{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,27]],"date-time":"2025-03-27T13:22:23Z","timestamp":1743081743241,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":19,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789811684296"},{"type":"electronic","value":"9789811684302"}],"license":[{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,1]],"date-time":"2022-01-01T00:00:00Z","timestamp":1640995200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2022]]},"DOI":"10.1007\/978-981-16-8430-2_8","type":"book-chapter","created":{"date-parts":[[2022,1,4]],"date-time":"2022-01-04T18:02:42Z","timestamp":1641319362000},"page":"82-91","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A Mill Control System Based on GA-BP Network for Output Prediction"],"prefix":"10.1007","author":[{"given":"Hongwei","family":"Ren","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sheng","family":"Zheng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyu","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,1,4]]},"reference":[{"doi-asserted-by":"crossref","unstructured":"Dazhi, W., Qiang, W., Qingbo, M., et al.: High temperature-assisted electrohydrodynamic jet printing of sintered type nano silver ink on a heated substrate. J. Micromechanics Microeng 29(4), 045012 (2019)","key":"8_CR1","DOI":"10.1088\/1361-6439\/ab0739"},{"doi-asserted-by":"crossref","unstructured":"Johnson Chelsea, E., Martin, P., Roberts Katherine, A., et al.: The Capability of Raman Microspectroscopy to Differentiate Printing Inks. J. Forensic Sci. 63(1), 66\u201379 (2018)","key":"8_CR2","DOI":"10.1111\/1556-4029.13508"},{"doi-asserted-by":"crossref","unstructured":"Gu, W., Li, Y.,  Zhang, X.: Printing industry and the environment. Adv. Mater. Res. 663, 759\u2013762 (2013)","key":"8_CR3","DOI":"10.4028\/www.scientific.net\/AMR.663.759"},{"doi-asserted-by":"crossref","unstructured":"Gao, P.,  Zhou, W., Han, Y., et al.: Enhancing the capacity of large-scale ball mill through process and equipment optimization: an industrial test verification. Adv. Powder Technol. 31(5), 2079\u20132091(2020)","key":"8_CR4","DOI":"10.1016\/j.apt.2020.03.001"},{"unstructured":"Liu, Z., Zhen, C.: Modeling of complex equipment coal mill in power plant. Int. Core J. Eng. 5(7), 10\u201316 (2019)","key":"8_CR5"},{"doi-asserted-by":"crossref","unstructured":"Xu, J., Jun, T., Zhao, T., et al.: Research on intelligent prediction and forecast model for construction period of transmission and transformation engineering based on bp neural network\u201d.\u00a0In: IOP Conference Series: Earth and Environmental Science, vol. 687(1), p. 012154 (2021)","key":"8_CR6","DOI":"10.1088\/1755-1315\/687\/1\/012154"},{"doi-asserted-by":"crossref","unstructured":"Zhu, W., Wang, H., Zhang, X.: Synergy evaluation model of container multimodal transport based on BP neural network. Neural Comput. Appl. 33(9), 4087\u20134095 (2021)","key":"8_CR7","DOI":"10.1007\/s00521-020-05584-1"},{"doi-asserted-by":"crossref","unstructured":"Dou, K., Sun, X.: Long-term weather prediction based on GA-BP neural network. In: IOP Conference Series: Earth and Environmental Science, vol. 668(1), p. 012015 (2021)","key":"8_CR8","DOI":"10.1088\/1755-1315\/668\/1\/012015"},{"doi-asserted-by":"crossref","unstructured":"Huang, D.J., Tian, C.C., Jiang, J.Y., et al.: Application of GA-BP neural network model for small watershed flood forecasting in Chun\u2019an county, China. In: IOP Conference Series: Earth and Environmental Science, vol. 612(1), p. 012066 (2020)","key":"8_CR9","DOI":"10.1088\/1755-1315\/612\/1\/012066"},{"doi-asserted-by":"crossref","unstructured":"Liang, H., Wei, Q., Lu, D., et al.: Application of GA-BP neural network algorithm in killing well control system. Neural Comput. Appl. 33(3), 1\u201312 (2020)","key":"8_CR10","DOI":"10.1007\/s00521-020-05298-4"},{"doi-asserted-by":"crossref","unstructured":"Bortnowski, P., G\u0142adysiewicz, L., Ozdoba, M., et al.: Energy efficiency analysis of copper ore ball mill drive systems. Energies 14(6), 1786\u20131786 (2021).","key":"8_CR11","DOI":"10.3390\/en14061786"},{"doi-asserted-by":"crossref","unstructured":"Huang, L., Xie, G., Zhao, W., et al.: Regional logistics demand forecasting: a BP neural network approach.