{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,21]],"date-time":"2025-05-21T05:52:31Z","timestamp":1747806751129},"publisher-location":"Berlin, Heidelberg","reference-count":20,"publisher":"Springer Berlin Heidelberg","isbn-type":[{"type":"print","value":"9783540886358"},{"type":"electronic","value":"9783540886365"}],"license":[{"start":{"date-parts":[[2008,1,1]],"date-time":"2008-01-01T00:00:00Z","timestamp":1199145600000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2008]]},"DOI":"10.1007\/978-3-540-88636-5_95","type":"book-chapter","created":{"date-parts":[[2008,10,16]],"date-time":"2008-10-16T22:19:04Z","timestamp":1224195544000},"page":"1009-1019","source":"Crossref","is-referenced-by-count":9,"title":["A Comparison between Back Propagation and the Maximum Sensibility Neural Network to Surface Roughness Prediction in Machining of Titanium (Ti 6Al 4V) Alloy"],"prefix":"10.1007","author":[{"given":"Indira","family":"Escamilla","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Luis","family":"Torres","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Pedro","family":"Perez","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia","family":"Zambrano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","reference":[{"key":"95_CR1","doi-asserted-by":"crossref","unstructured":"Meziane, F., Vadera, S.: Intelligent systems in manufacturing: current developments and future Integrated manufacturing Systems, vol.\u00a011, pp. 218\u2013238 (2000)","DOI":"10.1108\/09576060010326221"},{"key":"95_CR2","unstructured":"Morales, R., Vallejo, A., Avellan, J.: AI approaches for cutting tool diagnosis in machining processes. In: Proceedings of the 25th IASTED 978-0-88986-629-4, pp. 186\u2013191 (2007)"},{"key":"95_CR3","doi-asserted-by":"crossref","unstructured":"Pawadea, R.S., Suhas, S., Brahmankar, P.K.: Effect of machining parameters and cutting edge geometry on surface integrity of high-speed turned Inconel 718. International Journal of Machine Tools and Manufacture (2007), doi:10.1016\/j.ijmachtools.2007.08.004","DOI":"10.1016\/j.ijmachtools.2007.08.004"},{"key":"95_CR4","doi-asserted-by":"crossref","unstructured":"He, W., Zhang, Y.F., Lee, K.S., Liu, T.I.: Development of a fuzzy-neuro system for parameter resetting injection molding. Transactions of the ASME\u00a0123 (February 2001)","DOI":"10.1115\/1.1286732"},{"key":"95_CR5","unstructured":"Rico, L., D\u00edaz, J.: Surface roughness prediction at 1018 cold rolled steel using Response Surface Methodology and neural networks. Culcyt Research Year\u00a02(10) (2005)"},{"key":"95_CR6","first-page":"111","volume-title":"Artificial Intelligence: A Modern Approach","author":"S.J. Russell","year":"2003","unstructured":"Russell, S.J., Norvig, P.: Artificial Intelligence: A Modern Approach, 2nd edn., pp. 111\u2013114. Prentice Hall, Upper Saddle River (2003)","edition":"2"},{"key":"95_CR7","doi-asserted-by":"crossref","unstructured":"Ramesh, S., Karunamoorthy, L., Ramakrishnan, R.: Modeling for prediction of surface roughness in machining of Ti64 alloy using response surface methodology. Journal of Materials Processing Technology (2007), doi:10.1016\/j.jmatprotec.2007.11.031","DOI":"10.1016\/j.jmatprotec.2007.11.031"},{"key":"95_CR8","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.jmatprotec.2004.08.012","volume":"166","author":"C.H. Che-Haron","year":"2005","unstructured":"Che-Haron, C.H., Jawaid, A.: The effect of machining on surface integrity of titanium alloy Ti\u20136% Al\u20134% V. Journal of Materials Processing Technology\u00a0166, 188\u2013192 (2005)","journal-title":"Journal of Materials Processing Technology"},{"key":"95_CR9","doi-asserted-by":"publisher","first-page":"443","DOI":"10.1016\/S0749-6419(01)00003-1","volume":"18","author":"A. Molinari","year":"2002","unstructured":"Molinari, A., Musquar, C., Sutter, G.: Adiabatic shear banding in high speed machining of Ti\u20136Al\u20134V: experiments and modeling. International Journal of Plasticity\u00a018, 443\u2013459 (2002)","journal-title":"International Journal of