{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,7,8]],"date-time":"2025-07-08T14:33:53Z","timestamp":1751985233828},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T00:00:00Z","timestamp":1649376000000},"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":["Wireless Pers Commun"],"published-print":{"date-parts":[[2022,7]]},"DOI":"10.1007\/s11277-022-09625-x","type":"journal-article","created":{"date-parts":[[2022,4,8]],"date-time":"2022-04-08T14:05:13Z","timestamp":1649426713000},"page":"1653-1675","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":4,"title":["Marine Propeller Design Using Evolving Chaotic Autonomous Particle Swarm Optimization"],"prefix":"10.1007","volume":"125","author":[{"given":"Rasoul","family":"Karimi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Vahid","family":"Shokri","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mohammad","family":"Khishe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mehran Khaki","family":"Jameie","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,4,8]]},"reference":[{"issue":"4","key":"9625_CR1","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1139\/juvs-2014-0019","volume":"4","author":"B Rutkay","year":"2016","unstructured":"Rutkay, B., & Lalibert\u00e9, J. (2016). Design and manufacture of propellers for small unmanned aerial vehicles. Journal of Unmanned Vehicle Systems, 4(4), 228\u2013245.","journal-title":"Journal of Unmanned Vehicle Systems"},{"key":"9625_CR2","unstructured":"Parsons, L. S. (1993). Management of Marine Fisheries in Canada Canadian Bulletin of Fisheries and Aquatic Sciences No. 225."},{"issue":"6","key":"9625_CR3","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1016\/S0965-9978(00)00110-1","volume":"32","author":"J Branke","year":"2001","unstructured":"Branke, J., Kau\u00dfler, T., & Schmeck, H. (2001). Guidance in evolutionary multi-objective optimization. Advances in Engineering Software, 32(6), 499\u2013507.","journal-title":"Advances in Engineering Software"},{"key":"9625_CR4","doi-asserted-by":"crossref","unstructured":"Hu, Y., Qing, J. X., Liu, Z. H., et al. (2021). Hovering efficiency optimization of the ducted propeller with weight penalty taken into account. Aerospace Science and Technology, 117, 106937.","DOI":"10.1016\/j.ast.2021.106937"},{"key":"9625_CR5","doi-asserted-by":"crossref","unstructured":"Mi, X., Tian, Y., & Kang, B. (2021). A hybrid multi-criteria decision making approach for assessing health-care waste management technologies based on soft likelihood function and D-numbers.\u00a0Applied Intelligence, 1\u201320.","DOI":"10.1007\/s10489-020-02148-7"},{"key":"9625_CR6","unstructured":"Mosavi, M. R., Khishe, M., & Ebrahimi, E. (2016). Classification of sonar targets using OMKC, genetic algorithms and statistical moments."},{"key":"9625_CR7","doi-asserted-by":"crossref","unstructured":"Carlton, J. S. (2012). Marine propeller & propulsion. Butterworth-Heinemann.","DOI":"10.1016\/B978-0-08-097123-0.00010-1"},{"key":"9625_CR8","doi-asserted-by":"publisher","DOI":"10.1007\/978-94-017-8751-2","volume-title":"Ship design: Methodologies of preliminary design","author":"A Papanikolaou","year":"2014","unstructured":"Papanikolaou, A. (2014). Ship design: Methodologies of preliminary design. Springer."