{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,3,26]],"date-time":"2024-03-26T01:08:48Z","timestamp":1711415328433},"reference-count":68,"publisher":"Springer Science and Business Media LLC","issue":"6","license":[{"start":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T00:00:00Z","timestamp":1699401600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T00:00:00Z","timestamp":1699401600000},"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 Supercomput"],"published-print":{"date-parts":[[2024,4]]},"DOI":"10.1007\/s11227-023-05728-9","type":"journal-article","created":{"date-parts":[[2023,11,8]],"date-time":"2023-11-08T07:02:37Z","timestamp":1699426957000},"page":"7483-7506","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Chipping value prediction for dicing saw based on sparrow search algorithm and neural networks"],"prefix":"10.1007","volume":"80","author":[{"given":"Jun","family":"Shi","sequence":"first","affiliation":[]},{"given":"Peiyi","family":"Zhang","sequence":"additional","affiliation":[]},{"given":"Sihan","family":"Du","sequence":"additional","affiliation":[]},{"given":"Wanyong","family":"Liang","sequence":"additional","affiliation":[]},{"given":"Weifeng","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Qingbo","family":"Li","sequence":"additional","affiliation":[]},{"given":"Hechao","family":"Hou","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2023,11,8]]},"reference":[{"key":"5728_CR1","doi-asserted-by":"crossref","unstructured":"Edler S, Schels A, Biba J, Hansch W, Bachmann M, D\u00fcsberg F, Werber M, Langer C, Meyer M, Bergen D et al (2021) Silicon field emitters fabricated by dicing-saw and wet-chemical-etching. J Vac Sci Technol B 39(1):027001","DOI":"10.1116\/6.0000466"},{"issue":"7\u20138","key":"5728_CR2","doi-asserted-by":"crossref","first-page":"2299","DOI":"10.1007\/s00170-020-05798-6","volume":"109","author":"J Wu","year":"2020","unstructured":"Wu J, Chen G, Chen F (2020) Positioning accuracy control of dual-axis dicing saw for machining semiconductor chip. Int J Adv Manuf Technol 109(7\u20138):2299\u20132310","journal-title":"Int J Adv Manuf Technol"},{"key":"5728_CR3","first-page":"10","volume":"234","author":"M Vagues","year":"2003","unstructured":"Vagues M (2003) Analysing backside chipping issues of the die at wafer saw. Partial Fulfillment MatE 234:10\u201323","journal-title":"Partial Fulfillment MatE"},{"issue":"2","key":"5728_CR4","doi-asserted-by":"crossref","first-page":"130","DOI":"10.3390\/e23020130","volume":"23","author":"W Zheng","year":"2021","unstructured":"Zheng W, Luo Y, Chen Y, Wang X (2021) A simplified fractional order PID controller\u2019s optimal tuning: a case study on a PMSM speed servo. Entropy 23(2):130","journal-title":"Entropy"},{"issue":"2","key":"5728_CR5","doi-asserted-by":"crossref","first-page":"491","DOI":"10.1109\/TR.2012.2194177","volume":"61","author":"DA Tobon-Mejia","year":"2012","unstructured":"Tobon-Mejia DA, Medjaher K, Zerhouni N, Tripot G (2012) A data-driven failure prognostics method based on mixture of gaussians hidden Markov models. IEEE Trans Reliab 61(2):491\u2013503","journal-title":"IEEE Trans Reliab"},{"key":"5728_CR6","doi-asserted-by":"crossref","first-page":"344","DOI":"10.1016\/j.egyr.2019.11.086","volume":"6","author":"N Khammayom","year":"2020","unstructured":"Khammayom N, Maruyama N, Chaichana C (2020) Simplified model of cooling\/heating load prediction for various air-conditioned room types. Energy Rep 6:344\u2013351","journal-title":"Energy Rep"},{"issue":"19","key":"5728_CR7","doi-asserted-by":"crossref","first-page":"6108","DOI":"10.3390\/en14196108","volume":"14","author":"A Sel","year":"2021","unstructured":"Sel A, Sel B, Coskun U, Kasnakoglu C (2021) Comparative study of an EKF-based parameter estimation and a nonlinear optimization-based estimation on PMSM system