{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,3,31]],"date-time":"2025-03-31T01:51:37Z","timestamp":1743385897646,"version":"3.37.3"},"reference-count":73,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T00:00:00Z","timestamp":1667347200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T00:00:00Z","timestamp":1667347200000},"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":["J Intell Manuf"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1007\/s10845-022-02047-3","type":"journal-article","created":{"date-parts":[[2022,11,2]],"date-time":"2022-11-02T19:12:35Z","timestamp":1667416355000},"page":"257-273","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Data-driven cymbal bronze alloy identification via evolutionary machine learning with automatic feature selection"],"prefix":"10.1007","volume":"35","author":[{"given":"Tales H. A.","family":"Boratto","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Camila M.","family":"Saporetti","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Samuel C. A.","family":"Basilio","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexandre A.","family":"Cury","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-2844-9470","authenticated-orcid":false,"given":"Leonardo","family":"Goliatt","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,11,2]]},"reference":[{"key":"2047_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.rineng.2022.100419","volume":"14","author":"T Aihara","year":"2022","unstructured":"Aihara, T., & Ito, K. (2022). Relationship between chaotic vibrations and acoustic properties of percussion cymbals. Results in Engineering, 14, 100419. https:\/\/doi.org\/10.1016\/j.rineng.2022.100419","journal-title":"Results in Engineering"},{"key":"2047_CR2","unstructured":"AKG. (2021). C414 XLII - Reference multipattern condenser microphone. Retrieved March 28, 2021 from https:\/\/www.akg.com\/Microphones\/Condenser%20Microphones\/C414+XLII.html"},{"key":"2047_CR3","doi-asserted-by":"publisher","first-page":"40","DOI":"10.1214\/09-SS054","volume":"4","author":"S Arlot","year":"2010","unstructured":"Arlot, S., & Celisse, A. (2010). A survey of cross-validation procedures for model selection. Statistics Surveys, 4, 40\u201379.","journal-title":"Statistics Surveys"},{"key":"2047_CR4","doi-asserted-by":"publisher","DOI":"10.1016\/j.softx.2020.100456","volume":"11","author":"M Barandas","year":"2020","unstructured":"Barandas, M., Folgado, D., Fernandes, L., Santos, S., Abreu, M., Bota, P., Liu, H., Schultz, T., & Gamboa, H. (2020). Tsfel: Time series feature extraction library. SoftwareX, 11, 100456.","journal-title":"SoftwareX"},{"issue":"1","key":"2047_CR5","doi-asserted-by":"publisher","first-page":"1","DOI":"10.51526\/kbes.2022.3.1.1-16","volume":"3","author":"SA Basilio","year":"2022","unstructured":"Basilio, S. A., & Goliatt, L. (2022). Gradient boosting hybridized with exponential natural evolution strategies for estimating the strength of geopolymer self-compacting concrete. Knowledge-Based Engineering and Sciences, 3(1), 1\u201316.","journal-title":"Knowledge-Based Engineering and Sciences"},{"issue":"9","key":"2047_CR6","doi-asserted-by":"publisher","first-page":"2172","DOI":"10.1109\/TLA.2022.9878173","volume":"20","author":"T Boratto","year":"2022","unstructured":"Boratto, T., Cury, A., & Goliatt, L. (2022). A fuzzy approach to drum cymbals classification. IEEE Latin America Transactions, 20(9), 2172\u20132180. https:\/\/doi.org\/10.1109\/TLA.2022.9878173","journal-title":"IEEE Latin America Transactions"},{"key":"2047_CR7","unstructured":"Boratto, T. H., Cury, A., & Goliatt, L. (2022b). Crash cymbal sounds. https:\/\/data.mendeley.com\/datasets\/9tytvdxd24\/1"},{"key":"2047_CR8","doi-asserted-by":"publisher","unstructured":"Boratto, T. H. A., Marcomini, R. F., Goliatt, L., Pagotto, C. R., Cury, A. A., Pereira, I. J. U., & Nishida, F. D. (2021) Effects