\u00a0Complex  Intell. Syst. (C31), 1\u201316 (2021)","key":"8_CR12","DOI":"10.1007\/s40747-021-00297-x"},{"doi-asserted-by":"crossref","unstructured":"Qiao, X., Guo, F., Zhang, R., et al.: Short-term tidal current prediction based on GA-BP neural network. In: IOP Conference Series. Earth and Environmental Science, vol. 513(1), p. 012061 (2020)","key":"8_CR13","DOI":"10.1088\/1755-1315\/513\/1\/012061"},{"doi-asserted-by":"crossref","unstructured":"Han, Q.Y., Qian, L.J.,  Chu, X.Y.: Study on energy consumption prediction of liquor-making based on GA-BP neural net. Appl. Mech. Mater. 3485, 1681\u20131687 (2014)","key":"8_CR14","DOI":"10.4028\/www.scientific.net\/AMM.635-637.1681"},{"doi-asserted-by":"crossref","unstructured":"Zhang, S., Hu, Q.: Students' comprehensive quality evaluation based on BP neural network optimized by genetic algorithm. Xi'an institute of posts and telecommunications. In: Proceedings of the 2nd International Conference on Education, E-learning and Management Technology, pp. 6\u20137. Xi'an Institute of Posts and Telecommunications (2017)","key":"8_CR15","DOI":"10.12783\/dtssehs\/eemt2017\/14560"},{"doi-asserted-by":"crossref","unstructured":"Tan, T., Yang, Z.,  Chang, F., et al.: Prediction of the first weighting from the working face roof in a coal mine based on a GA-BP neural network. Appl. Sci. 9(19), 4159 (2019)","key":"8_CR16","DOI":"10.3390\/app9194159"},{"doi-asserted-by":"crossref","unstructured":"Zheng, L., Xin, L., Kan, W., et al.: GA-BP neural network-based strain prediction in full-scale static testing of wind Turbine blades. Energies 12(6), 1026 (2019)","key":"8_CR17","DOI":"10.3390\/en12061026"},{"doi-asserted-by":"crossref","unstructured":"J, Tang., W X, Li., B, Zhao.: The application of GA-BP algorithm in prediction of tool wear state. In: IOP Conference Series: Materials Science and Engineering, vol. 398(1) (2018)","key":"8_CR18","DOI":"10.1088\/1757-899X\/398\/1\/012025"},{"unstructured":"Guo, B., Xu, J., Ling, C., et al.: Prediction of the heat load in central heating systems using GA-BP algorithm. Int. J. Adv. Network Monit. Controls 2(4), 137\u2013141 (2018)","key":"8_CR19"}],"container-title":["Lecture Notes in Electrical Engineering","Genetic and Evolutionary Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-16-8430-2_8","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,5,5]],"date-time":"2022-05-05T17:07:31Z","timestamp":1651770451000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-16-8430-2_8"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022]]},"ISBN":["9789811684296","9789811684302"],"references-count":19,"URL":"https:\/\/doi.org\/10.1007\/978-981-16-8430-2_8","relation":{},"ISSN":["1876-1100","1876-1119"],"issn-type":[{"type":"print","value":"1876-1100"},{"type":"electronic","value":"1876-1119"}],"subject":[],"published":{"date-parts":[[2022]]},"assertion":[{"value":"4 January 2022","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICGEC","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Genetic and Evolutionary Computing","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Jilin City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"China","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2021","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"21 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"23 October 2021","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"14","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"icgec2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}