identification. Energies 14(19):6108","journal-title":"Energies"},{"issue":"3","key":"5728_CR8","doi-asserted-by":"crossref","first-page":"2703","DOI":"10.1007\/s10489-021-02507-y","volume":"52","author":"Y Peng","year":"2022","unstructured":"Peng Y, Gong D, Deng C, Li H, Cai H, Zhang H (2022) An automatic hyperparameter optimization DNN model for precipitation prediction. Appl Intell 52(3):2703\u20132719","journal-title":"Appl Intell"},{"issue":"6","key":"5728_CR9","doi-asserted-by":"crossref","first-page":"713","DOI":"10.1049\/iet-spr.2017.0320","volume":"12","author":"J Zhao","year":"2018","unstructured":"Zhao J, Mao X, Chen L (2018) Learning deep features to recognise speech emotion using merged deep CNN. IET Signal Proc 12(6):713\u2013721","journal-title":"IET Signal Proc"},{"issue":"1","key":"5728_CR10","doi-asserted-by":"crossref","first-page":"8385","DOI":"10.1038\/s41598-019-44852-6","volume":"9","author":"K Park","year":"2019","unstructured":"Park K, Kim J, Lee J (2019) Visual field prediction using recurrent neural network. Sci Rep 9(1):8385","journal-title":"Sci Rep"},{"key":"5728_CR11","doi-asserted-by":"crossref","unstructured":"Zhang Y, Gao G et al (2022) Optimization and evaluation of an intelligent short-term blood glucose prediction model based on noninvasive monitoring and deep learning techniques. J Healthc Eng 2022:8956850","DOI":"10.1155\/2022\/8956850"},{"issue":"14","key":"5728_CR12","doi-asserted-by":"crossref","first-page":"3896","DOI":"10.3390\/s20143896","volume":"20","author":"M Munoz-Organero","year":"2020","unstructured":"Munoz-Organero M (2020) Deep physiological model for blood glucose prediction in t1dm patients. Sensors 20(14):3896","journal-title":"Sensors"},{"key":"5728_CR13","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1016\/j.microrel.2018.10.013","volume":"91","author":"T-J Su","year":"2018","unstructured":"Su T-J, Chen Y-F, Cheng J-C, Chiu C-L (2018) An artificial neural network approach for wafer dicing saw quality prediction. Microelectron Reliab 91:257\u2013261","journal-title":"Microelectron Reliab"},{"key":"5728_CR14","doi-asserted-by":"crossref","unstructured":"Li Z, Zeng J, Zhong Y (2019) An improved moth-flame algorithm based on differential evolution and shuffled frog leaping algorithm. 2019 Chinese Automation Congress (CAC), pp 4858\u20134863","DOI":"10.1109\/CAC48633.2019.8996624"},{"key":"5728_CR15","doi-asserted-by":"crossref","first-page":"107847","DOI":"10.1016\/j.optlastec.2022.107847","volume":"149","author":"MN Rohman","year":"2022","unstructured":"Rohman MN, Ho J-R, Tung P-C, Tsui H-P, Lin C-K (2022) Prediction and optimization of geometrical quality for pulsed laser cutting of non-oriented electrical steel sheet. Opt Laser Technol 149:107847","journal-title":"Opt Laser Technol"},{"issue":"24","key":"5728_CR16","doi-asserted-by":"crossref","first-page":"4631","DOI":"10.3390\/math10244631","volume":"10","author":"BR Chang","year":"2022","unstructured":"Chang BR, Tsai H-F, Mo H-Y (2022) Detection and prediction of chipping in wafer grinding based on dicing signal. Mathematics 10(24):4631","journal-title":"Mathematics"},{"key":"5728_CR17","doi-asserted-by":"crossref","first-page":"119887","DOI":"10.1016\/j.energy.2021.119887","volume":"221","author":"T Peng","year":"2021","unstructured":"Peng T, Zhang C, Zhou J, Nazir MS (2021) An integrated framework of bi-directional long-short term memory (BiLSTM) based on sine cosine algorithm for hourly solar radiation forecasting. Energy 221:119887","journal-title":"Energy"},{"issue":"14","key":"5728_CR18","doi-asserted-by":"crossref","first-page":"7188","DOI":"10.3390\/app12147188","volume":"12","author":"L Lyu","year":"2022","unstructured":"Lyu L, Wang Z, Yun H, Yang Z (2022) Deep knowledge tracing based on spatial and temporal representation learning for learning performance prediction. Appl Sci 