{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T16:49:47Z","timestamp":1766508587947,"version":"3.48.0"},"reference-count":28,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T00:00:00Z","timestamp":1766448000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"},{"start":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T00:00:00Z","timestamp":1766448000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0"}],"funder":[{"name":"National Natural Science Foundation of China Regional Project","award":["61863011"],"award-info":[{"award-number":["61863011"]}]},{"name":"National Natural Science Foundation of China Regional Project","award":["61863011"],"award-info":[{"award-number":["61863011"]}]},{"name":"Meizhou Applied Science and Technology Special Fund Project","award":["2019B0201005"],"award-info":[{"award-number":["2019B0201005"]}]},{"name":"Meizhou Applied Science and Technology Special Fund Project","award":["2019B0201005"],"award-info":[{"award-number":["2019B0201005"]}]},{"name":"Jiaying University Talent Research Launch Project","award":["2022RC84"],"award-info":[{"award-number":["2022RC84"]}]},{"name":"Jiaying University Talent Research Launch Project","award":["2022RC84"],"award-info":[{"award-number":["2022RC84"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Discov Computing"],"DOI":"10.1007\/s10791-025-09878-7","type":"journal-article","created":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T15:24:09Z","timestamp":1766503449000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Hybrid adaptive Wolf-Particle swarm optimization algorithm and its application in CNN neural network hyperparameters optimization"],"prefix":"10.1007","volume":"28","author":[{"given":"Keyin","family":"Chen","sequence":"first","affiliation":[]},{"given":"Jinzhen","family":"Xie","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2025,12,23]]},"reference":[{"issue":"1","key":"9878_CR1","first-page":"1","volume":"26","author":"MLSNS Lakshmi","year":"2025","unstructured":"Lakshmi MLSNS, Siva Chakra Avinash B, Suneetha R, Rajalakshmi P, Meha Soman S. Active antenna selection for reconfigurable intelligent surfaces using Rotation-Invariant coordinate convolutional neural network and multi-dimensional attention spiking neural network for 5G\/6G communication. Sens Imaging. 2025;26(1):1\u201325.","journal-title":"Sens Imaging"},{"issue":"2","key":"9878_CR2","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1109\/LCOMM.2024.3519340","volume":"29","author":"J Zhang","year":"2025","unstructured":"Zhang J, Xu Z, Zhang S, Hu K, Shen Y. A deep learning-based indoor positioning approach using channel and spatial attention. IEEE Commun Lett. 2025;29(2):373\u20137.","journal-title":"IEEE Commun Lett"},{"issue":"4","key":"9878_CR3","doi-asserted-by":"crossref","first-page":"793","DOI":"10.1016\/j.jer.2024.01.018","volume":"12","author":"F Antonius","year":"2024","unstructured":"Antonius F. Efficient resource allocation through CNN-game theory based network slicing recognition for next-generation networks. J Eng Res. 2024;12(4):793\u2013805.","journal-title":"J Eng Res"},{"issue":"5","key":"9878_CR4","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1049\/cmu2.12336","volume":"16","author":"K Yadav","year":"2022","unstructured":"Yadav K, Jain A, Alharbi Y, Alferaidi A, Alkwai LM, Ahmed NMOS, et al. A secure data transmission and efficient data balancing approach for 5G-based IoT data using UUDIS-ECC and LSRHS-CNN algorithms. IET Commun. 