},{"issue":"1","key":"9625_CR9","doi-asserted-by":"publisher","first-page":"43","DOI":"10.1016\/S0263-2241(98)00044-X","volume":"24","author":"P Castellini","year":"1998","unstructured":"Castellini, P., & Santolini, C. (1998). Vibration measurements on blades of a naval propeller rotating in water with tracking laser vibrometer. Measurement, 24(1), 43\u201354.","journal-title":"Measurement"},{"key":"9625_CR10","doi-asserted-by":"crossref","unstructured":"Lv, S., & Song, F. (2022). Particle swarm intelligence and the evolution of cooperation in the spatial public goods game with punishment. Applied Mathematics and Computation, 412, 126586.","DOI":"10.1016\/j.amc.2021.126586"},{"issue":"10","key":"9625_CR11","doi-asserted-by":"publisher","first-page":"4309","DOI":"10.1109\/TNNLS.2020.3017213","volume":"32","author":"Z Fang","year":"2021","unstructured":"Fang, Z., Lu, J., Liu, F., Xuan, J., & Zhang, G. (2021). Open set domain adaptation: Theoretical bound and algorithm. IEEE Transaction on Neural Networks and Learning Systems, 32(10), 4309\u20134322.","journal-title":"IEEE Transaction on Neural Networks and Learning Systems"},{"issue":"4","key":"9625_CR12","doi-asserted-by":"publisher","first-page":"393","DOI":"10.14311\/NNW.2016.26.023","volume":"26","author":"MR Mosavi","year":"2016","unstructured":"Mosavi, M. R., Khishe, M., & Ghamgosar, A. (2016). Classification of sonar data set using neural network trained by Gray Wolf Optimization. Neural Network World, 26(4), 393.","journal-title":"Neural Network World"},{"issue":"73","key":"9625_CR13","first-page":"11","volume":"19","author":"SMR Mousavi","year":"2015","unstructured":"Mousavi, S. M. R., Khisheh, M., Aghababaei, M., & Mohammadzadeh, F. (2015). Approximation of active sonar clutter\u2019s statistical parameters using array\u2019s effective beam-width. Iranian Journal of Marine Science and Technology, 19(73), 11\u201322.","journal-title":"Iranian Journal of Marine Science and Technology"},{"key":"9625_CR14","doi-asserted-by":"crossref","unstructured":"Zhong, L., Fang, Z., Liu, F., et al. (2021). Bridging the theoretical bound and deep algorithms for open set domain adaptation. IEEE Transaction on Neural Networks and Learning Systems, 1\u201315.","DOI":"10.1109\/TNNLS.2021.3119965"},{"key":"9625_CR15","doi-asserted-by":"crossref","unstructured":"Zhang, J., Shaw, A. D., Wang, C., et al. (2021). Aeroelastic model and analysis of an active camber morphing wing. Aerospace Science and Technology, 111, 106534.","DOI":"10.1016\/j.ast.2021.106534"},{"issue":"04","key":"9625_CR16","doi-asserted-by":"publisher","first-page":"229","DOI":"10.5957\/mt1.2003.40.4.229","volume":"40","author":"E Benini","year":"2003","unstructured":"Benini, E. (2003). Multi-objective design optimization of B-screw series propellers using evolutionary algorithms. Marine Technology and SNAME News, 40(04), 229\u2013238.","journal-title":"Marine Technology and SNAME News"},{"key":"9625_CR17","doi-asserted-by":"publisher","first-page":"387","DOI":"10.2112\/SI103-079.1","volume":"103","author":"L Yang","year":"2020","unstructured":"Yang, L. (2020). Marine oil spill control based on discrete mathematical model. Journal of Coastal Research, 103, 387\u2013391.","journal-title":"Journal of Coastal Research"},{"key":"9625_CR18","doi-asserted-by":"publisher","first-page":"15","DOI":"10.1016\/j.apacoust.2016.11.012","volume":"118","author":"M Khishe","year":"2017","unstructured":"Khishe, M., Mosavi, M. R., & Kaveh, M. (2017). Improved migration models of biogeography-based optimization for sonar dataset classification by using neural network. Applied Acoustics, 118, 15\u201329.","journal-title":"Applied Acoustics"},{"issue":"1","key":"9625_CR19","first-page":"1","volume":"68","author":"M Khishe","year":"2014","unstructured":"Khishe, M., Aghababaee, M., & Mohammadzadeh, F. (2014). Active sonar clutter control by using array beamforming. Iranian Journal of Marine Science and Technology, 68(1), 1\u20136.","journal-title":"Iranian Journal of Marine Science and Technology"},{"key":"9625_CR20","unstructured":"Sk\u00e5land, E. K. (2016). The influence of the choice of propeller design tool on propeller performance. Master\u2019s thesis, NTNU."