analysis of two differents cymbals manufacturing methods. In: 11th Congresso Brasileiro de Engenharia de Fabrica\u00e7\u00e3o (COBEF), https:\/\/doi.org\/10.26678\/ABCM.COBEF2021.COB21-0164","DOI":"10.26678\/ABCM.COBEF2021.COB21-0164"},{"key":"2047_CR9","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1016\/j.ins.2013.02.041","volume":"237","author":"I Boussa\u00efd","year":"2013","unstructured":"Boussa\u00efd, I., Lepagnot, J., & Siarry, P. (2013). A survey on optimization metaheuristics. Information Sciences, 237, 82\u2013117.","journal-title":"Information Sciences"},{"key":"2047_CR10","unstructured":"Cavaco, S., & Almeida, H. (2012). Automatic cymbal classification using non-negative matrix factorization. In: 2012 19th International Conference on Systems, Signals and Image Processing (IWSSIP), pp. 468\u2013471."},{"key":"2047_CR11","unstructured":"Chen, T., & He, T. (2015). Higgs boson discovery with boosted trees. In: NIPS 2014 workshop on high-energy physics and machine learning, pp. 69\u201380."},{"key":"2047_CR12","unstructured":"Claesen, M., & Moor, B. D. (2015). Hyperparameter search in machine learning. CoRR abs\/1502.02127. arxiv:1502.02127"},{"issue":"1","key":"2047_CR13","doi-asserted-by":"publisher","first-page":"25","DOI":"10.1063\/1.1530990","volume":"13","author":"JP Crutchfield","year":"2003","unstructured":"Crutchfield, J. P., & Feldman, D. P. (2003). Regularities unseen, randomness observed: Levels of entropy convergence. Chaos: An Interdisciplinary Journal of Nonlinear Science, 13(1), 25\u201354. https:\/\/doi.org\/10.1063\/1.1530990","journal-title":"Chaos: An Interdisciplinary Journal of Nonlinear Science"},{"key":"2047_CR14","first-page":"1","volume":"27","author":"A Defazio","year":"2014","unstructured":"Defazio, A., Bach, F., & Lacoste-Julien, S. (2014). Saga: A fast incremental gradient method with support for non-strongly convex composite objectives. Advances in Neural Information Processing Systems, 27, 1.","journal-title":"Advances in Neural Information Processing Systems"},{"key":"2047_CR15","unstructured":"Di Giulio, G., Esposito, E., Santolini, C., & Scalise, L. (2001). Experimental vibrational analysis of drum cymbals. In: Proceedings of International Symposium on Musical Acoustics (ISMA2001), pp. 724\u2013730."},{"key":"2047_CR16","first-page":"1","volume":"1","author":"T Dokeroglu","year":"2022","unstructured":"Dokeroglu, T., Deniz, A., & Kiziloz, H. E. (2022). A comprehensive survey on recent metaheuristics for feature selection. Neurocomputing, 1, 1.","journal-title":"Neurocomputing"},{"key":"2047_CR17","doi-asserted-by":"publisher","first-page":"225","DOI":"10.1016\/B978-0-12-819154-5.00023-0","volume-title":"Knowledge Discovery in Big Data from Astronomy and Earth Observation","author":"K El Bouchefry","year":"2020","unstructured":"El Bouchefry, K., & de Souza, R. S. (2020). Chapter 12 - learning in big data: Introduction to machine learning. In F. Adam (Ed.), Knowledge Discovery in Big Data from Astronomy and Earth Observation (pp. 225\u2013249). Elsevier."},{"issue":"6B","key":"2047_CR18","doi-asserted-by":"publisher","first-page":"3191","DOI":"10.1016\/j.jksuci.2022.04.008","volume":"34","author":"D Fern\u00e1ndez-Cerero","year":"2022","unstructured":"Fern\u00e1ndez-Cerero, D., Troyano, J. A., Jak\u00f3bik, A., & Fern\u00e1ndez-Montes, A. (2022). Machine learning regression to boost scheduling performance in hyper-scale cloud-computing data centres. Journal of King Saud University - Computer and Information Sciences, 34(6B), 3191\u20133203. https:\/\/doi.org\/10.1016\/j.jksuci.2022.04.008","journal-title":"Journal of King Saud University - Computer and Information Sciences"},{"key":"2047_CR19","first-page":"1","volume":"1","author":"VR Franco","year":"2022","unstructured":"Franco, V. R., Hott, M. C., Andrade, R. G., & Goliatt, L. (2022). Hybrid