{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,29]],"date-time":"2025-10-29T13:53:05Z","timestamp":1761745985174,"version":"3.40.3"},"publisher-location":"Singapore","reference-count":24,"publisher":"Springer Nature Singapore","isbn-type":[{"type":"print","value":"9789819722747"},{"type":"electronic","value":"9789819722754"}],"license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2024]]},"DOI":"10.1007\/978-981-97-2275-4_10","type":"book-chapter","created":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T19:02:10Z","timestamp":1713207730000},"page":"121-132","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Prediction of Rice Processing Loss Rate Based on GA-BP Neural Network"],"prefix":"10.1007","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-6845-6125","authenticated-orcid":false,"given":"Hua","family":"Yang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jian","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Neng","family":"Liu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Kecheng","family":"Yi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jing","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rou","family":"Fu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jun","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yunzhu","family":"Xiang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pengcheng","family":"Yang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyu","family":"Hang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tiancheng","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Siyi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,4,16]]},"reference":[{"issue":"05","key":"10_CR1","first-page":"27","volume":"47","author":"HQ Li","year":"2019","unstructured":"Li, H.Q., Zhao, Y.Q., Yan, Q., Lin, F.: Vehicle Wheel matching and vehicle reverse dynamics based on genetic neural network. J. Huazhong Univ. Sci. Technol. (Nat. Sci. Edition) 47(05), 27\u201332 (2019)","journal-title":"J. Huazhong Univ. Sci. Technol. (Nat. Sci. Edition)"},{"key":"10_CR2","unstructured":"Liu, M.C.: Road Scene Recognition of Substation Inspection Robot Based on Deep Learning. Southwest Jiaotong University (2019)"},{"issue":"3","key":"10_CR3","doi-asserted-by":"publisher","first-page":"1134","DOI":"10.1109\/TNNLS.2020.3040969","volume":"33","author":"Q Yu","year":"2022","unstructured":"Yu, Q., Song, S., Ma, C., Pan, L., Tan, K.C.: Synaptic learning with augmented spikes. IEEE Trans. Neural Netw. Learn. Syst. 33(3), 1134\u20131146 (2022)","journal-title":"IEEE Trans. Neural Netw. Learn. Syst."},{"key":"10_CR4","doi-asserted-by":"publisher","first-page":"127006","DOI":"10.1016\/j.energy.2023.127006","volume":"271","author":"QN Zhu","year":"2023","unstructured":"Zhu, Q.N., Jiang, F., Li, C.S.: Time-varying interval prediction and decision-making for short-term wind power using convolutional gated recurrent unit and multi-objective elephant clan optimization. Energy 271, 127006 (2023)","journal-title":"Energy"},{"key":"10_CR5","doi-asserted-by":"publisher","first-page":"109602","DOI":"10.1016\/j.asoc.2022.109602","volume":"129","author":"F Jiang","year":"2022","unstructured":"Jiang, F., Zhu, Q., Yang, J., Chen, G., Tian, T.: Clustering-based interval prediction of electric load using multi-objective pathfinder algorithm and Elman neural network. Appl. Soft Comput. 129, 109602 (2022)","journal-title":"Appl. Soft Comput."},{"issue":"2","key":"10_CR6","doi-asserted-by":"publisher","first-page":"171","DOI":"10.3969\/j.issn.1000-2375.2022.00.089","volume":"45","author":"H Yang","year":"2023","unstructured":"Yang, H., Liu, T.Q., et al.: Harmony search algorithm based on membrane computing framework and its application. J. Hubei Univ. (Nat. Sci. Edition) 45(2), 171\u2013180 (2023). https:\/\/doi.org\/10.3969\/j.issn.1000-2375.2022.00.089","journal-title":"J. Hubei Univ. (Nat. Sci. Edition)"},{"issue":"18","key":"10_CR7","doi-asserted-by":"publisher","first-page":"10188","DOI":"10.3390\/app131810188","volume":"13","author":"H Yang","year":"2023","unstructured":"Yang, H., Lin, D., Zhang, G., Zhang, H., Wang, J., Zhang, S.: Research on detection of rice pests and diseases based on improved YOLOV5 algorithm. Appl. Sci. 13(18), 10188 (2023). https:\/\/doi.org\/10.3390\/app131810188","journal-title":"Appl. Sci."