{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T08:27:34Z","timestamp":1760171254596,"version":"3.41.2"},"reference-count":31,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,12,22]],"date-time":"2021-12-22T00:00:00Z","timestamp":1640131200000},"content-version":"vor","delay-in-days":355,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"\u201c13th Five-Year Plan\u201d of Shaanxi Education Sciences Planning","award":["SGH20Y1170"],"award-info":[{"award-number":["SGH20Y1170"]}]}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Computational Intelligence and Neuroscience"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>With the development of neural networks in deep learning, artificial intelligence machine learning has become the main focus of researchers. In College English grammar detection, oral grammar is the most error rate content. So, this paper optimizes MLP based on GA in the deep learning neural network and then studies the intelligent image correction of College English spoken grammar. The main direction is to discuss and analyze GA\u2010MLP\u2010NN algorithm technology first and then predict the error correction model of spoken language grammar by combining the optimized algorithm. The results show that GA\u2010MLP\u2010NN provides excellent accuracy for the prediction of the whole syntax error correction model. Then, the paper studies the deep learning technology to build an intelligent image error correction model of College English spoken grammar. The results show that the effect of intelligent correction of spoken grammar is very fast and accurate.<\/jats:p>","DOI":"10.1155\/2021\/7371416","type":"journal-article","created":{"date-parts":[[2021,12,23]],"date-time":"2021-12-23T03:51:56Z","timestamp":1640231516000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Intelligent Error Correction of College English Spoken Grammar Based on the GA\u2010MLP\u2010NN Algorithm"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-1824-392X","authenticated-orcid":false,"given":"Yining","family":"Du","sequence":"first","affiliation":[]}],"member":"311","published-online":{"date-parts":[[2021,12,22]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.3390\/su13179898"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1080\/15502724.2020.1755306"},{"key":"e_1_2_9_3_2","first-page":"58","article-title":"Remote sensing image segmentation method based on neural network","volume":"10","author":"Ding T. 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