12(14):7188","journal-title":"Appl Sci"},{"issue":"11\u201312","key":"5728_CR19","doi-asserted-by":"crossref","first-page":"4025","DOI":"10.1007\/s00170-022-10455-1","volume":"123","author":"X Li","year":"2022","unstructured":"Li X, Qin X, Wu J, Yang J (2022) Tool wear prediction based on convolutional bidirectional LSTM model with improved particle swarm optimization. Int J Adv Manuf Technol 123(11\u201312):4025\u20134039","journal-title":"Int J Adv Manuf Technol"},{"key":"5728_CR20","doi-asserted-by":"crossref","first-page":"4519","DOI":"10.1007\/s11063-022-11055-6","volume":"55","author":"M Kaveh","year":"2022","unstructured":"Kaveh M, Mesgari MS (2022) Application of meta-heuristic algorithms for training neural networks and deep learning architectures: a comprehensive review. Neural Process Lett 55:4519\u20134622","journal-title":"Neural Process Lett"},{"key":"5728_CR21","volume":"285","author":"Y Zhou","year":"2023","unstructured":"Zhou Y, Wang S, Xie Y, Shen X, Fernandez C (2023) Remaining useful life prediction and state of health diagnosis for lithium-ion batteries based on improved grey wolf optimization algorithm-deep extreme learning machine algorithm. Energy 285:128761","journal-title":"Energy"},{"key":"5728_CR22","doi-asserted-by":"crossref","DOI":"10.1016\/j.energy.2023.126660","volume":"268","author":"C Sekhar","year":"2023","unstructured":"Sekhar C, Dahiya R (2023) Robust framework based on hybrid deep learning approach for short term load forecasting of building electricity demand. Energy 268:126660","journal-title":"Energy"},{"issue":"8","key":"5728_CR23","doi-asserted-by":"crossref","first-page":"4073","DOI":"10.3390\/app12084073","volume":"12","author":"L Qian","year":"2022","unstructured":"Qian L, Zheng Y, Li L, Ma Y, Zhou C (2022) A new method of inland water ship trajectory prediction based on long short-term memory network optimized by genetic algorithm. Appl Sci 12(8):4073","journal-title":"Appl Sci"},{"key":"5728_CR24","volume":"275","author":"M Yu","year":"2023","unstructured":"Yu M, Niu D, Wang K, Du R, Yu X, Sun L (2023) Short-term photovoltaic power point-interval forecasting based on double-layer decomposition and WOA-BiLSTM-attention and considering weather classification. Energy 275:127348","journal-title":"Energy"},{"key":"5728_CR25","doi-asserted-by":"crossref","first-page":"161524","DOI":"10.1109\/ACCESS.2019.2951370","volume":"7","author":"L Cao","year":"2019","unstructured":"Cao L, Cai Y, Yue Y (2019) Swarm intelligence-based performance optimization for mobile wireless sensor networks: survey, challenges, and future directions. IEEE Access 7:161524\u2013161553","journal-title":"IEEE Access"},{"issue":"1","key":"5728_CR26","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1007\/s11831-022-09800-0","volume":"30","author":"A Mohammadi","year":"2023","unstructured":"Mohammadi A, Sheikholeslam F, Mirjalili S (2023) Nature-inspired metaheuristic search algorithms for optimizing benchmark problems: inclined planes system optimization to state-of-the-art methods. Arch Comput Methods Eng 30(1):331\u2013389","journal-title":"Arch Comput Methods Eng"},{"key":"5728_CR27","doi-asserted-by":"crossref","first-page":"1103","DOI":"10.1007\/s11831-020-09412-6","volume":"28","author":"M Sharma","year":"2021","unstructured":"Sharma M (2021) A comprehensive analysis of nature-inspired meta-heuristic techniques for feature selection problem. Arch Comput Methods Eng 28:1103\u20131127","journal-title":"Arch Comput Methods Eng"},{"issue":"11\u201312","key":"5728_CR28","doi-asserted-by":"crossref","first-page":"4399","DOI":"10.1007\/s00170-022-10466-y","volume":"123","author":"J Shi","year":"2022","unstructured":"Shi J, Zhang Y, Sun Y, Cao W, Zhou L (2022) Tool life prediction of dicing saw based on PSO-BP neural network. Int J Adv Manuf Technol 123(11\u201312):4399\u20134412","journal-title":"Int