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Experiments show that compared with the traditional BP neural network, the proposed method can effectively improve the accuracy and stability of the prediction. There is a nonlinear correlation between reservoir reconstruction data and gas well production, which does not apply to traditional linear prediction methods<\/jats:p>","DOI":"10.3233\/jifs-189279","type":"journal-article","created":{"date-parts":[[2020,9,15]],"date-time":"2020-09-15T09:16:38Z","timestamp":1600161398000},"page":"8823-8830","source":"Crossref","is-referenced-by-count":3,"title":["Economic benefit of shale gas exploitation based on back propagation neural network"],"prefix":"10.1177","volume":"39","author":[{"given":"Jiafeng","family":"Li","sequence":"first","affiliation":[{"name":"School of Economics and Management, Wuhan University, Hubei, China"}]},{"given":"Hui","family":"Hu","sequence":"additional","affiliation":[{"name":"Economic Development Research Centre, Wuhan University, Hubei, China"}]},{"given":"Xiang","family":"Li","sequence":"additional","affiliation":[{"name":"Carroll School of Management, Boston College, MA 02467, United 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