Plasticity"},{"key":"95_CR10","doi-asserted-by":"publisher","first-page":"153","DOI":"10.1016\/j.jmatprotec.2007.01.017","volume":"189","author":"H. Krain","year":"2007","unstructured":"Krain, H., Sharman, A., Ridgway, K.: Optimization of tool life and productivity when end milling Inconel 718 M. Journal of materials processing technology\u00a0189, 153\u2013161 (2007)","journal-title":"Journal of materials processing technology"},{"key":"95_CR11","doi-asserted-by":"crossref","unstructured":"Kopac, J., Bahor, M., Sokovic, M.: Optimal machining parameters for achieving the desired surface roughness in fine turning of cold preformed steel workpieces. International Journal of Machine Tools and Manufacture, 42707\u201342716 (2002)","DOI":"10.1016\/S0890-6955(01)00163-8"},{"key":"95_CR12","first-page":"735","volume":"27","author":"H. Oktem","year":"2006","unstructured":"Oktem, H., Erzurumlu, F.: Prediction of minimum surface roughness in end milling mold parts using neural network and genetic algorithm Materials and Design. Journal\u00a027, 735\u2013744 (2006)","journal-title":"Journal"},{"issue":"1-2","key":"95_CR13","doi-asserted-by":"publisher","first-page":"194","DOI":"10.1080\/09647040600602805","volume":"16","author":"S.K. Egiazaryan","year":"2007","unstructured":"Egiazaryan, S.K., G.G.: Theory of functional systems in the scientific school of p.k. anokhin. Journal of the History of the Neurosciences\u00a016(1-2), 194\u2013205 (2007)","journal-title":"Journal of the History of the Neurosciences"},{"key":"95_CR14","volume-title":"Biology and Neurophysiology of the Conditioned Reflex and Its Role in Adaptive Behavior","author":"P. Anokhin","year":"1974","unstructured":"Anokhin, P.: Biology and Neurophysiology of the Conditioned Reflex and Its Role in Adaptive Behavior. Pergamon, Oxford (1974)"},{"key":"95_CR15","volume-title":"Psicolog\u00eda y la filosof\u00eda de la ciencia: Metodolog\u00eda del sistema funcional","author":"P.K. Anojin","year":"1985","unstructured":"Anojin, P.K.: Psicolog\u00eda y la filosof\u00eda de la ciencia: Metodolog\u00eda del sistema funcional. editorial Trillas, M\u00e9xico (1985)"},{"key":"95_CR16","doi-asserted-by":"crossref","unstructured":"Red\u2019ko, V.G., Prokhorov, D.V., Burtsev, M.S.: Theory of functional systems, adaptive critics and neural networks. In: Proceedings of IJCNN, pp. 1787\u20131792 (2004)","DOI":"10.1109\/IJCNN.2004.1380879"},{"key":"95_CR17","unstructured":"Torres-Trevi\u00f1o, L.M.: Controladores din\u00e1micos con la red neuronal de m\u00e1xima sensibilidad. Master\u2019s thesis, Autonomous University of san Luis Potosi, San Luis Potos\u00ed, M\u00e9xico (1998)"},{"key":"95_CR18","unstructured":"Carlos Gonz\u00e1lez Gonz\u00e1lez y Ramon Zeleny, Metrolog\u00eda Dimensional. Mc Graw Hill"},{"key":"95_CR19","doi-asserted-by":"publisher","first-page":"123","DOI":"10.1016\/j.chemolab.2005.06.002","volume":"79","author":"B. Kim","year":"2005","unstructured":"Kim, B., Kim, S.: GA-optimized back propagation neural network with multi-parameterized gradients and applications to predicting plasma etch data. Chemometrics and Intelligent Laboratory Systems\u00a079, 123\u2013128 (2005)","journal-title":"Chemometrics and Intelligent Laboratory Systems"},{"key":"95_CR20","doi-asserted-by":"publisher","first-page":"3","DOI":"10.1016\/S0167-7012(00)00201-3","volume":"43","author":"I.A. Basheer","year":"2000","unstructured":"Basheer, I.A., Hajmeer, M.: Artificial neural networks: fundamentals, computing, design, and application. Journal of Microbiological Methods\u00a043, 3\u201331 (2000)","journal-title":"Journal of Microbiological Methods"}],"container-title":["Lecture Notes in Computer Science","MICAI 2008: Advances in Artificial Intelligence"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-540-88636-5_95","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,14]],"date-time":"2019-05-14T14:46:18Z","timestamp":1557845178000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-540-88636-5_95"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2008]]},"ISBN":["9783540886358","9783540886365"],"references-count":20,"URL":"https:\/\/doi.org\/10.1007\/978-3-540-88636-5_95","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2008]]}}}