{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,26]],"date-time":"2025-03-26T04:30:52Z","timestamp":1742963452240,"version":"3.40.3"},"publisher-location":"Cham","reference-count":26,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030891336"},{"type":"electronic","value":"9783030891343"}],"license":[{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2021,1,1]],"date-time":"2021-01-01T00:00:00Z","timestamp":1609459200000},"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":[[2021]]},"DOI":"10.1007\/978-3-030-89134-3_48","type":"book-chapter","created":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T10:39:41Z","timestamp":1634467181000},"page":"524-535","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Inverse Determination of B340LA Material Parameters in Bending Springback Process by Dynamic Optimization Approach"],"prefix":"10.1007","author":[{"given":"Zhefeng","family":"Guo","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Li","family":"Liang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Tianyue","family":"Zhou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Huixian","family":"Zhang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Limin","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2021,10,18]]},"reference":[{"issue":"5-8","key":"48_CR1","doi-asserted-by":"publisher","first-page":"1095","DOI":"10.1007\/s00170-014-6532-x","volume":"79","author":"D-K Leu","year":"2015","unstructured":"Leu, D.-K.: Position deviation and springback in V-die bending process with asymmetric dies. Int. J. Adv. Manuf. Technol. 79(5\u20138), 1095\u20131108 (2015). https:\/\/doi.org\/10.1007\/s00170-014-6532-x","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"48_CR2","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s00170-014-6190-z","volume":"76","author":"Y Zong","year":"2014","unstructured":"Zong, Y., Liu, P., Guo, B., Shan, D.: Springback evaluation in hot v-bending of Ti-6Al-4V alloy sheets. Int. J. Adv. Manuf. Technol. 76, 1\u20139 (2014). https:\/\/doi.org\/10.1007\/s00170-014-6190-z","journal-title":"Int. J. Adv. Manuf. Technol."},{"issue":"9","key":"48_CR3","doi-asserted-by":"publisher","first-page":"3287","DOI":"10.1007\/s11771-015-2868-0","volume":"22","author":"J Zhou","year":"2015","unstructured":"Zhou, J., Zhuo, F., Huang, L., Luo, Y.: Multi-objective optimization of stamping forming process of head using Pareto-based genetic algorithm. J. Central South Univ. 22(9), 3287\u20133295 (2015). https:\/\/doi.org\/10.1007\/s11771-015-2868-0","journal-title":"J. Central South Univ."},{"issue":"10","key":"48_CR4","doi-asserted-by":"publisher","first-page":"3957","DOI":"10.1007\/s11771-015-2940-9","volume":"22","author":"N Barathwaj","year":"2015","unstructured":"Barathwaj, N., Raja, P., Gokulraj, S.: Optimization of assembly line balancing using genetic algorithm. J. Central South Univ. 22(10), 3957\u20133969 (2015). https:\/\/doi.org\/10.1007\/s11771-015-2940-9","journal-title":"J. Central South Univ."},{"issue":"4","key":"48_CR5","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1007\/s42757-019-0047-5","volume":"2","author":"H Ghorbani","year":"2019","unstructured":"Ghorbani, H., et al.: Performance comparison of bubble point pressure from oil PVT data: several neurocomputing techniques compared. Experimental Comput. Multiphase Flow 2(4), 225\u2013246 (2019). https:\/\/doi.org\/10.1007\/s42757-019-0047-5","journal-title":"Experimental Comput. Multiphase Flow"},{"issue":"1-4","key":"48_CR6","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1007\/s00170-014-5788-5","volume":"73","author":"M Manoochehri","year":"2014","unstructured":"Manoochehri, M., Kolahan, F.: Integration of artificial neural network and simulated annealing algorithm to optimize deep drawing process. Int. J. Adv. Manuf. Technol. 73(1\u20134), 241\u2013249 (2014). https:\/\/doi.org\/10.1007\/s00170-014-5788-5","journal-title":"Int. J. Adv. Manuf. Technol."