},{"key":"9625_CR21","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili, S. (2015). The ant lion optimizer. Advances in Engineering Software, 83, 80\u201398.","journal-title":"Advances in Engineering Software"},{"key":"9625_CR22","doi-asserted-by":"publisher","first-page":"412","DOI":"10.2112\/SI103-084.1","volume":"103","author":"L Tingqin","year":"2020","unstructured":"Tingqin, L., & Haixia, D. (2020). Automatic calculation method for mechanical load of full rotation crane ship based on flow function theory. Journal of Coastal Research, 103, 412\u2013416.","journal-title":"Journal of Coastal Research"},{"issue":"7","key":"9625_CR23","doi-asserted-by":"publisher","first-page":"581","DOI":"10.1139\/cjce-2018-0352","volume":"46","author":"B Hussein","year":"2019","unstructured":"Hussein, B., & Moselhi, O. (2019). An evolutionary stochastic discrete time-cost trade-off method. Canadian Journal of Civil Engineering, 46(7), 581\u2013600.","journal-title":"Canadian Journal of Civil Engineering"},{"key":"9625_CR24","doi-asserted-by":"crossref","unstructured":"Mahmoodabadi, M. J., Shahangian, M. M., & Nejadkourki, N. (2021). An optimal MRAC\u2013ASMC scheme for robot manipulators based on the artificial bee colony.\u00a0Transactions of the Canadian Society for Mechanical Engineering, (ja).","DOI":"10.1139\/tcsme-2019-0228"},{"key":"9625_CR25","unstructured":"Burton, P. J., Messier, C., Smith, D. W., & Adamowicz, W. L. (Eds.). (2003).\u00a0Towards sustainable management of the boreal forest. NRC Research Press."},{"key":"9625_CR26","doi-asserted-by":"publisher","first-page":"111","DOI":"10.1016\/j.knosys.2018.07.040","volume":"161","author":"F Gursoy","year":"2018","unstructured":"Gursoy, F., & Gunnec, D. (2018). Influence maximization in social networks under deterministic linear threshold model. Knowledge-Based Systems, 161, 111\u2013123.","journal-title":"Knowledge-Based Systems"},{"issue":"3","key":"9625_CR27","doi-asserted-by":"publisher","first-page":"6843","DOI":"10.1016\/j.eswa.2008.08.022","volume":"36","author":"MH Aghdam","year":"2009","unstructured":"Aghdam, M. H., Ghasem-Aghaee, N., & Basiri, M. E. (2009). Text feature selection using ant colony optimization. Expert Systems with Applications, 36(3), 6843\u20136853.","journal-title":"Expert Systems with Applications"},{"key":"9625_CR28","doi-asserted-by":"publisher","first-page":"144","DOI":"10.1016\/j.knosys.2015.04.007","volume":"84","author":"P Moradi","year":"2015","unstructured":"Moradi, P., & Rostami, M. (2015). Integration of graph clustering with ant colony optimization for feature selection. Knowledge-Based Systems, 84, 144\u2013161.","journal-title":"Knowledge-Based Systems"},{"key":"9625_CR29","doi-asserted-by":"crossref","unstructured":"Paniri, M., Dowlatshahi, M. B., & Nezamabadi-Pour, H. (2020). MLACO: A multi-label feature selection algorithm based on ant colony optimization.\u00a0Knowledge-Based Systems,\u00a0192, 105285.","DOI":"10.1016\/j.knosys.2019.105285"},{"key":"9625_CR30","doi-asserted-by":"publisher","first-page":"270","DOI":"10.1016\/j.knosys.2018.06.025","volume":"159","author":"H Ghimatgar","year":"2018","unstructured":"Ghimatgar, H., Kazemi, K., Helfroush, M. S., & Aarabi, A. (2018). An improved feature selection algorithm based on graph clustering and ant colony optimization. Knowledge-Based Systems, 159, 270\u2013285.","journal-title":"Knowledge-Based Systems"},{"issue":"11","key":"9625_CR31","doi-asserted-by":"publisher","first-page":"1750185","DOI":"10.1142\/S0218126617501857","volume":"26","author":"MR Mosavi","year":"2017","unstructured":"Mosavi, M. R., & Khishe, M. (2017). Training a feed-forward neural network using particle swarm optimizer with autonomous groups for sonar target classification. Journal of