machine learning methods combined with computer vision approaches to estimate biophysical parameters of pastures. Evolutionary Intelligence, 1, 1\u201314.","journal-title":"Evolutionary Intelligence"},{"key":"2047_CR20","first-page":"1","volume":"1","author":"JH Friedman","year":"1991","unstructured":"Friedman, J. H. (1991). Multivariate adaptive regression splines. The Annals of Statistics, 1, 1\u201367.","journal-title":"The Annals of Statistics"},{"issue":"3","key":"2047_CR21","doi-asserted-by":"publisher","first-page":"346","DOI":"10.1080\/21642583.2018.1553691","volume":"6","author":"H Fu","year":"2018","unstructured":"Fu, H., Liu, H., Deng, X., & Sun, F. (2018). Wood material recognition for industrial applications. Systems Science & Control Engineering, 6(3), 346\u2013358. https:\/\/doi.org\/10.1080\/21642583.2018.1553691","journal-title":"Systems Science & Control Engineering"},{"issue":"14","key":"2047_CR22","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1016\/S1352-2310(97)00447-0","volume":"32","author":"M Gardner","year":"1998","unstructured":"Gardner, M., & Dorling, S. (1998). Artificial neural networks (the multilayer perceptron)-a review of applications in the atmospheric sciences. Atmospheric Environment, 32(14), 2627\u20132636. https:\/\/doi.org\/10.1016\/S1352-2310(97)00447-0","journal-title":"Atmospheric Environment"},{"key":"2047_CR23","volume-title":"Hands-on machine learning with Scikit-Learn and TensorFlow : concepts, tools, and techniques to build intelligent systems","author":"A Geron","year":"2017","unstructured":"Geron, A. (2017). Hands-on machine learning with Scikit-Learn and TensorFlow\u202f: concepts, tools, and techniques to build intelligent systems. Sebastopol, CA: O\u2019Reilly Media."},{"issue":"2","key":"2047_CR24","doi-asserted-by":"publisher","first-page":"1171","DOI":"10.1121\/1.2149839","volume":"119","author":"BL Giordano","year":"2006","unstructured":"Giordano, B. L., & McAdams, S. (2006). Material identification of real impact sounds: Effects of size variation in steel, glass, wood, and plexiglass plates. The Journal of the Acoustical Society of America, 119(2), 1171\u20131181. https:\/\/doi.org\/10.1121\/1.2149839","journal-title":"The Journal of the Acoustical Society of America"},{"key":"2047_CR25","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118295","volume":"212","author":"L Goliatt","year":"2023","unstructured":"Goliatt, L., & Yaseen, Z. M. (2023). Development of a hybrid computational intelligent model for daily global solar radiation prediction. Expert Systems with Applications, 212, 118295. https:\/\/doi.org\/10.1016\/j.eswa.2022.118295","journal-title":"Expert Systems with Applications"},{"issue":"1","key":"2047_CR26","doi-asserted-by":"publisher","first-page":"1298","DOI":"10.1080\/19942060.2021.1972043","volume":"15","author":"L Goliatt","year":"2021","unstructured":"Goliatt, L., Sulaiman, S. O., Khedher, K. M., Farooque, A. A., & Yaseen, Z. M. (2021). Estimation of natural streams longitudinal dispersion coefficient using hybrid evolutionary machine learning model. Engineering Applications of Computational Fluid Mechanics, 15(1), 1298\u20131320. https:\/\/doi.org\/10.1080\/19942060.2021.1972043","journal-title":"Engineering Applications of Computational Fluid Mechanics"},{"issue":"3","key":"2047_CR27","doi-asserted-by":"publisher","first-page":"3659","DOI":"10.1016\/j.eswa.2011.09.058","volume":"39","author":"L Guelman","year":"2012","unstructured":"Guelman, L. (2012). Gradient boosting trees for auto insurance loss cost modeling and prediction. Expert Systems with Applications, 39(3), 3659\u20133667. https:\/\/doi.org\/10.1016\/j.eswa.2011.09.058","journal-title":"Expert Systems with Applications"},{"key":"2047_CR28","doi-asserted-by":"publisher","unstructured":"Harris, C. R., Millman, K. J., van