{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:27:01Z","timestamp":1747189621866,"version":"3.40.5"},"reference-count":19,"publisher":"World Scientific Pub Co Pte Ltd","issue":"14","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Patt. Recogn. Artif. Intell."],"published-print":{"date-parts":[[2020,12,30]]},"abstract":"<jats:p> The corrosion of reinforcement has always been a problem to be solved in the field of architecture. In this paper, the corrosion characteristics of chromium alloy steel under different pH conditions are studied. The impedance characteristics and equivalent circuit are predicted by neural network model. First of all, in simulated pore solution with different pH values, the characteristics of Nyquist impedance spectroscopy of the whole chromium alloy under passivation stage and the damaged passivation film of reinforcing bars under initial corrosion stage have been found. Then, according to the difference of impedance characteristics under different pH values, different equivalent circuits have been established and [Formula: see text] values of different equivalent circuits under different chloride ion concentration have been calculated. By fitting the electrochemical parameters of the equivalent circuit with [Formula: see text] values, the equivalent circuit model which can be predicted by neural network has good consistency with the equivalent circuit which can be predicted by [Formula: see text] values. <\/jats:p>","DOI":"10.1142\/s0218001420590478","type":"journal-article","created":{"date-parts":[[2020,2,21]],"date-time":"2020-02-21T08:21:22Z","timestamp":1582273282000},"page":"2059047","source":"Crossref","is-referenced-by-count":1,"title":["Prediction and Analysis of Reinforcement Corrosion in Simulated Concrete Pore Solution Based on Neural Network"],"prefix":"10.1142","volume":"34","author":[{"given":"Fengjiao","family":"Jiang","sequence":"first","affiliation":[{"name":"College of Information Engineering, Dalian Ocean University, Dalian, P.\u00a0R.\u00a0China"},{"name":"Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, P.\u00a0R.\u00a0China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8227-2928","authenticated-orcid":false,"given":"Jinxin","family":"Gong","sequence":"additional","affiliation":[{"name":"Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, P.\u00a0R.\u00a0China"}]},{"given":"Jichao","family":"Zhu","sequence":"additional","affiliation":[{"name":"School of Civil Safety Engineering, Dalian Jiaotong University, Dalian, P.\u00a0R.\u00a0China"}]},{"given":"Huan","family":"Wang","sequence":"additional","affiliation":[{"name":"Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, P.\u00a0R.\u00a0China"}]},{"given":"Weibo","family":"Song","sequence":"additional","affiliation":[{"name":"College of Information Engineering, Dalian Ocean University, Dalian, P.\u00a0R.\u00a0China"},{"name":"Faculty of Infrastructure Engineering, Dalian University of Technology, Dalian, P.\u00a0R.\u00a0China"}]}],"member":"219","published-online":{"date-parts":[[2020,5,4]]},"reference":[{"key":"S0218001420590478BIB001","doi-asserted-by":"crossref","first-page":"1126","DOI":"10.1016\/j.apsusc.2016.07.142","volume":"389","author":"Ai Z.","year":"2016","journal-title":"Appl. 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