Circuits, Systems and Computers, 26(11), 1750185.","journal-title":"Journal of Circuits, Systems and Computers"},{"issue":"1","key":"9625_CR32","doi-asserted-by":"publisher","first-page":"108","DOI":"10.1007\/s11633-018-1158-3","volume":"17","author":"S Afrakhteh","year":"2020","unstructured":"Afrakhteh, S., Mosavi, M. R., Khishe, M., & Ayatollahi, A. (2020). Accurate classification of EEG signals using neural networks trained by hybrid population-physic-based algorithm. International Journal of Automation and Computing, 17(1), 108\u2013122.","journal-title":"International Journal of Automation and Computing"},{"issue":"5","key":"9625_CR33","doi-asserted-by":"publisher","first-page":"739","DOI":"10.1007\/s10766-013-0275-4","volume":"42","author":"F Ramezani","year":"2014","unstructured":"Ramezani, F., Lu, J., & Hussain, F. K. (2014). Task-based system load balancing in cloud computing using particle swarm optimization. International Journal of Parallel Programming, 42(5), 739\u2013754.","journal-title":"International Journal of Parallel Programming"},{"issue":"2","key":"9625_CR34","doi-asserted-by":"publisher","first-page":"82","DOI":"10.1109\/4235.771163","volume":"3","author":"X Yao","year":"1999","unstructured":"Yao, X., Liu, Y., & Lin, G. (1999). Evolutionary programming made faster. IEEE Transactions on Evolutionary computation, 3(2), 82\u2013102.","journal-title":"IEEE Transactions on Evolutionary computation"},{"key":"9625_CR35","unstructured":"Tetko, I. V., Tanchuk, V. Y., & Luik, A. I. (1994). Application of an evolutionary algorithm to the structure-activity relationship. In\u00a0Proceedings 3rd Annual Conference on Evolutionary Programming\u00a0(pp. 109\u2013119). NJ: J. World Scientific, River Edge."},{"key":"9625_CR36","doi-asserted-by":"publisher","first-page":"58","DOI":"10.1016\/j.knosys.2018.01.028","volume":"146","author":"S Song","year":"2018","unstructured":"Song, S., Gao, S., Chen, X., Jia, D., Qian, X., & Todo, Y. (2018). AIMOES: Archive information assisted multi-objective evolutionary strategy for ab initio protein structure prediction. Knowledge-Based Systems, 146, 58\u201372.","journal-title":"Knowledge-Based Systems"},{"key":"9625_CR37","doi-asserted-by":"publisher","first-page":"103","DOI":"10.1016\/j.knosys.2019.03.003","volume":"174","author":"AS Akopov","year":"2019","unstructured":"Akopov, A. S., Beklaryan, L. A., Thakur, M., & Verma, B. D. (2019). Parallel multi-agent real-coded genetic algorithm for large-scale black-box single-objective optimisation. Knowledge-Based Systems, 174, 103\u2013122.","journal-title":"Knowledge-Based Systems"},{"key":"9625_CR38","doi-asserted-by":"publisher","first-page":"116","DOI":"10.1016\/j.knosys.2017.02.013","volume":"123","author":"AK Das","year":"2017","unstructured":"Das, A. K., Das, S., & Ghosh, A. (2017). Ensemble feature selection using bi-objective genetic algorithm. Knowledge-Based Systems, 123, 116\u2013127.","journal-title":"Knowledge-Based Systems"},{"key":"9625_CR39","unstructured":"Wolpert, D. H., & Macready, W. G. (1995).\u00a0No free lunch theorems for search\u00a0(Vol. 10). Technical Report SFI-TR-95-02-010, Santa Fe Institute."},{"key":"9625_CR40","doi-asserted-by":"crossref","unstructured":"Eberhart, R., & Kennedy, J. (1995). A new optimizer using particle swarm theory. In\u00a0MHS\u201995. Proceedings of the Sixth International Symposium on Micro Machine and Human Science\u00a0(pp. 39\u201343). IEEE.","DOI":"10.1109\/MHS.1995.494215"},{"issue":"4","key":"9625_CR41","doi-asserted-by":"publisher","first-page":"4623","DOI":"10.1007\/s11277-017-4110-x","volume":"95","author":"MR Mosavi","year":"2017","unstructured":"Mosavi, M. R., Khishe, M., & Akbarisani, M. (2017). Neural network trained by biogeography-based