{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T23:12:26Z","timestamp":1770419546599,"version":"3.49.0"},"reference-count":49,"publisher":"Wiley","license":[{"start":{"date-parts":[[2020,10,28]],"date-time":"2020-10-28T00:00:00Z","timestamp":1603843200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51739003"],"award-info":[{"award-number":["51739003"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["51909173"],"award-info":[{"award-number":["51909173"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["B200201058"],"award-info":[{"award-number":["B200201058"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","award":["CX2019K01"],"award-info":[{"award-number":["CX2019K01"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009012","name":"Hohai University","doi-asserted-by":"publisher","award":["51739003"],"award-info":[{"award-number":["51739003"]}],"id":[{"id":"10.13039\/501100009012","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009012","name":"Hohai University","doi-asserted-by":"publisher","award":["51909173"],"award-info":[{"award-number":["51909173"]}],"id":[{"id":"10.13039\/501100009012","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009012","name":"Hohai University","doi-asserted-by":"publisher","award":["B200201058"],"award-info":[{"award-number":["B200201058"]}],"id":[{"id":"10.13039\/501100009012","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100009012","name":"Hohai University","doi-asserted-by":"publisher","award":["CX2019K01"],"award-info":[{"award-number":["CX2019K01"]}],"id":[{"id":"10.13039\/501100009012","id-type":"DOI","asserted-by":"publisher"}]},{"name":"Open Foundation of Changjiang Survey, Planning, Design and Research Co., Ltd.","award":["51739003"],"award-info":[{"award-number":["51739003"]}]},{"name":"Open Foundation of Changjiang Survey, Planning, Design and Research Co., Ltd.","award":["51909173"],"award-info":[{"award-number":["51909173"]}]},{"name":"Open Foundation of Changjiang Survey, Planning, Design and Research Co., Ltd.","award":["B200201058"],"award-info":[{"award-number":["B200201058"]}]},{"name":"Open Foundation of Changjiang Survey, Planning, Design and Research Co., Ltd.","award":["CX2019K01"],"award-info":[{"award-number":["CX2019K01"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Complexity"],"published-print":{"date-parts":[[2020,10,28]]},"abstract":"<jats:p>Dam behavior is difficult to predict due to its complexity. At the same time, dam deformation behavior is vital to dam systems. Developing a precise prediction model of dam deformation from prototype data is still challenging but determinant in the structural safety assessment. In this paper, an artificial neural network (ANN), trained by the improved artificial fish swarm algorithm (IAFSA) and backpropagation algorithm (BP), is proposed for predicting the dam deformation. Initially, crossover operator is embedded into AFSA, which aims to enhance the performance. In light of the influence mechanism of many factors on dam deformation behavior, the hybrid (IAFSA and BP) model uses statistical input to obtain the optimal connection weights and threshold values of the neural network. The hybrid model integrates IAFSA\u2019s strong global searching ability and BP\u2019s strong local search ability. To avoid overfitting the training set data, a validation set is adopted to check the generalization capability. Subsequently, the obtained optimal parameters are applied to predict the dam deformation behavior. The hybrid model\u2019s preciseness is verified against the radial displacements of a pendulum in a concrete arch dam and simulations of four models: statistical model, BP-ANN optimized by genetic algorithm (GA), particle swarm optimization (PSO), and AFSA. Results demonstrate that the proposed model outperforms other models and may provide alarms for safety control.<\/jats:p>","DOI":"10.1155\/2020\/5463893","type":"journal-article","created":{"date-parts":[[2020,10,29]],"date-time":"2020-10-29T03:05:10Z","timestamp":1603940710000},"page":"1-13","source":"Crossref","is-referenced-by-count":19,"title":["On the Use of an Improved Artificial Fish Swarm Algorithm-Backpropagation Neural Network for Predicting Dam Deformation Behavior"],"prefix":"10.1155","volume":"2020","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-4992-9972","authenticated-orcid":true,"given":"Bo","family":"Dai","sequence":"first","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China"},{"name":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5411-9571","authenticated-orcid":true,"given":"Hao","family":"Gu","sequence":"additional","affiliation":[{"name":"College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China"},{"name":"College of Agricultural Engineering, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8066-0794","authenticated-orcid":true,"given":"Yantao","family":"Zhu","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China"},{"name":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-1070-9761","authenticated-orcid":true,"given":"Siyu","family":"Chen","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China"},{"name":"College of Water Conservancy and Hydropower Engineering, Hohai University, Nanjing 210098, China"},{"name":"National Engineering Research Center of Water Resources Efficient Utilization and Engineering Safety, Hohai University, Nanjing 210098, China"}]},{"given":"E. Fernandez","family":"Rodriguez","sequence":"additional","affiliation":[{"name":"Technological Institute of Merida, Technological Avenue, Merida 