J Adv Manuf Technol"},{"issue":"23","key":"5728_CR29","doi-asserted-by":"crossref","first-page":"16293","DOI":"10.3390\/su142316293","volume":"14","author":"P Suanpang","year":"2022","unstructured":"Suanpang P, Jamjuntr P, Jermsittiparsert K, Kaewyong P (2022) Tourism service scheduling in smart city based on hybrid genetic algorithm simulated annealing algorithm. Sustainability 14(23):16293","journal-title":"Sustainability"},{"key":"5728_CR30","doi-asserted-by":"crossref","first-page":"1841","DOI":"10.1007\/s10462-020-09893-8","volume":"54","author":"A Tzanetos","year":"2021","unstructured":"Tzanetos A, Dounias G (2021) Nature inspired optimization algorithms or simply variations of metaheuristics? Artif Intell Rev 54:1841\u20131862","journal-title":"Artif Intell Rev"},{"key":"5728_CR31","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/978-3-030-19638-7_8","volume-title":"Optimization of manufacturing processes","author":"NA Zolpakar","year":"2020","unstructured":"Zolpakar NA, Lodhi SS, Pathak S, Sharma MA (2020) Application of multi-objective genetic algorithm (MOGA) optimization in machining processes. In: Gupta K, Gupta MK (eds) Optimization of manufacturing processes. Springer, Berlin, pp 185\u2013199"},{"key":"5728_CR32","doi-asserted-by":"crossref","first-page":"1509","DOI":"10.1016\/j.matpr.2021.12.047","volume":"57","author":"P Chaudhari","year":"2022","unstructured":"Chaudhari P, Thakur AK, Kumar R, Banerjee N, Kumar A (2022) Comparison of NSGA-III with NSGA-II for multi objective optimization of adiabatic styrene reactor. Mater Today Proc 57:1509\u20131514","journal-title":"Mater Today Proc"},{"key":"5728_CR33","doi-asserted-by":"crossref","first-page":"795","DOI":"10.1007\/s00170-013-5513-9","volume":"71","author":"H Zhang","year":"2014","unstructured":"Zhang H, Liu H, Li L (2014) Research on a kind of assembly sequence planning based on immune algorithm and particle swarm optimization algorithm. Int J Adv Manuf Technol 71:795\u2013808","journal-title":"Int J Adv Manuf Technol"},{"issue":"03","key":"5728_CR34","doi-asserted-by":"crossref","first-page":"2050031","DOI":"10.1142\/S0219455420500315","volume":"20","author":"Q Han","year":"2020","unstructured":"Han Q, Zhang X, Xu K, Du X (2020) Free parameter optimization of DTMDs based on improved hybrid genetic-simulated annealing algorithm. Int J Struct Stab Dyn 20(03):2050031","journal-title":"Int J Struct Stab Dyn"},{"key":"5728_CR35","doi-asserted-by":"crossref","first-page":"576","DOI":"10.1016\/j.ins.2022.08.115","volume":"612","author":"W Deng","year":"2022","unstructured":"Deng W, Zhang L, Zhou X, Zhou Y, Sun Y, Zhu W, Chen H, Deng W, Chen H, Zhao H (2022) Multi-strategy particle swarm and ant colony hybrid optimization for airport taxiway planning problem. Inf Sci 612:576\u2013593","journal-title":"Inf Sci"},{"key":"5728_CR36","doi-asserted-by":"crossref","first-page":"417","DOI":"10.1007\/s10462-016-9486-6","volume":"47","author":"S Akyol","year":"2017","unstructured":"Akyol S, Alatas B (2017) Plant intelligence based metaheuristic optimization algorithms. Artif Intell Rev 47:417\u2013462","journal-title":"Artif Intell Rev"},{"key":"5728_CR37","doi-asserted-by":"crossref","first-page":"153456","DOI":"10.1109\/ACCESS.2021.3128433","volume":"9","author":"C Wu","year":"2021","unstructured":"Wu C, Fu X, Pei J (2021) A novel sparrow search algorithm for the traveling salesman problem. IEEE Access 9:153456\u2013153471","journal-title":"IEEE Access"},{"issue":"4","key":"5728_CR38","doi-asserted-by":"crossref","first-page":"1224","DOI":"10.3390\/s21041224","volume":"21","author":"G Liu","year":"2021","unstructured":"Liu G, Shu C, Liang Z, Peng B (2021) A modified sparrow search algorithm with application in 3d route planning for UAV. Sensors 21(4):1224","journal-title":"Sensors"},{"key":"5728_CR39","volume":"329","author":"M