2022;16(5):571\u201383.","journal-title":"IET Commun"},{"issue":"1","key":"9878_CR5","doi-asserted-by":"crossref","first-page":"4567","DOI":"10.1038\/s41598-025-88869-6","volume":"15","author":"Y Tong","year":"2025","unstructured":"Tong Y, Lin L, Tian L, Wang Z, Wu W, Wu J. Coverage optimization and node minimization in wsns: an enhanced hybrid PSO approach with spatial position encoding. Sci Rep. 2025;15(1):4567.","journal-title":"Sci Rep"},{"issue":"13","key":"9878_CR6","doi-asserted-by":"crossref","first-page":"1548","DOI":"10.1080\/15325008.2015.1041625","volume":"43","author":"AA El-Fergany","year":"2015","unstructured":"El-Fergany AA, Hasanien HM. Single and multi-objective optimal power flow using grey Wolf optimizer and differential evolution algorithms. Electr Machines Power Syst. 2015;43(13):1548\u201359.","journal-title":"Electr Machines Power Syst"},{"key":"9878_CR7","doi-asserted-by":"crossref","DOI":"10.1016\/j.simpat.2024.102915","volume":"133","author":"S Gupta","year":"2024","unstructured":"Gupta S, Singh RS. User-defined weight based multi objective task scheduling in cloud using whale optimization algorithm. Simul Model Pract Theory. 2024;133:102915.","journal-title":"Simul Model Pract Theory"},{"key":"9878_CR8","doi-asserted-by":"crossref","DOI":"10.1016\/j.jterra.2025.101067","volume":"119","author":"B Golanbari","year":"2025","unstructured":"Golanbari B, Mardani A, Valizadeh M, Farhadi N. Hybrid grey wolf optimizer-ANN for predicting wheel energy consumption in off-road vehicles and enhancing resource management. J Terramech. 2025;119:101067.","journal-title":"J Terramech"},{"issue":"9","key":"9878_CR9","doi-asserted-by":"crossref","first-page":"2707","DOI":"10.3390\/pr13092707","volume":"13","author":"ARMA Besha","year":"2025","unstructured":"Besha ARMA, Ojekemi OS, Oz T, Adegboye O. Plsco: an optimization-driven approach for enhancing predictive maintenance accuracy in intelligent manufacturing. Processes. 2025;13(9):2707.","journal-title":"Processes"},{"issue":"2","key":"9878_CR10","doi-asserted-by":"crossref","first-page":"128","DOI":"10.1007\/s10586-024-04753-4","volume":"28","author":"OR Adegboye","year":"2025","unstructured":"Adegboye OR, Feda AK. Improved exponential distribution optimizer: enhancing global numerical optimization problem solving and optimizing machine learning parameters. Cluster Comput. 2025;28(2):128.","journal-title":"Cluster Comput"},{"issue":"15","key":"9878_CR11","doi-asserted-by":"crossref","first-page":"6783","DOI":"10.3390\/su17156783","volume":"17","author":"M Almsallti","year":"2025","unstructured":"Almsallti M, Alzubi AB, Adegboye OR. Hybrid metaheuristic optimized extreme learning machine for sustainability focused CO2 emission prediction using Globalization-Driven indicators. Sustainability. 2025;17(15):6783.","journal-title":"Sustainability"},{"issue":"4","key":"9878_CR12","doi-asserted-by":"crossref","first-page":"814","DOI":"10.1080\/00207721.2023.2293687","volume":"55","author":"J Xue","year":"2024","unstructured":"Xue J, Shen B. A survey on sparrow search algorithms and their applications. Int J Syst Sci. 2024;55(4):814\u201332.","journal-title":"Int J Syst Sci"},{"key":"9878_CR13","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2024.3518581","author":"J Xue","year":"2024","unstructured":"Xue J, Zhang C, Wang M, Dong X. MOSSA: An Efficient Swarm Intelligent Algorithm to Solve Global Optimization and Carbon Fiber Drawing Process Problems. IEEE Internet Things J. 2024. https:\/\/doi.org\/10.1109\/JIOT.2024.3518581.","journal-title":"IEEE Internet Things J"},{"issue":"2","key":"9878_CR14","doi-asserted-by":"crossref","first-page":"45","DOI":"10.1007\/s12065-025-01029-7","volume":"18","author":"AK Singh","year":"2025","unstructured":"Singh AK, Kumar A. Hybrid multi-objective particle swarm optimization feature selection approach with firefly algorithm using decision tree classifier. Evol Intel. 