},{"key":"48_CR7","doi-asserted-by":"publisher","first-page":"39","DOI":"10.1016\/j.neucom.2013.03.076","volume":"148","author":"LN Vitorino","year":"2015","unstructured":"Vitorino, L.N., Ribeiro, S.F., Bastos, C.J.A.: A mechanism based on artificial Bee colony to generate diversity in particle swarm optimization. Neurocomputing 148, 39\u201345 (2015)","journal-title":"Neurocomputing"},{"unstructured":"Eberhart, R., Kennedy, J.: New optimizer using particle swarm theory. In: Proceedings of the 1995 6th International Symposium on Micro Machine and Human Science, Nagoya, Japan, pp. 39\u201343 (1995)","key":"48_CR8"},{"unstructured":"Bonyadi, M.R. A theoretical guideline for designing an effective adaptive particle swarm. IEEE Trans. Evol. Comput. 2019 (2019)","key":"48_CR9"},{"doi-asserted-by":"crossref","unstructured":"Chen, D.-D., Lin, Y.-C., Chen, X.-M.: A strategy to control microstructures of a Ni-based superalloy during hot forging based on particle swarm optimization algorithm. Adv. Manuf. 2019, 238\u2013247 (2019)","key":"48_CR10","DOI":"10.1007\/s40436-019-00259-0"},{"issue":"4","key":"48_CR11","doi-asserted-by":"publisher","first-page":"561","DOI":"10.1016\/j.acme.2014.04.006","volume":"14","author":"M Winnicki","year":"2014","unstructured":"Winnicki, M., Ma\u0142achowska, A., Ambroziak, A.: Taguchi optimization of the thickness of a coating deposited by LPCS. Arch. Civ. Mech. Eng. 14(4), 561\u2013568 (2014). https:\/\/doi.org\/10.1016\/j.acme.2014.04.006","journal-title":"Arch. Civ. Mech. Eng."},{"key":"48_CR12","doi-asserted-by":"publisher","first-page":"10","DOI":"10.1016\/j.jspi.2015.03.002","volume":"164","author":"M Piffl","year":"2015","unstructured":"Piffl, M., Stadlober, E.: The depth-design: an efficient generation of high dimensional computer experiments. J. Stat. Plan. Infer. 164, 10\u201326 (2015)","journal-title":"J. Stat. Plan. Infer."},{"key":"48_CR13","doi-asserted-by":"publisher","first-page":"584","DOI":"10.1007\/s12613-012-0599-x","volume":"19","author":"M Milivojevic","year":"2012","unstructured":"Milivojevic, M., Stopic, S., Friedrich, B., Stojanovic, B., Drndarevic, D.: Computer modeling of high-pressure leaching process of nickel laterite by design of experiments and neural networks. Int. J. Min. Met. Mater. 19, 584\u2013594 (2012)","journal-title":"Int. J. Min. Met. Mater."},{"issue":"4","key":"48_CR14","doi-asserted-by":"publisher","first-page":"477","DOI":"10.1016\/j.acme.2012.07.005","volume":"12","author":"H Hasanzadehshooiili","year":"2012","unstructured":"Hasanzadehshooiili, H., Lakirouhani, A., \u0160apalas, A.: Neural network prediction of buckling load of steel arch-shells. Arch. Civ. Mech. Eng. 12(4), 477\u2013484 (2012). https:\/\/doi.org\/10.1016\/j.acme.2012.07.005","journal-title":"Arch. Civ. Mech. Eng."},{"key":"48_CR15","first-page":"1323","volume":"223","author":"M Haddadzadeh","year":"2009","unstructured":"Haddadzadeh, M., Razfar, M.R., Mamaghani, M.R.M.: Novel approach to initial blank design in deep drawing using artificial neural network. P I Mech. Eng. B-J Eng. 223, 1323\u20131330 (2009)","journal-title":"P I Mech. Eng. B-J Eng."},{"issue":"2","key":"48_CR16","doi-asserted-by":"publisher","first-page":"229","DOI":"10.1016\/j.acme.2012.11.004","volume":"13","author":"Y Song","year":"2013","unstructured":"Song, Y., Yu, Z.: Springback prediction in T-section beam bending process using neural networks and finite element method. Arch. Civ. Mech. Eng. 13(2), 229\u2013241 (2013). https:\/\/doi.org\/10.1016\/j.acme.2012.11.004","journal-title":"Arch. Civ. Mech. Eng."},{"key":"48_CR17","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1007\/s00158-012-0824-2","volume":"47","author":"S Kitayama","year":"2013","unstructured":"Kitayama, S., Huang, S.S., Yamazaki, K.: Optimization of variable blank holder force trajectory for springback reduction via sequential approximate optimization with radial basis function network. Struct. Multidiscip. O 47, 289\u2013300 (2013)","journal-title":"Struct. Multidiscip. O"},{"key":"48_CR18","doi-asserted-by":"publisher","first-page":"397","DOI":"10.1115\/1.2744399","volume":"129","author":"JH Song","year":"2007","unstructured":"Song, J.H., Huh, H., Kim, S.H.: Stress-based springback reduction of a channel shaped auto-body part with high-strength steel using response surface methodology. J. Eng. Mater-T ASME 129, 397\u2013406 (2007)","journal-title":"J. Eng. Mater-T ASME"},{"issue":"3","key":"48_CR19","doi-asserted-by":"publisher","first-page":"199","DOI":"10.1007\/s12613-012-0538","volume":"19","author":"X Guo","year":"2012","unstructured":"Guo, X., Li, D., Wu, Z., Tian, Q.