der Walt, S. J., Gommers, R., Virtanen, P., Cournapeau, D., Wieser, E., Taylor, J., Berg, S., Smith, N. J., Kern, R., Picus, M., Hoyer, S., van Kerkwijk, M. H., Brett, M., Haldane, A., & del R\u0131o JF, Wiebe M, Peterson P, G\u2019erard-Marchant P, Sheppard K, Reddy T, Weckesser W, Abbasi H, Gohlke C, Oliphant TE,. (2020). Array programming with NumPy. Nature, 585(7825), 357\u2013362. https:\/\/doi.org\/10.1038\/s41586-020-2649-2","DOI":"10.1038\/s41586-020-2649-2"},{"key":"2047_CR29","doi-asserted-by":"publisher","DOI":"10.1007\/s11356-022-21201-1","author":"S Heddam","year":"2022","unstructured":"Heddam, S., Yaseen, Z. M., Falah, M. W., Goliatt, L., Tan, M. L., Sa\u2019adi, Z., Ahmadianfar, I., Saggi, M., Bhatia, A., & Samui, P. (2022). Cyanobacteria blue-green algae prediction enhancement using hybrid machine learning-based gamma test variable selection and empirical wavelet transform. Environmental Science and Pollution Research. https:\/\/doi.org\/10.1007\/s11356-022-21201-1","journal-title":"Environmental Science and Pollution Research"},{"key":"2047_CR30","doi-asserted-by":"publisher","first-page":"69","DOI":"10.1007\/3-540-45722-4_8","volume-title":"Music and artificial intelligence","author":"P Herrera","year":"2002","unstructured":"Herrera, P., Yeterian, A., & Gouyon, F. (2002). Automatic classification of drum sounds: A comparison of feature selection methods and classification techniques. In C. Anagnostopoulou, M. Ferrand, & A. Smaill (Eds.), Music and artificial intelligence (pp. 69\u201380). Heidelberg: Springer."},{"issue":"4","key":"2047_CR31","doi-asserted-by":"publisher","first-page":"2191","DOI":"10.1007\/s10462-017-9605-z","volume":"52","author":"K Hussain","year":"2019","unstructured":"Hussain, K., Mohd Salleh, M. N., Cheng, S., & Shi, Y. (2019). Metaheuristic research: A comprehensive survey. Artificial Intelligence Review, 52(4), 2191\u20132233.","journal-title":"Artificial Intelligence Review"},{"issue":"2","key":"2047_CR32","doi-asserted-by":"publisher","first-page":"1545","DOI":"10.1016\/j.asej.2020.11.011","volume":"12","author":"A Ibrahem Ahmed Osman","year":"2021","unstructured":"Ibrahem Ahmed Osman, A., Najah Ahmed, A., Chow, M. F., Feng Huang, Y., & El-Shafie, A. (2021). Extreme gradient boosting (xgboost) model to predict the groundwater levels in Selangor, Malaysia. Ain Shams Engineering Journal, 12(2), 1545\u20131556.","journal-title":"Ain Shams Engineering Journal"},{"key":"2047_CR33","doi-asserted-by":"publisher","first-page":"16","DOI":"10.3390\/math10162971","volume":"10","author":"RMA Ikram","year":"2022","unstructured":"Ikram, R. M. A., Goliatt, L., Kisi, O., Trajkovic, S., & Shahid, S. (2022). Covariance matrix adaptation evolution strategy for improving machine learning approaches in streamflow prediction. Mathematics, 10, 16. https:\/\/doi.org\/10.3390\/math10162971","journal-title":"Mathematics"},{"key":"2047_CR34","doi-asserted-by":"publisher","first-page":"89","DOI":"10.1016\/j.ymssp.2016.11.009","volume":"88","author":"J Javh","year":"2017","unstructured":"Javh, J., Slavi\u010d, J., & Bolte\u017ear, M. (2017). The subpixel resolution of optical-flow-based modal analysis. Mechanical Systems and Signal Processing, 88, 89\u201399. https:\/\/doi.org\/10.1016\/j.ymssp.2016.11.009","journal-title":"Mechanical Systems and Signal Processing"},{"key":"2047_CR35","doi-asserted-by":"publisher","unstructured":"Kannan, S. S., Jo, W., Parasuraman, R., & Min, B. C. (2020). Material mapping in unknown environments using tapping sound. In: 2020 IEEE\/RSJ International Conference on Intelligent Robots and Systems (IROS), pp. 4855\u20134861. https:\/\/doi.org\/10.1109\/IROS45743.2020.9341346","DOI":"10.1109\/IROS45743.2020.9341346"},{"key":"2047_CR36","doi-asserted-by":"crossref","unstructured":"Kaselouris, E., Alexandraki, C., Bakarezos, M., Tatarakis, M., Papadogiannis, N., & Dimitriou, V. (2022). A