Yang","year":"2023","unstructured":"Yang M, Liu Y (2023) Research on the potential for china to achieve carbon neutrality: a hybrid prediction model integrated with elman neural network and sparrow search algorithm. J Environ Manag 329:117081","journal-title":"J Environ Manag"},{"issue":"24","key":"5728_CR40","doi-asserted-by":"crossref","first-page":"6476","DOI":"10.1002\/cpe.6476","volume":"33","author":"H Wang","year":"2021","unstructured":"Wang H, Wu X (2021) Forecasting hydropower generation by GFDL-CM3 climate model and hybrid hydrological-Elman neural network model based on improved sparrow search algorithm (ISSA). Concurr Comput Pract Exp 33(24):6476","journal-title":"Concurr Comput Pract Exp"},{"key":"5728_CR41","doi-asserted-by":"crossref","first-page":"14997","DOI":"10.1016\/j.egyr.2022.11.051","volume":"8","author":"X Ai","year":"2022","unstructured":"Ai X, Li S, Xu H (2022) Short-term wind speed forecasting based on two-stage preprocessing method, sparrow search algorithm and long short-term memory neural network. Energy Rep 8:14997\u201315010","journal-title":"Energy Rep"},{"issue":"9","key":"5728_CR42","doi-asserted-by":"crossref","first-page":"1579","DOI":"10.3390\/sym13091579","volume":"13","author":"X Wang","year":"2021","unstructured":"Wang X, Gao X, Wang Z, Ma C, Song Z (2021) A combined model based on EOBL-CSSA-LSSVM for power load forecasting. Symmetry 13(9):1579","journal-title":"Symmetry"},{"key":"5728_CR43","volume":"261","author":"X Li","year":"2022","unstructured":"Li X, Guo M, Zhang R (2022) A data-driven prediction model for maximum pitting corrosion depth of subsea oil pipelines using SSA-LSTM approach. Ocean Eng 261:112062","journal-title":"Ocean Eng"},{"key":"5728_CR44","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1016\/j.inffus.2017.12.007","volume":"44","author":"D Charte","year":"2018","unstructured":"Charte D, Charte F, Garc\u00eda S, Jesus MJ, Herrera F (2018) A practical tutorial on autoencoders for nonlinear feature fusion: taxonomy, models, software and guidelines. Inf Fusion 44:78\u201396","journal-title":"Inf Fusion"},{"key":"5728_CR45","doi-asserted-by":"crossref","DOI":"10.1016\/j.cosrev.2021.100378","volume":"40","author":"F Anowar","year":"2021","unstructured":"Anowar F, Sadaoui S, Selim B (2021) Conceptual and empirical comparison of dimensionality reduction algorithms (PCA, KPCA, LDA, MDS, SVD, LLE, ISOMAP, LE, ICA, t-SNE). Comput Sci Rev 40:100378","journal-title":"Comput Sci Rev"},{"key":"5728_CR46","unstructured":"Zhi S, Yuan L (2023) Nonlinear process fault detection based on KPCA and SSA optimized SVM. Comput Mod 0(06):15"},{"key":"5728_CR47","doi-asserted-by":"crossref","first-page":"4025","DOI":"10.1007\/s12206-020-2213-x","volume":"34","author":"UE Akpudo","year":"2020","unstructured":"Akpudo UE, Hur J-W (2020) A feature fusion-based prognostics approach for rolling element bearings. J Mech Sci Technol 34:4025\u20134035","journal-title":"J Mech Sci Technol"},{"key":"5728_CR48","doi-asserted-by":"crossref","first-page":"347","DOI":"10.1016\/j.neunet.2022.05.005","volume":"152","author":"P Li","year":"2022","unstructured":"Li P, Zhang W, Lu C, Zhang R, Li X (2022) Robust kernel principal component analysis with optimal mean. Neural Netw 152:347\u2013352","journal-title":"Neural Netw"},{"issue":"6","key":"5728_CR49","doi-asserted-by":"crossref","first-page":"2347","DOI":"10.1007\/s12206-021-0507-2","volume":"35","author":"Y He","year":"2021","unstructured":"He Y, Ye L, Zhu X, Wang Z (2021) Feature extraction based on PSO-FC optimizing KPCA and wear fault identification of planetary gear. J Mech Sci Technol 35(6):2347\u20132357","journal-title":"J Mech Sci Technol"},{"issue":"22","key":"5728_CR50","doi-asserted-by":"crossref","first-page":"3678","DOI":"10.3390\/electronics11223678","volume":"11","author":"W Wang","year":"2022","unstructured":"Wang W, Tian J (2022) An improved nonlinear tuna swarm optimization algorithm based on circle chaos map and levy flight operator. Electronics 11(22):3678","journal-title":"Electronics"},{"key":"5728_CR51","doi-asserted-by":"crossref","unstructured":"Wang Y, Liu Q, Sun J, Wang L, Song X, Zhao X et al (2022) Multistrategy improved sparrow search algorithm optimized deep neural network for esophageal cancer. Comput Intell Neurosci 2022:1036913","DOI":"10.1155\/2022\/1036913"},{"key":"5728_CR52","first-page":"2151","volume":"17","author":"Y Xiao","year":"2021","unstructured":"Xiao Y, Sun X, Zhang Y, Guo Y, Wang Y, Li J (2021) An improved slime mould algorithm based on tent chaotic mapping and nonlinear inertia weight. Int J Innov Comput Inf Control 17:2151\u20132176","journal-title":"Int J Innov Comput Inf Control"},{"issue":"2","key":"5728_CR53","doi-asserted-by":"crossref","first-page":"773","DOI":"10.1090\/proc\/15244","volume":"149","author":"D Carrasco-Olivera","year":"2021","unstructured":"Carrasco-Olivera D, Morales C, Villavicencio H (2021) Stability and expansivity of tent map. Proc Am Math Soc 149(2):773\u2013786","journal-title":"Proc Am Math Soc"},{"issue":"3","key":"5728_CR54","doi-asserted-by":"crossref","first-page":"558","DOI":"10.1109\/TBCAS.2017.2665659","volume":"11","author":"H Peng","year":"2017","unstructured":"Peng H, Tian Y, Kurths J, Li L, Yang Y, Wang D (2017) D Secure and energy-efficient data transmission system based on chaotic compressive sensing in body-to-body networks. IEEE Trans Biomed Circuits Syst 11(3):558\u2013573","journal-title":"IEEE Trans Biomed Circuits Syst"},{"key":"5728_CR55","doi-asserted-by":"crossref","first-page":"333","DOI":"10.1016\/j.asoc.2014.06.034","volume":"23","author":"H Hakl\u0131","year":"2014","unstructured":"Hakl\u0131 H, U\u011fuz H (2014) A novel particle swarm optimization algorithm with levy flight. Appl Soft Comput 23:333\u2013345","journal-title":"Appl Soft Comput"},{"key":"5728_CR56","first-page":"1","volume":"2021","author":"L Xie","year":"2021","unstructured":"Xie L, Han T, Zhou H, Zhang Z-R, Han B, Tang A (2021) Tuna swarm optimization: a novel swarm-based metaheuristic algorithm for global optimization. Comput Intell Neurosci 2021:1\u201322","journal-title":"Comput Intell Neurosci"},{"issue":"1","key":"5728_CR57","doi-asserted-by":"crossref","first-page":"22","DOI":"10.1080\/21642583.2019.1708830","volume":"8","author":"J Xue","year":"2020","unstructured":"Xue J, Shen B (2020) A novel swarm intelligence optimization approach: sparrow search algorithm. Syst Sci Control Eng 8(1):22\u201334","journal-title":"Syst Sci Control Eng"},{"key":"5728_CR58","doi-asserted-by":"crossref","first-page":"162059","DOI":"10.1109\/ACCESS.2021.3133286","volume":"9","author":"M Dehghani","year":"2021","unstructured":"Dehghani M, Hub\u00e1lovsk\u1ef3 \u0160, Trojovsk\u1ef3 P (2021) Northern goshawk optimization: a new swarm-based algorithm for solving optimization problems. IEEE Access 9:162059\u2013162080","journal-title":"IEEE Access"},{"key":"5728_CR59","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili S, Mirjalili SM (2014) Lewis A Grey wolf optimizer. Adv Eng Softw 69:46\u201361","journal-title":"Adv Eng Softw"},{"key":"5728_CR60","doi-asserted-by":"crossref","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari AA, Mirjalili S, Faris H, Aljarah I, Mafarja M, Chen H (2019) Harris hawks optimization: algorithm and applications. Future Gener Comput Syst 97:849\u2013872","journal-title":"Future Gener Comput Syst"},{"issue":"12","key":"5728_CR61","doi-asserted-by":"crossref","first-page":"4580","DOI":"10.1002\/ese3.1291","volume":"10","author":"A Al-Shaikhi","year":"2022","unstructured":"Al-Shaikhi A, Nuha H, Mohandes M, Rehman S, Adrian M (2022) Vertical wind speed extrapolation model using long short-term memory and particle swarm optimization. Energy Sci