97219, Mexico"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1111\/j.1539-6924.1993.tb01069.x"},{"key":"2","volume-title":"Safety Monitoring of Dams and Dam Foundations-Theories & Methods and Their Application","author":"C. Gu","year":"2006"},{"key":"3","doi-asserted-by":"publisher","DOI":"10.1016\/j.ymssp.2018.03.022"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.strusafe.2015.05.001"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1002\/stc.1575"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1016\/j.aei.2018.11.006"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.engstruct.2018.05.084"},{"key":"8","doi-asserted-by":"publisher","DOI":"10.1016\/j.advengsoft.2013.06.019"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijrmms.2009.09.011"},{"key":"10","doi-asserted-by":"publisher","DOI":"10.2514\/2.2111"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1109\/tsmc.2019.2956121"},{"key":"12","doi-asserted-by":"publisher","DOI":"10.1016\/j.swevo.2019.02.004"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1177\/003754970107600201"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.3390\/app6060164"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1016\/j.strusafe.2014.02.004"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2016.05.031"},{"key":"17","doi-asserted-by":"publisher","DOI":"10.1109\/tnnls.2018.2846646"},{"key":"18","doi-asserted-by":"publisher","DOI":"10.1016\/j.engstruct.2016.04.012"},{"key":"19","doi-asserted-by":"publisher","DOI":"10.1007\/s11831-015-9157-9"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1177\/1369433218788635"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.1002\/stc.1997"},{"key":"22","doi-asserted-by":"publisher","DOI":"10.1016\/j.engstruct.2010.12.011"},{"key":"23","doi-asserted-by":"publisher","DOI":"10.1016\/j.neucom.2019.09.110"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1007\/s00366-020-00956-6"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1007\/s10704-006-6582-7"},{"key":"26","doi-asserted-by":"publisher","DOI":"10.1155\/2016\/6858697"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1155\/2018\/1712653"},{"key":"28","doi-asserted-by":"publisher","DOI":"10.1038\/323533a0"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1155\/2019\/1467565"},{"key":"30","volume-title":"Brief Introduction of Back Propagation (BP) Neural Network Algorithm and its Improvement","author":"J. Li","year":"2012"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.1038\/nature14539"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1109\/34.107014"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1093\/ietfec\/e88-a.12.3645"},{"key":"34","doi-asserted-by":"publisher","DOI":"10.1155\/2017\/2586107"},{"key":"35","volume-title":"A New Intelligent Optimization-Artificial Fish Swarm Algorithm","author":"X. Li","year":"2003"},{"key":"36","doi-asserted-by":"publisher","DOI":"10.1007\/s10462-012-9342-2"},{"key":"37","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2010.11.001"},{"key":"38","doi-asserted-by":"publisher","DOI":"10.1111\/j.1467-8667.2007.00499.x"},{"key":"39","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijepes.2014.05.017"},{"key":"40","doi-asserted-by":"crossref","article-title":"Flocks, herds and schools: a distributed behavioral model","author":"C. W. Reynolds","DOI":"10.1145\/280811.281008"},{"key":"41","doi-asserted-by":"publisher","DOI":"10.3390\/s19092047"},{"key":"42","first-page":"7","volume-title":"Approximation With Artificial Neural Networks","author":"B. C. Cs\u00e1ji","year":"2001"},{"key":"43","doi-asserted-by":"publisher","DOI":"10.1007\/bf02551274"},{"key":"44","doi-asserted-by":"crossref","DOI":"10.1007\/978-0-387-84858-7","volume-title":"The Elements of Statistical Learning: Data Mining, Inference, and Prediction","author":"T. Hastie","year":"2009"},{"key":"45","first-page":"65","article-title":"Theory of the backpropagation neural network","volume-title":"Neural Networks for Perception","author":"R. Hecht-Nielsen","year":"1992"},{"key":"46","first-page":"395","article-title":"Predicting sunspots and exchange rates with connectionist networks","author":"A. Weigend","year":"1992","journal-title":"Nonlinear Modelling Forecasting"},{"key":"47","doi-asserted-by":"crossref","DOI":"10.1007\/978-3-030-36808-1_31","article-title":"Deep neural network hyperparameter optimization with orthogonal array tuning","volume-title":"International Conference on Neural Information Processing","author":"X. Zhang","year":"2019"},{"key":"48","article-title":"Hyper-parameter optimization: a review of algorithms and applications","author":"T. Yu","year":"2020"},{"key":"49","volume-title":"Kolmogorov\u2019s Mapping Neural Network Existence Theorem","author":"R. Hecht-Nielsen","year":"1957"}],"container-title":["Complexity"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/5463893.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/5463893.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/complexity\/2020\/5463893.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,10,29]],"date-time":"2020-10-29T03:05:15Z","timestamp":1603940715000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/complexity\/2020\/5463893\/"}},"subtitle":[],"editor":[{"given":"Zong Woo","family":"Geem","sequence":"additional","affiliation":[]}],"short-title":[],"issued":{"date-parts":[[2020,10,28]]},"references-count":49,"alternative-id":["5463893","5463893"],"URL":"https:\/\/doi.org\/10.1155\/2020\/5463893","relation":{},"ISSN":["1099-0526","1076-2787"],"issn-type":[{"value":"1099-0526","type":"electronic"},{"value":"1076-2787","type":"print"}],"subject":[],"published":{"date-parts":[[2020,10,28]]}}}