{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T00:51:31Z","timestamp":1701478291222},"reference-count":0,"publisher":"IOS Press","isbn-type":[{"value":"9781643684444","type":"print"},{"value":"9781643684451","type":"electronic"}],"license":[{"start":{"date-parts":[[2023,11,30]],"date-time":"2023-11-30T00:00:00Z","timestamp":1701302400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2023,11,30]]},"abstract":"<jats:p>Household consumption is an important part of stimulating domestic demand, developing the economy and promoting the steady growth of China\u2019s GDP. In this paper, the consumption levels of residents in cities in Henan Province are obtained through factor analysis. There are obvious differences among regions, which can be divided into three levels according to the comprehensive score: high-consumption cities, medium-consumption cities and low-consumption cities. Secondly, the BP neural network is used to train the model using MATLAB software, with 8 evaluation indicators as the input layer and resident consumption level as the output layer. The prediction results show that the prediction accuracy of BP neural network has reached 83.33%, which is highly scientific and reasonable. It can add a new perspective to predict the consumption level of residents, provide scientific research data for urban consumption departments, improve the residents\u2019 awareness of reasonable expenditure in Henan Province, and drive the economic development of Henan Province.<\/jats:p>","DOI":"10.3233\/faia230843","type":"book-chapter","created":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:54:39Z","timestamp":1701446079000},"source":"Crossref","is-referenced-by-count":0,"title":["Application of BP Neural Network in the Prediction of Residents\u2019 Consumption Level"],"prefix":"10.3233","author":[{"given":"Hong","family":"Han","sequence":"first","affiliation":[{"name":"Henan University of Science and Technology"}]},{"given":"Yuehua","family":"Duan","sequence":"additional","affiliation":[{"name":"Henan University of Science and Technology"}]}],"member":"7437","container-title":["Frontiers in Artificial Intelligence and Applications","Advances in Artificial Intelligence, Big Data and Algorithms"],"original-title":[],"link":[{"URL":"https:\/\/ebooks.iospress.nl\/pdf\/doi\/10.3233\/FAIA230843","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,12,1]],"date-time":"2023-12-01T15:54:48Z","timestamp":1701446088000},"score":1,"resource":{"primary":{"URL":"https:\/\/ebooks.iospress.nl\/doi\/10.3233\/FAIA230843"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,30]]},"ISBN":["9781643684444","9781643684451"],"references-count":0,"URL":"https:\/\/doi.org\/10.3233\/faia230843","relation":{},"ISSN":["0922-6389","1879-8314"],"issn-type":[{"value":"0922-6389","type":"print"},{"value":"1879-8314","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,30]]}}}