optimizer with chaos for sonar data set classification. Wireless Personal Communications, 95(4), 4623\u20134642.","journal-title":"Wireless Personal Communications"},{"issue":"2","key":"9625_CR42","doi-asserted-by":"publisher","first-page":"405","DOI":"10.1007\/s10470-018-1366-3","volume":"100","author":"M Kaveh","year":"2019","unstructured":"Kaveh, M., Khishe, M., & Mosavi, M. R. (2019). Design and implementation of a neighborhood search biogeography-based optimization trainer for classifying sonar dataset using multi-layer perceptron neural network. Analog Integrated Circuits and Signal Processing, 100(2), 405\u2013428.","journal-title":"Analog Integrated Circuits and Signal Processing"},{"key":"9625_CR43","doi-asserted-by":"publisher","first-page":"91","DOI":"10.1016\/j.eswa.2016.06.004","volume":"62","author":"E Zorarpac\u0131","year":"2016","unstructured":"Zorarpac\u0131, E., & \u00d6zel, S. A. (2016). A hybrid approach of differential evolution and artificial bee colony for feature selection. Expert Systems with Applications, 62, 91\u2013103.","journal-title":"Expert Systems with Applications"},{"key":"9625_CR44","doi-asserted-by":"publisher","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","volume":"114","author":"S Mirjalili","year":"2017","unstructured":"Mirjalili, S., Gandomi, A. H., Mirjalili, S. Z., Saremi, S., Faris, H., & Mirjalili, S. M. (2017). Salp Swarm Algorithm: A bio-inspired optimizer for engineering design problems. Advances in Engineering Software, 114, 163\u2013191.","journal-title":"Advances in Engineering Software"},{"key":"9625_CR45","doi-asserted-by":"publisher","first-page":"3099","DOI":"10.1109\/JIOT.2020.3033473","volume":"8","author":"B Cao","year":"2021","unstructured":"Cao, B., et al. (2021). RFID reader anticollision based on distributed parallel particle swarm optimization. IEEE Internet of Things Journal, 8, 3099\u20133107.","journal-title":"IEEE Internet of Things Journal"},{"key":"9625_CR46","doi-asserted-by":"publisher","first-page":"98","DOI":"10.1016\/j.oceaneng.2019.04.013","volume":"181","author":"M Khishe","year":"2019","unstructured":"Khishe, M., & Mohammadi, H. (2019). Passive sonar target classification using multi-layer perceptron trained by salp swarm algorithm. Ocean Engineering, 181, 98\u2013108.","journal-title":"Ocean Engineering"},{"key":"9625_CR47","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/s00477-018-1600-7","volume":"33","author":"W Huo","year":"2019","unstructured":"Huo, W., Li, Z., Wang, J., et al. (2019). Multiple hydrological models comparison and an improved Bayesian model averaging approach for ensemble prediction over semi-humid regions. Stochastic Environmental Research and Risk Assessment, 33, 217\u2013238.","journal-title":"Stochastic Environmental Research and Risk Assessment"},{"key":"9625_CR48","doi-asserted-by":"publisher","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili, S. (2015). Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems, 89, 228\u2013249.","journal-title":"Knowledge-Based Systems"},{"key":"9625_CR49","doi-asserted-by":"publisher","first-page":"120","DOI":"10.1016\/j.knosys.2015.12.022","volume":"96","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S. (2016). SCA: A sine cosine algorithm for solving optimization problems. Knowledge-Based Systems, 96, 120\u2013133.","journal-title":"Knowledge-Based Systems"},{"issue":"4","key":"9625_CR50","doi-asserted-by":"publisher","first-page":"1053","DOI":"10.1007\/s00521-015-1920-1","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S. (2016). Dragonfly algorithm: A new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Computing and Applications, 27(4), 1053\u20131073.","journal-title":"Neural Computing and