detailed fem study on the vibro-acoustic behaviour of crash and splash musical cymbals. International Journal of Circuits, Systems and Signal Processing, 16, 948\u2013955.https:\/\/doi.org\/10.46300\/9106.2022.16.116","DOI":"10.46300\/9106.2022.16.116"},{"key":"2047_CR37","doi-asserted-by":"crossref","unstructured":"Kele\u015f, S., G\u00fcnl\u00fc, A., & Ercanli, I. (2021). Estimating aboveground stand carbon by combining sentinel-1 and sentinel-2 satellite data: A case study from turkey. In: Forest Resources Resilience and Conflicts. Elsevier, pp. 117\u2013126.","DOI":"10.1016\/B978-0-12-822931-6.00008-3"},{"key":"2047_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107117","volume":"225","author":"H Kim","year":"2021","unstructured":"Kim, H., & Lee, T. H. (2021). A robust elastic net via bootstrap method under sampling uncertainty for significance analysis of high-dimensional design problems. Knowledge-Based Systems, 225, 107117. https:\/\/doi.org\/10.1016\/j.knosys.2021.107117","journal-title":"Knowledge-Based Systems"},{"key":"2047_CR39","doi-asserted-by":"crossref","unstructured":"Knees, P., & Schedl, M. (2015). Music retrieval and recommendation: A tutorial overview. Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval.","DOI":"10.1145\/2766462.2767880"},{"issue":"3","key":"2047_CR40","doi-asserted-by":"publisher","first-page":"211","DOI":"10.6029\/smartcr.2014.03.007","volume":"4","author":"V Kumar","year":"2014","unstructured":"Kumar, V., & Minz, S. (2014). Feature selection: A literature review. SmartCR, 4(3), 211\u2013229.","journal-title":"SmartCR"},{"key":"2047_CR41","doi-asserted-by":"publisher","DOI":"10.1088\/1742-6596\/744\/1\/012110","volume":"744","author":"F Kuratani","year":"2016","unstructured":"Kuratani, F., Yoshida, T., Koide, T., Mizuta, T., & Osamura, K. (2016). Understanding the effect of hammering process on the vibration characteristics of cymbals. Journal of Physics: Conference Series, 744, 012110. https:\/\/doi.org\/10.1088\/1742-6596\/744\/1\/012110","journal-title":"Journal of Physics: Conference Series"},{"key":"2047_CR42","unstructured":"Lee, S. I., Lee, H., Abbeel, P., & Ng, A. (2006). Efficient l1 regularized logistic regression. In: Proceedings of the 21st National Conference on Artificial Intelligence (AAAI-06), vol.\u00a021."},{"key":"2047_CR43","first-page":"1","volume":"11","author":"J Liu","year":"2021","unstructured":"Liu, J., Bai, M., Jiang, N., Cheng, R., Li, X., Wang, Y., & Yu, D. (2021). Interclass interference suppression in multi-class problems. Applied Sciences, 11, 1.","journal-title":"Applied Sciences"},{"issue":"4","key":"2047_CR44","doi-asserted-by":"publisher","first-page":"172988141771499","DOI":"10.1177\/1729881417714996","volume":"14","author":"E Lopez-Caudana","year":"2017","unstructured":"Lopez-Caudana, E., Quiroz, O., Rodr\u00edguez, A., Y\u00e9pez, L., & Ibarra, D. (2017). Classification of materials by acoustic signal processing in real time for NAO robots. International Journal of Advanced Robotic Systems, 14(4), 1729881417714996. https:\/\/doi.org\/10.1177\/1729881417714996","journal-title":"International Journal of Advanced Robotic Systems"},{"key":"2047_CR45","doi-asserted-by":"publisher","first-page":"255","DOI":"10.1007\/978-3-030-63710-1_20","volume-title":"Bioinspired optimization methods and their applications","author":"AD Martinho","year":"2020","unstructured":"Martinho, A. D., Ribeiro, C. B. M., Gorodetskaya, Y., Fonseca, T. L., & Goliatt, L. (2020). Extreme learning machine with evolutionary parameter tuning applied to forecast the daily natural flow at Cahora Bassa dam, Mozambique. In B. Filipi\u010d, E. Minisci, & M. Vasile (Eds.), Bioinspired optimization methods and their applications (pp. 255\u2013267). Cham: Springer."