{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,2,22]],"date-time":"2025-02-22T05:27:10Z","timestamp":1740202030495,"version":"3.37.3"},"reference-count":0,"publisher":"IOS Press","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"abstract":"<jats:p>Structural failure classification for the reinforced concrete (RC) buildings is one of the machine learning challenging tasks. Several successful studies were conducted to train the Neural Network (NN) with well-known optimization techniques. In the current work, a cuckoo search (CS) based classification model of structural failure of the RC buildings was proposed. The proposed NN-CS system was compared to well-known models, namely the Multilayer perceptron feed-forward network (MLP-FFN) trained with scaled conjugate gradient descent and the NN supported by the Particle swarm optimization algorithm (NN-PSO). The performance metrics, including the accuracy, precision, recall, and F-measure were calculated. The experimental results established the superiority of the proposed NN-CS with reasonable improvement (93.33% accuracy) compared to the other models.<\/jats:p>","DOI":"10.3233\/978-1-61499-939-3-58","type":"book-chapter","created":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T10:26:53Z","timestamp":1740133613000},"source":"Crossref","is-referenced-by-count":0,"title":["Structural Failure Prediction in Multi Storied Reinforced Concrete Buildings Using Cuckoo Search Optimization Combined with Neural Network"],"prefix":"10.3233","author":[{"family":"Chatterjee Sankhadeep","sequence":"additional","affiliation":[]},{"family":"Dey Nilanjan","sequence":"additional","affiliation":[]},{"family":"Ashour Amira S.","sequence":"additional","affiliation":[]},{"family":"Sen Soumya","sequence":"additional","affiliation":[]},{"family":"Shi Fuqian","sequence":"additional","affiliation":[]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Information Technology and Intelligent Transportation Systems"],"original-title":[],"deposited":{"date-parts":[[2025,2,21]],"date-time":"2025-02-21T11:07:36Z","timestamp":1740136056000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.medra.org\/servlet\/aliasResolver?alias=iospressISBN&isbn=978-1-61499-938-6&spage=58&doi=10.3233\/978-1-61499-939-3-58"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/978-1-61499-939-3-58","relation":{},"ISSN":["0922-6389"],"issn-type":[{"value":"0922-6389","type":"print"}],"subject":[],"published":{"date-parts":[[2019]]}}}