Eng 10(12):4580\u20134594","journal-title":"Energy Sci Eng"},{"issue":"23","key":"5728_CR62","doi-asserted-by":"crossref","first-page":"33151","DOI":"10.1007\/s11042-022-13093-7","volume":"81","author":"E Ehsaeyan","year":"2022","unstructured":"Ehsaeyan E, Zolghadrasli A (2022) Foa: fireworks optimization algorithm. Multimed Tools Appl 81(23):33151\u201333170","journal-title":"Multimed Tools Appl"},{"key":"5728_CR63","doi-asserted-by":"crossref","unstructured":"Kubota N, Shimojima K, Fukuda T (1996) The role of virus infection in virus-evolutionary genetic algorithm. In: Proceedings of IEEE International Conference on Evolutionary Computation, pp 182\u2013187","DOI":"10.1109\/ICEC.1996.542357"},{"issue":"1","key":"5728_CR64","doi-asserted-by":"crossref","first-page":"95","DOI":"10.3390\/machines11010095","volume":"11","author":"NA Fountas","year":"2023","unstructured":"Fountas NA, Kechagias JD, Vaxevanidis NM (2023) Optimization of selective laser sintering\/melting operations by using a virus-evolutionary genetic algorithm. Machines 11(1):95","journal-title":"Machines"},{"key":"5728_CR65","doi-asserted-by":"crossref","first-page":"211","DOI":"10.1007\/978-3-030-28954-6_11","volume-title":"Explainable AI: interpreting, explaining and visualizing deep learning","author":"L Arras","year":"2019","unstructured":"Arras L, Arjona-Medina J, Widrich M, Montavon G, Gillhofer M, M\u00fcller K-R, Hochreiter S, Samek W (2019) Explaining and interpreting LSTMs. In: Samek W, Montavon G, Vedaldi A, Hansen LK, M\u00fcller KR (eds) Explainable AI: interpreting, explaining and visualizing deep learning. Springer, Berlin, pp 211\u2013238"},{"issue":"4","key":"5728_CR66","doi-asserted-by":"crossref","first-page":"4412","DOI":"10.1007\/s11227-022-04827-3","volume":"79","author":"J Huang","year":"2023","unstructured":"Huang J, Yang S, Li J, Oh J (2023) Prediction model of sparse autoencoder-based bidirectional LSTM for wastewater flow rate. J Supercomput 79(4):4412\u20134435","journal-title":"J Supercomput"},{"key":"5728_CR67","volume":"251","author":"J Li","year":"2022","unstructured":"Li J, Song Z, Wang X, Wang Y, Jia Y (2022) A novel offshore wind farm typhoon wind speed prediction model based on PSO-Bi-LSTM improved by VMD. Energy 251:123848","journal-title":"Energy"},{"key":"5728_CR68","volume":"29","author":"B Tian","year":"2021","unstructured":"Tian B, Wang G, Xu Z, Zhang Y, Zhao X (2021) Communication delay compensation for string stability of CACC system using LSTM prediction. Veh Commun 29:100333","journal-title":"Veh Commun"}],"container-title":["The Journal of Supercomputing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05728-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s11227-023-05728-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s11227-023-05728-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,25]],"date-time":"2024-03-25T11:37:33Z","timestamp":1711366653000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s11227-023-05728-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,8]]},"references-count":68,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2024,4]]}},"alternative-id":["5728"],"URL":"https:\/\/doi.org\/10.1007\/s11227-023-05728-9","relation":{},"ISSN":["0920-8542","1573-0484"],"issn-type":[{"value":"0920-8542","type":"print"},{"value":"1573-0484","type":"electronic"}],"subject":[],"published":{"date-parts":[[2023,11,8]]},"assertion":[{"value":"14 October 2023","order":1,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 November 2023","order":2,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"No potential conflict of interest was reported by the authors.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The author warrants that our contribution is original and that we have full power to make this consent.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}]}}