Applications"},{"issue":"4","key":"9625_CR51","doi-asserted-by":"publisher","first-page":"2241","DOI":"10.1007\/s11277-019-06520-w","volume":"108","author":"M Khishe","year":"2019","unstructured":"Khishe, M., & Safari, A. (2019). Classification of sonar targets using an MLP neural network trained by dragonfly algorithm. Wireless Personal Communications, 108(4), 2241\u20132260.","journal-title":"Wireless Personal Communications"},{"key":"9625_CR52","doi-asserted-by":"publisher","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"M Seyedali","year":"2015","unstructured":"Seyedali, M. (2015). The ant lion optimizer. Advances in Engineering Software, 83, 80\u201398.","journal-title":"Advances in Engineering Software"},{"key":"9625_CR53","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.knosys.2014.07.025","volume":"75","author":"H Salimi","year":"2015","unstructured":"Salimi, H. (2015). Stochastic fractal search: A powerful metaheuristic algorithm. Knowledge-Based Systems, 75, 1\u201318.","journal-title":"Knowledge-Based Systems"},{"key":"9625_CR54","doi-asserted-by":"publisher","first-page":"121","DOI":"10.1016\/j.apacoust.2018.03.012","volume":"137","author":"M Khishe","year":"2018","unstructured":"Khishe, M., Mosavi, M. R., & Moridi, A. (2018). Chaotic fractal walk trainer for sonar data set classification using multi-layer perceptron neural network and its hardware implementation. Applied Acoustics, 137, 121\u2013139.","journal-title":"Applied Acoustics"},{"key":"9625_CR55","doi-asserted-by":"publisher","first-page":"188","DOI":"10.1016\/j.ins.2014.01.038","volume":"269","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Let a biogeography-based optimizer train your multi-layer perceptron. Information Sciences, 269, 188\u2013209.","journal-title":"Information Sciences"},{"key":"9625_CR56","doi-asserted-by":"crossref","unstructured":"Abedifar, V., Eshghi, M., Mirjalili, S., & Mirjalili, S. M. (2013). An optimized virtual network mapping using PSO in cloud computing. In\u00a02013 21st Iranian Conference on Electrical Engineering (ICEE)\u00a0(pp. 1\u20136). IEEE.","DOI":"10.1109\/IranianCEE.2013.6599723"},{"issue":"4","key":"9625_CR57","doi-asserted-by":"publisher","first-page":"1018","DOI":"10.1109\/TMM.2014.2307169","volume":"16","author":"LS Nguyen","year":"2014","unstructured":"Nguyen, L. S., Frauendorfer, D., Mast, M. S., & Gatica-Perez, D. (2014). Hire me: Computational inference of hirability in employment interviews based on nonverbal behavior. IEEE Transactions on Multimedia, 16(4), 1018\u20131031.","journal-title":"IEEE Transactions on Multimedia"},{"issue":"3","key":"9625_CR58","doi-asserted-by":"publisher","first-page":"217","DOI":"10.1007\/s13042-012-0089-5","volume":"4","author":"M Barakat","year":"2013","unstructured":"Barakat, M., Lefebvre, D., Khalil, M., Druaux, F., & Mustapha, O. (2013). Parameter selection algorithm with self adaptive growing neural network classifier for diagnosis issues. International Journal of Machine Learning and Cybernetics, 4(3), 217\u2013233.","journal-title":"International Journal of Machine Learning and Cybernetics"},{"key":"9625_CR59","doi-asserted-by":"publisher","first-page":"54","DOI":"10.1016\/j.ins.2012.01.011","volume":"193","author":"ZX Guo","year":"2012","unstructured":"Guo, Z. X., Wong, W. K., & Li, M. (2012). Sparsely connected neural network-based time series forecasting. Information Sciences, 193, 54\u201371.","journal-title":"Information Sciences"},{"issue":"48","key":"9625_CR60","first-page":"7","volume":"24","author":"BC Cs\u00e1ji","year":"2001","unstructured":"Cs\u00e1ji, B. C. (2001). Approximation with artificial neural networks. Faculty of Sciences, Etvs Lornd University, Hungary, 24(48), 7.","journal-title":"Faculty of Sciences, Etvs Lornd