},{"key":"2047_CR46","doi-asserted-by":"publisher","unstructured":"Wes, M. (2010). Data Structures for Statistical Computing in Python. In: S. van\u00a0der Walt, J. Millman (eds) Proceedings of the 9th Python in Science Conference, pp. 56\u201361. https:\/\/doi.org\/10.25080\/Majora-92bf1922-00a","DOI":"10.25080\/Majora-92bf1922-00a"},{"key":"2047_CR47","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-21945-5","author":"M M\u00fcller","year":"2015","unstructured":"M\u00fcller, M. (2015). Fundamentals of Music Processing. Springer International Publishing. https:\/\/doi.org\/10.1007\/978-3-319-21945-5","journal-title":"Springer International Publishing"},{"key":"2047_CR48","doi-asserted-by":"publisher","unstructured":"Ng, A. Y. (2004). Feature selection, l1 vs. l2 regularization, and rotational invariance. In: Proceedings of the Twenty-First International Conference on Machine Learning, Association for Computing Machinery, New York, USA, ICML \u201904, p\u00a078, https:\/\/doi.org\/10.1145\/1015330.1015435.","DOI":"10.1145\/1015330.1015435"},{"key":"2047_CR49","doi-asserted-by":"publisher","first-page":"977","DOI":"10.1121\/1.5091013","volume":"145","author":"Q Nguyen","year":"2019","unstructured":"Nguyen, Q., & Touz\u00e9, C. (2019). Nonlinear vibrations of thin plates with variable thickness: Application to sound synthesis of cymbals. The Journal of the Acoustical Society of America, 145, 977\u2013988. https:\/\/doi.org\/10.1121\/1.5091013","journal-title":"The Journal of the Acoustical Society of America"},{"issue":"881","key":"2047_CR50","doi-asserted-by":"publisher","first-page":"1900237","DOI":"10.1299\/transjsme.19-00237","volume":"86","author":"W Ogawa","year":"2020","unstructured":"Ogawa, W., Kuratani, F., Yoshida, T., Koide, T., & Mizuta, T. (2020). Effect of bell size on sound characteristics of cymbals. Transactions of the JSME, 86(881), 1900237\u20131900237. https:\/\/doi.org\/10.1299\/transjsme.19-00237","journal-title":"Transactions of the JSME"},{"key":"2047_CR51","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s11665-016-2408-6","volume":"25","author":"K Osamura","year":"2016","unstructured":"Osamura, K., Kuratani, F., Koide, T., Ogawa, W., Taniguchi, H., Monju, Y., Mizuta, T., & Shobu, T. (2016). The correlation between the percussive sound and the residual stress\/strain distributions in a cymbal. Journal of Materials Engineering and Performance, 25, 1. https:\/\/doi.org\/10.1007\/s11665-016-2408-6","journal-title":"Journal of Materials Engineering and Performance"},{"key":"2047_CR52","first-page":"2825","volume":"12","author":"F Pedregosa","year":"2011","unstructured":"Pedregosa, F., Varoquaux, G., Gramfort, A., Michel, V., Thirion, B., Grisel, O., Blondel, M., Prettenhofer, P., Weiss, R., Dubourg, V., et al. (2011). Scikit-learn: Machine learning in python. The Journal of Machine Learning Research, 12, 2825\u20132830.","journal-title":"The Journal of Machine Learning Research"},{"key":"2047_CR53","unstructured":"Perrin, R., Swallowe, G., Zietlow, S., & Moore, T. (2008). Normal modes of cymbals. Proceedings of the Institute of Acoustics"},{"key":"2047_CR54","series-title":"Musical Instruments Series","volume-title":"The Cymbal Book","author":"H Pinksterboer","year":"1992","unstructured":"Pinksterboer, H., & Mattingly, R. (1992). The Cymbal Book. Musical Instruments SeriesHal Leonard Publishing Corporation."