-H.: Application of response surface methodology in optimizaing the sulfationoastingeaching process of nickel laterite. Int. J. Miner. Metall. Mater. 19(3), 199\u2013204 (2012). https:\/\/doi.org\/10.1007\/s12613-012-0538","journal-title":"Int. J. Miner. Metall. Mater."},{"key":"48_CR20","doi-asserted-by":"publisher","first-page":"159","DOI":"10.1016\/j.commatsci.2014.07.033","volume":"95","author":"W Zhang","year":"2014","unstructured":"Zhang, W., Cho, C., Xiao, Y.: An effective inverse procedure for identifying viscoplastic material properties of polymer Nafion. Comp. Mater. Sci. 95, 159\u2013165 (2014)","journal-title":"Comp. Mater. Sci."},{"key":"48_CR21","doi-asserted-by":"publisher","first-page":"419","DOI":"10.1080\/03052150410001686486","volume":"36","author":"LQ Wang","year":"2004","unstructured":"Wang, L.Q., Shan, S.Q., Wang, G.G.: Mode-pursuing sampling method for global optimization on expensive black-box functions. Eng. Optimiz. 36, 419\u2013438 (2004)","journal-title":"Eng. Optimiz."},{"key":"48_CR22","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1080\/03052150802345995","volume":"41","author":"X Duan","year":"2009","unstructured":"Duan, X., Wang, G.G., Kang, X., Niu, Q., Naterer, G., Peng, Q.: Performance study of mode-pursuing sampling method. Eng. Optimiz. 41, 1\u201321 (2009)","journal-title":"Eng. Optimiz."},{"key":"48_CR23","doi-asserted-by":"publisher","first-page":"210","DOI":"10.1115\/1.1561044","volume":"125","author":"GG Wang","year":"2003","unstructured":"Wang, G.G.: Adaptive response surface method using inherited Latin hypercube design points. J. Mech. Design. 125, 210\u2013220 (2003)","journal-title":"J. Mech. Design."},{"doi-asserted-by":"crossref","unstructured":"Liu, H., Jiang, K.Y., Li, B., Lu, P.: A rapid inverse determination of material performance parameters in sheet metal forming. In: 2nd International Conference on Advanced Engineering Materials and Technology, Zhuhai, China, pp. 1035\u20131040, 06\u201308 July 2012","key":"48_CR24","DOI":"10.4028\/www.scientific.net\/AMR.538-541.1035"},{"key":"48_CR25","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.jmapro.2015.09.009","volume":"20","author":"Y Yan","year":"2015","unstructured":"Yan, Y., Wang, H.B., Li, Q.: The inverse parameter identification of Hill 48 yield criterion and its verification in press bending and roll forming process simulations. J. Manuf. Process. 20, 46\u201353 (2015)","journal-title":"J. Manuf. Process."},{"unstructured":"Zhu, Q.C.: Research on the Drawing Process and Spring Back Control of the B-pillar Reinforced Panel. master. Thesis, Hefei University of Technology, Hefei, China (2013) (in Chinese)","key":"48_CR26"}],"container-title":["Lecture Notes in Computer Science","Intelligent Robotics and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-89134-3_48","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,10,17]],"date-time":"2021-10-17T11:18:23Z","timestamp":1634469503000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-030-89134-3_48"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2021]]},"ISBN":["9783030891336","9783030891343"],"references-count":26,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-89134-3_48","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2021]]},"assertion":[{"value":"18 October 2021","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"ICIRA","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Conference on Intelligent Robotics and Applications","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Yantai","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":"22 October 2021","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"25 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":"icira2021","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"https:\/\/www.icira2021.org\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}