University, Hungary"},{"key":"9625_CR61","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46\u201361.","journal-title":"Advances in Engineering Software"},{"key":"9625_CR62","doi-asserted-by":"crossref","unstructured":"Hedayatzadeh, R., Salmassi, F. A., Keshtgari, M., Akbari, R., & Ziarati, K. (2010). Termite colony optimization: A novel approach for optimizing continuous problems. In\u00a02010 18th Iranian Conference on Electrical Engineering\u00a0(pp. 553\u2013558). IEEE.","DOI":"10.1109\/IRANIANCEE.2010.5507009"},{"issue":"6","key":"9625_CR63","doi-asserted-by":"publisher","first-page":"4683","DOI":"10.1007\/s13369-014-1156-x","volume":"39","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Lewis, A., & Sadiq, A. S. (2014). Autonomous particles groups for particle swarm optimization. Arabian Journal for Science and Engineering, 39(6), 4683\u20134697.","journal-title":"Arabian Journal for Science and Engineering"},{"issue":"3","key":"9625_CR64","doi-asserted-by":"publisher","first-page":"663","DOI":"10.1007\/s00521-013-1525-5","volume":"25","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Mirjalili, S. M., & Yang, X. S. (2014). Binary bat algorithm. Neural Computing and Applications, 25(3), 663\u2013681.","journal-title":"Neural Computing and Applications"},{"key":"9625_CR65","doi-asserted-by":"crossref","unstructured":"Wang, G. G., Gandomi, A. H., & Alavi, A. H. (2013). A chaotic particle-swarm krill herd algorithm for global numerical optimization.\u00a0Kybernetes.","DOI":"10.1155\/2013\/213853"},{"issue":"9\u201310","key":"9625_CR66","doi-asserted-by":"publisher","first-page":"2454","DOI":"10.1016\/j.apm.2013.10.052","volume":"38","author":"GG Wang","year":"2014","unstructured":"Wang, G. G., Gandomi, A. H., & Alavi, A. H. (2014). An effective krill herd algorithm with migration operator in biogeography-based optimization. Applied Mathematical Modelling, 38(9\u201310), 2454\u20132462.","journal-title":"Applied Mathematical Modelling"},{"key":"9625_CR67","unstructured":"Bertschneider, H., Bosschers, J., Choi, G. H., Ciappi, E., Farabee, T., Kawakita, C., & Tang, D. (2014). Specialist committee on hydrodynamic noise.\u00a0Final Report and Recommendations to the 27th ITTC. Copenhagen, Sweden,\u00a045."},{"issue":"78","key":"9625_CR68","first-page":"65","volume":"20","author":"SM Mousavi","year":"2016","unstructured":"Mousavi, S. M., Kaveh, M., & Khishe, M. (2016). Sonar Data Set Classification Using MLP Neural Network Trained By Modified Biogeography-Based Optimization. Iranian Journal of Marine Science and Technology, 20(78), 65\u201374.","journal-title":"Iranian Journal of Marine Science and Technology"}],"container-title":["Wireless Personal Communications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11277-022-09625-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11277-022-09625-x\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11277-022-09625-x.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,7,6]],"date-time":"2022-07-06T13:06:47Z","timestamp":1657112807000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11277-022-09625-x"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,4,8]]},"references-count":68,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2022,7]]}},"alternative-id":["9625"],"URL":"https:\/\/doi.org\/10.1007\/s11277-022-09625-x","relation":{},"ISSN":["0929-6212","1572-834X"],"issn-type":[{"value":"0929-6212","type":"print"},{"value":"1572-834X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,4,8]]},"assertion":[{"value":"7 February 2022","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 April 2022","order":2,"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 there is no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}