},{"key":"2047_CR55","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4939-0755-7","volume-title":"Springer handbook of acoustics","author":"T Rossing","year":"2014","unstructured":"Rossing, T. (2014). Springer handbook of acoustics (2nd ed.). New York: Springer Handbooks.","edition":"2"},{"key":"2047_CR56","doi-asserted-by":"publisher","unstructured":"Saporetti, C., Fonseca, D., Oliveira, L., Pereira, E., & Goliatt, L. (2022). Hybrid machine learning models for estimating total organic carbon from mineral constituents in core samples of shale gas fields. Marine and Petroleum Geology, p. 105783, https:\/\/doi.org\/10.1016\/j.marpetgeo.2022.105783","DOI":"10.1016\/j.marpetgeo.2022.105783"},{"issue":"12","key":"2047_CR57","doi-asserted-by":"publisher","first-page":"1819","DOI":"10.1109\/LGRS.2019.2911473","volume":"16","author":"CM Saporetti","year":"2019","unstructured":"Saporetti, C. M., da Fonseca, L. G., & Pereira, E. (2019). A lithology identification approach based on machine learning with evolutionary parameter tuning. IEEE Geoscience and Remote Sensing Letters, 16(12), 1819\u20131823. https:\/\/doi.org\/10.1109\/LGRS.2019.2911473","journal-title":"IEEE Geoscience and Remote Sensing Letters"},{"key":"2047_CR58","doi-asserted-by":"crossref","unstructured":"Seabold, S., & Perktold, J. (2010). statsmodels: Econometric and statistical modeling with python. In: 9th Python in Science Conference.","DOI":"10.25080\/Majora-92bf1922-011"},{"key":"2047_CR59","unstructured":"Shure. (2021). PGA81 - Microfone condensador cardioide para instrumento. Retrieved April 02, 2021 from https:\/\/www.shure.com\/pt-BR\/produtos\/microfones\/pga81"},{"key":"2047_CR60","doi-asserted-by":"publisher","first-page":"137","DOI":"10.24425\/afe.2021.136090","volume":"21","author":"S Slamet","year":"2021","unstructured":"Slamet, S., Suyitno, S., Kusumaningtyas, I., & Miasa, I. (2021). Effect of high-tin bronze composition on physical, mechanical, and acoustic properties of gamelan materials. Archives of Foundry Engineering, 21, 137\u2013145. https:\/\/doi.org\/10.24425\/afe.2021.136090","journal-title":"Archives of Foundry Engineering"},{"key":"2047_CR61","first-page":"1","volume":"1","author":"DP Souza","year":"2022","unstructured":"Souza, D. P., Martinho, A. D., Rocha, C. C., Christo, Ed. S., & Goliatt, L. (2022). Group method of data handling to forecast the daily water flow at the Cahora Bassa dam. Acta Geophysica, 1, 1\u201313.","journal-title":"Acta Geophysica"},{"key":"2047_CR62","doi-asserted-by":"crossref","unstructured":"Souza, V. M. A., Batista, G. E. A. P. A., Souza-Filho, N. E. (2015). Automatic classification of drum sounds with indefinite pitch. In: Proceedings of International Joint Conference on Neural Networks (IJCNN).","DOI":"10.1109\/IJCNN.2015.7280342"},{"issue":"4","key":"2047_CR63","doi-asserted-by":"publisher","first-page":"341","DOI":"10.1023\/A:1008202821328","volume":"11","author":"R Storn","year":"1997","unstructured":"Storn, R., & Price, K. (1997). Differential evolution-a simple and efficient heuristic for global optimization over continuous spaces. Journal of Global Optimization, 11(4), 341\u2013359.","journal-title":"Journal of Global Optimization"},{"key":"2047_CR64","doi-asserted-by":"publisher","DOI":"10.1016\/j.cam.2021.113462","volume":"392","author":"M Su","year":"2021","unstructured":"Su, M., & Wang, W. (2021). Elastic net penalized quantile regression model. Journal of Computational and Applied Mathematics, 392, 113462. https:\/\/doi.org\/10.1016\/j.cam.2021.113462","journal-title":"Journal of Computational and Applied Mathematics"},{"key":"2047_CR65","doi-asserted-by":"publisher","unstructured":"Sugita, I. K. G., & Priambadi, I. G. N. (2017). The study of dendrite arm spacing (das) on acoustical of tin bronze 20sn alloy as gamelan bali materials. Engineering and Innovative Materials V, Trans Tech Publications Ltd, Materials Science Forum, 889, 133\u2013137. https:\/\/doi.org\/10.4028\/www.scientific.net\/MSF.889.133","DOI":"10.4028\/www.scientific.net\/MSF.889.133"},{"key":"2047_CR66","doi-asserted-by":"publisher","unstructured":"Pandas Development Team, T. (2020). pandas-dev\/pandas: Pandas. https:\/\/doi.org\/10.5281\/zenodo.3509134","DOI":"10.5281\/zenodo.3509134"},{"key":"2047_CR67","volume-title":"Statistical Learning Theory","author":"VN Vapnik","year":"1998","unstructured":"Vapnik, V. N. (1998). Statistical Learning Theory. Wiley-Interscience."