},{"issue":"05","key":"10_CR8","first-page":"80","volume":"37","author":"WQ You","year":"2020","unstructured":"You, W.Q., Zhuang, K.J.: Combination prediction of grain production in china based on the IOWA operator. J. Chongqing Technol. Bus. Univ. (Nat. Sci. Edition) 37(05), 80\u201387 (2020)","journal-title":"J. Chongqing Technol. Bus. Univ. (Nat. Sci. Edition)"},{"issue":"5","key":"10_CR9","first-page":"227","volume":"42","author":"H Wang","year":"2020","unstructured":"Wang, H., Fu, H.Y., Wang, J.L., et al.: Comparative study on heterogeneous estimation models of ramie yield based on multiple regression and BP neural network. China Flax 42(5), 227\u2013238 (2020)","journal-title":"China Flax"},{"issue":"2","key":"10_CR10","first-page":"341","volume":"35","author":"JQ Zhang","year":"2009","unstructured":"Zhang, J.Q., Zhang, L.X., Zhang, M.H., et al.: Prediction of soybean growth and development stages using neural network and statistical models. Acta Agron. Sin. 35(2), 341\u2013347 (2009)","journal-title":"Acta Agron. Sin."},{"issue":"2","key":"10_CR11","first-page":"434","volume":"35","author":"C Fan","year":"2023","unstructured":"Fan, C., Zhao, Z.H., Zhang, X.S., et al.: Forecasting model of first-season rice development stage based on BP neural network. J. Zhejiang Agric. Sci. 35(2), 434\u2013444 (2023)","journal-title":"J. Zhejiang Agric. Sci."},{"issue":"1","key":"10_CR12","doi-asserted-by":"publisher","first-page":"271","DOI":"10.1007\/s40747-021-00362-5","volume":"8","author":"J Lin","year":"2022","unstructured":"Lin, J., He, C., Cheng, R.: Adaptive dropout for high-dimensional expensive multiobjective optimization. Complex Intell. Syst. 8(1), 271\u2013285 (2022)","journal-title":"Complex Intell. Syst."},{"issue":"11","key":"10_CR13","first-page":"1842","volume":"32","author":"YQ Xing","year":"2023","unstructured":"Xing, Y.Q., Zhou, J., Huang, W.L., et al.: Prediction model of wheat fusarium head blight based on BP neural network in rice-wheat rotation areas. Acta Agriculturae Boreali-occidentalis Sinica 32(11), 1842\u20131848 (2023)","journal-title":"Acta Agriculturae Boreali-occidentalis Sinica"},{"issue":"06","key":"10_CR14","first-page":"712","volume":"41","author":"JY Lei","year":"2022","unstructured":"Lei, J.Y., Ye, S., Xia, M., et al.: Grape leaf disease detection based on improved YOLOv4. J. South-Cent. Univ. Natl. (Nat. Sci. Edition) 41(06), 712\u2013719 (2022)","journal-title":"J. South-Cent. Univ. Natl. (Nat. Sci. Edition)"},{"issue":"1","key":"10_CR15","first-page":"71","volume":"41","author":"W Wang","year":"2022","unstructured":"Wang, W., Liu, M., Zhao, Z., et al.: Improved convolutional neural network method for classification of apple leaves. J. South-Cent. Univ. Natl. (Nat. Sci. Edition) 41(1), 71\u201378 (2022)","journal-title":"J. South-Cent. Univ. Natl. (Nat. Sci. Edition)"},{"issue":"04","key":"10_CR16","first-page":"489","volume":"42","author":"TY Mao","year":"2023","unstructured":"Mao, T.Y., Zhu, J.J., Tie, J., et al.: Research on tea bud recognition method based on anchor-free detection network. J. South-Cent. Univ. Natl. (Nat. Sci. Edition) 42(04), 489\u2013496 (2023)","journal-title":"J. South-Cent. Univ. Natl. (Nat. Sci. Edition)"},{"issue":"7","key":"10_CR17","doi-asserted-by":"publisher","first-page":"1361","DOI":"10.3390\/AGRICULTURE13071361","volume":"13","author":"H Yang","year":"2023","unstructured":"Yang, H., Deng, X., Shen, H., Lei, Q., Zhang, S., Liu, N.: Disease detection and identification of rice leaf based on improved detection transformer. Agriculture 13(7), 1361 (2023). https:\/\/doi.org\/10.3390\/AGRICULTURE13071361","journal-title":"Agriculture"},{"key":"10_CR18","doi-asserted-by":"publisher","unstructured":"Yang, H., Wu, Y.F., at al.: Application of decomposition-based deep learning model in temperature prediction of grain piles. J. South-Central Univ. Natl. (Nat. Sci. Edition) 42(05), 696\u2013701 (2023). https:\/\/doi.org\/10.20056\/j.cnki.ZNMDZK.20230516","DOI":"10.20056\/j.cnki.ZNMDZK.20230516"},{"issue":"3","key":"10_CR19","first-page":"5","volume":"40","author":"K Tian","year":"2014","unstructured":"Tian, K., Sun, Y.T., Gao, H., et al.: Quantitative research on defects of BP neural network based on Bayesian algorithm. China Meas. Test. 40(3), 5 (2014)","journal-title":"China Meas. Test."