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Within the conceptual framework of computational logistics, an attention mechanism oriented hybrid convolutional neural network and recurrent neural network deep learning architecture (AMO\u2010HCR\u2010DLA) is proposed technically to predict the container terminal liner handling conditions that mainly include liner handling time (LHT) and total working time of quay crane farm (TWT\u2010QCF) for a calling liner. Consequently, the container terminal oriented logistics generalized computation (CTO\u2010LGC) automation and intelligence are established tentatively by AMO\u2010HCR\u2010DLA. A typical regional container terminal hub of China is selected to design, implement, execute, and evaluate the AMO\u2010HCR\u2010DLA with the actual production data. In the case of severe vibration of LHT and TWT\u2010QCF, while forecasting the handling conditions of 210 ships based on the CTO\u2010LGC running log of four years, the forecasting error of LHT within one hour is more than 97% and that of TWT\u2010QCF within six hours accounts for 89.405%. When predicting the operating conditions of 300 liners by the log of five years, the forecasting deviation of LHT within one hour is more than striking 99% and that of TWT\u2010QCF within six hours reaches up to 94.010% as well. All are far superior to the predicting outcomes by the classical algorithms of machine learning and deep learning. Hence, the AMO\u2010HCR\u2010DLA shows excellent performance for the prediction of CTHS with the low and stable computational consuming. It also demonstrates the feasibility, credibility, and realizability of the computing architecture and design paradigm of AMO\u2010HCR\u2010DLA preliminarily.<\/jats:p>","DOI":"10.1155\/2021\/3846078","type":"journal-article","created":{"date-parts":[[2021,7,9]],"date-time":"2021-07-09T20:50:07Z","timestamp":1625863807000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":8,"title":["An Attention Mechanism Oriented Hybrid CNN\u2010RNN Deep Learning Architecture of Container Terminal Liner Handling Conditions Prediction"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9322-1723","authenticated-orcid":false,"given":"Bin","family":"Li","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3853-2809","authenticated-orcid":false,"given":"Yuqing","family":"He","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,7,9]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2020.100301"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2020.100289"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2018.05.018"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2019.100203"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/tgrs.2020.2964627"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TASLP.2020.3036237"},{"key":"e_1_2_9_7_2","doi-asserted-by":"publisher","DOI":"10.1109\/RBME.2020.3006860"},{"key":"e_1_2_9_8_2","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2020.2979670"},{"key":"e_1_2_9_9_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.dsp.2020.102951"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.drudis.2019.07.006"},{"key":"e_1_2_9_11_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.neunet.2019.11.005"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/TMECH.2020.3022983"},{"key":"e_1_2_9_13_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2020.100341"},{"key":"e_1_2_9_14_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.tre.2019.101834"},{"key":"e_1_2_9_15_2","doi-asserted-by":"publisher","DOI":"10.3390\/su12093760"},{"key":"e_1_2_9_16_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.rser.2019.04.069"},{"key":"e_1_2_9_17_2","doi-asserted-by":"publisher","DOI":"10.1007\/s10696-020-09385-5"},{"key":"e_1_2_9_18_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ejor.2020.08.006"},{"key":"e_1_2_9_19_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijpe.2017.10.027"},{"key":"e_1_2_9_20_2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cie.2021.107118"},{"key":"e_1_2_9_21_2","doi-asserted-by":"crossref","unstructured":"ZhangW. 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