},{"key":"2047_CR68","doi-asserted-by":"crossref","unstructured":"Virtanen, P., Gommers, R., Oliphant, T. E., Haberland, M., Reddy, T., Cournapeau, D., Burovski, E., Peterson, P., Weckesser, W., Bright, J., van der Walt, S. J., Brett, M., Wilson, J., Millman, K. J., Mayorov, N., Nelson, A. R. J., Jones, E., Kern, R., Larson, E., Carey CJ, Polat I, Feng Y, Moore EW, VanderPlas J, Laxalde D, Perktold J, Cimrman R, Henriksen I, Quintero EA, Harris CR, Archibald AM, Ribeiro AH, Pedregosa F, van Mulbregt P, SciPy 10 Contributors,. (2020). SciPy 1.0: Fundamental Algorithms for Scientific Computing in Python. Nature Methods, 17, 261\u2013272.","DOI":"10.1038\/s41592-020-0772-5"},{"issue":"JJ1","key":"2047_CR69","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1557\/PROC-760-JJ1.6","volume":"760","author":"MA White","year":"2002","unstructured":"White, M. A., & MacMillan, P. (2002). The cymbal as an instructional device for materials education. MRS Proceedings, 760(JJ1), 6. https:\/\/doi.org\/10.1557\/PROC-760-JJ1.6","journal-title":"MRS Proceedings"},{"key":"2047_CR70","doi-asserted-by":"crossref","unstructured":"Wu, Z., Li, J., Cai, M., Lin, Y., & Zhang, W. (2016). On membership of black-box or white-box of artificial neural network models. In: 2016 IEEE 11th conference on industrial electronics and applications (ICIEA), IEEE, pp. 1400\u20131404.","DOI":"10.1109\/ICIEA.2016.7603804"},{"issue":"5","key":"2047_CR71","doi-asserted-by":"publisher","first-page":"525","DOI":"10.1016\/j.patrec.2008.11.012","volume":"30","author":"SC Yusta","year":"2009","unstructured":"Yusta, S. C. (2009). Different metaheuristic strategies to solve the feature selection problem. Pattern Recognition Letters, 30(5), 525\u2013534.","journal-title":"Pattern Recognition Letters"},{"key":"2047_CR72","doi-asserted-by":"publisher","unstructured":"Zhang, J., Niu, Q., Li, K., & Irwin, G. W. (2011). Model selection in svms using differential evolution. IFAC Proceedings Volumes, 44(1), 14717\u201314722. https:\/\/doi.org\/10.3182\/20110828-6-IT-1002.00584. www.sciencedirect.com\/science\/article\/pii\/S1474667016459938, 18th IFAC World Congress","DOI":"10.3182\/20110828-6-IT-1002.00584"},{"key":"2047_CR73","doi-asserted-by":"publisher","unstructured":"Zhang, W., Yang, G., Lin, Y., Ji, C., & Gupta, M. M. (2018). On definition of deep learning. In: 2018 World Automation Congress (WAC), pp 1\u20135, https:\/\/doi.org\/10.23919\/WAC.2018.8430387","DOI":"10.23919\/WAC.2018.8430387"}],"container-title":["Journal of Intelligent Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-022-02047-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10845-022-02047-3\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10845-022-02047-3.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,1,14]],"date-time":"2024-01-14T21:28:45Z","timestamp":1705267725000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10845-022-02047-3"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,11,2]]},"references-count":73,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2024,1]]}},"alternative-id":["2047"],"URL":"https:\/\/doi.org\/10.1007\/s10845-022-02047-3","relation":{},"ISSN":["0956-5515","1572-8145"],"issn-type":[{"type":"print","value":"0956-5515"},{"type":"electronic","value":"1572-8145"}],"subject":[],"published":{"date-parts":[[2022,11,2]]},"assertion":[{"value":"23 April 2022","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 November 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflicts of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"Source codes are made available by the authors upon request. The audio database is free and available on the Mendeley Data Repository() [7].","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Data and code availability"}}]}}