},{"issue":"S2","key":"10_CR20","first-page":"34","volume":"35","author":"XM Ma","year":"2013","unstructured":"Ma, X.M., Wang, X.: Improvement of BP neural network based on genetic algorithm. J. Yunnan Univ. (Nat. Sci. Edition) 35(S2), 34\u201338 (2013)","journal-title":"J. Yunnan Univ. (Nat. Sci. Edition)"},{"key":"10_CR21","unstructured":"Liang, Y.: Research on Fermentation of Lactic Acid Bacteria and Yeast Fermented Rice Noodle Slurry and Preparation of Rice Bread. South China University of Technology (2019)"},{"issue":"11","key":"10_CR22","first-page":"147","volume":"35","author":"XP Lan","year":"2020","unstructured":"Lan, X.P., Chen, J.Y., Jiang, Y.J., et al.: Construction of grain storage quality prediction model based on BP neural network algorithm. J. China Cereals Oils Assoc. 35(11), 147\u2013151 (2020)","journal-title":"J. China Cereals Oils Assoc."},{"key":"10_CR23","doi-asserted-by":"crossref","unstructured":"Chen, Y., Xu, J., Yu, H., Zhen, Z., Li, D.: Three-dimensional short-term prediction model of dissolved oxygen content based on pso-bpann algorithm coupled with kriging interpolation. Math. Probl. Eng. (2016)","DOI":"10.1155\/2016\/6564202"},{"issue":"1","key":"10_CR24","first-page":"34","volume":"36","author":"LJ Guo","year":"2023","unstructured":"Guo, L.J., Qiao, Z.Z.: Research on grain temperature prediction based on genetic algorithm optimized BP neural network. Grain Oil 36(1), 34\u201337 (2023)","journal-title":"Grain Oil"}],"container-title":["Communications in Computer and Information Science","Bio-Inspired Computing: Theories and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-981-97-2275-4_10","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,4,15]],"date-time":"2024-04-15T19:14:31Z","timestamp":1713208471000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-981-97-2275-4_10"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024]]},"ISBN":["9789819722747","9789819722754"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-981-97-2275-4_10","relation":{},"ISSN":["1865-0929","1865-0937"],"issn-type":[{"type":"print","value":"1865-0929"},{"type":"electronic","value":"1865-0937"}],"subject":[],"published":{"date-parts":[[2024]]},"assertion":[{"value":"16 April 2024","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"BIC-TA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Bio-Inspired Computing: Theories and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Changsha","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":"2023","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"15 December 2023","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"17 December 2023","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"18","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"bicta2023","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/2023.bicta.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Single-blind","order":1,"name":"type","label":"Type","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"EasyChair","order":2,"name":"conference_management_system","label":"Conference Management System","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"168","order":3,"name":"number_of_submissions_sent_for_review","label":"Number of Submissions Sent for Review","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"64","order":4,"name":"number_of_full_papers_accepted","label":"Number of Full Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"0","order":5,"name":"number_of_short_papers_accepted","label":"Number of Short Papers Accepted","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"38% - The value is computed by the equation \"Number of Full Papers Accepted \/ Number of Submissions Sent for Review * 100\" and then rounded to a whole number.","order":6,"name":"acceptance_rate_of_full_papers","label":"Acceptance Rate of Full Papers","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"3","order":7,"name":"average_number_of_reviews_per_paper","label":"Average Number of Reviews per Paper","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"4","order":8,"name":"average_number_of_papers_per_reviewer","label":"Average Number of Papers per Reviewer","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}},{"value":"Yes","order":9,"name":"external_reviewers_involved","label":"External Reviewers Involved","group":{"name":"ConfEventPeerReviewInformation","label":"Peer Review Information (provided by the conference organizers)"}}]}}