\/a><\/p>\n","protected":false},"author":862,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":""},"categories":[37,38],"tags":[],"_links":{"self":[{"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/posts\/6892"}],"collection":[{"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/users\/862"}],"replies":[{"embeddable":true,"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/comments?post=6892"}],"version-history":[{"count":2,"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/posts\/6892\/revisions"}],"predecessor-version":[{"id":6907,"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/posts\/6892\/revisions\/6907"}],"wp:attachment":[{"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/media?parent=6892"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/categories?post=6892"},{"taxonomy":"post_tag","embeddable":true,"href":"http:\/\/www.nlpir.org\/wordpress\/wp-json\/wp\/v2\/tags?post=6892"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}

INTRO <\/h3>\n\n\n\n In the new semester, our Lab, Web Search Mining and Security Lab, plans to hold an academic seminar every Monday, and each time a keynote speaker will share understanding of papers on his\/her related research with you.<\/p>\n\n\n\n

INTRO <\/h3>\n\n\n\n
In the new semester, our Lab, Web Search Mining and Security Lab, plans to hold an academic seminar every Monday, and each time a keynote speaker will share understanding of papers on his\/her related research with you.
<\/p>\n\n\n\n