2025;18(2):45.","journal-title":"Evol Intel"},{"key":"9878_CR15","doi-asserted-by":"crossref","unstructured":"Singh AK, Kumar A. Greedy particle swarm optimization approach using leaky ReLU function for minimum spanning tree Problem. AI-Based advanced optimization techniques for edge computing. Wiley. London. 2025:289\u2013315.","DOI":"10.1002\/9781394287062.ch11"},{"issue":"5","key":"9878_CR16","doi-asserted-by":"crossref","first-page":"832","DOI":"10.3390\/electronics14050832","volume":"14","author":"J Numbi","year":"2025","unstructured":"Numbi J, Zioui N, Tadjine M. Quantum particle swarm optimisation proportional-derivative control for trajectory tracking of a Car-like mobile robot. Electronics. 2025;14(5):832.","journal-title":"Electronics"},{"key":"9878_CR17","doi-asserted-by":"crossref","first-page":"8457","DOI":"10.1007\/s12652-020-02580-0","volume":"12","author":"G Dhiman","year":"2021","unstructured":"Dhiman G, Garg M, Nagar A, Kumar V, Dehghani M. A novel algorithm for global optimization: rat swarm optimizer. J Ambient Intell Humaniz Comput. 2021;12:8457\u201382.","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"8","key":"9878_CR18","first-page":"2456","volume":"107","author":"Q Wu","year":"2025","unstructured":"Wu Q. An enhanced Whale optimization algorithm with inertia weight and dynamic parameter adaptation for wireless sensor network deployment. Computing. 2025;107(8):2456\u201378.","journal-title":"Computing"},{"issue":"12","key":"9878_CR19","first-page":"145","volume":"57","author":"G Hu","year":"2024","unstructured":"Hu G, Guo Y, Zhao W, Houssein EH. An adaptive snow ablation-inspired particle swarm optimization with its application in geometric optimization. Artif Intell Rev. 2024;57(12):145.","journal-title":"Artif Intell Rev"},{"key":"9878_CR20","volume":"93","author":"Y Xu","year":"2025","unstructured":"Xu Y, Wang D, Zhang M, Zhang M, Yang M, Liang C. Quantum particle swarm optimization with chaotic encoding schemes for flexible job-shop scheduling problem. Swarm Evol Comput. 2025;93:101836.","journal-title":"Swarm Evol Comput"},{"issue":"2","key":"9878_CR21","first-page":"2014","volume":"635","author":"N Awad","year":"2017","unstructured":"Awad N, Ali M, Liang J, Qu B, Suganthan P. Problem definitions and evaluation criteria for the CEC 2017 special session and competition on single objective real-parameter numerical optimization. Congress on Evol Computation. 2017;635(2):2014.","journal-title":"Congress on Evol Computation"},{"issue":"5","key":"9878_CR22","first-page":"2456","volume":"71","author":"C Li","year":"2024","unstructured":"Li C, You C, Gu Y, Zhu Y. Parameter identification of the RBF-ARX model based on the hybrid Whale optimization algorithm. IEEE Trans Circuits Syst II Express Briefs. 2024;71(5):2456\u201360.","journal-title":"IEEE Trans Circuits Syst II Express Briefs"},{"issue":"4","key":"9878_CR23","first-page":"5601","volume":"45","author":"X Zhu","year":"2023","unstructured":"Zhu X, Liu S, Zhu X, You X. Enhancing sparrow search algorithm with hybrid multi-strategy and its engineering applications. J Intell Fuzzy Syst. 2023;45(4):5601\u201332.","journal-title":"J Intell Fuzzy Syst"},{"key":"9878_CR24","unstructured":"Krizhevsky A. Learning multiple layers of features from tiny images. University of Toronto. 2009."},{"issue":"11","key":"9878_CR25","doi-asserted-by":"crossref","DOI":"10.1088\/1402-4896\/acff2c","volume":"98","author":"W Deng","year":"2023","unstructured":"Deng W, He Q, Zhou X, Chen H, Zhao H. A sparrow search algorithm-optimized convolutional neural network for imbalanced data classification using synthetic minority over-sampling technique. Phys Scr. 2023;98(11):115012.","journal-title":"Phys Scr"},{"issue":"2","key":"9878_CR26","doi-asserted-by":"crossref","first-page":"255","DOI":"10.21817\/indjcse\/2023\/v14i2\/231402050","volume":"14","author":"A Abudayor","year":"2023","unstructured":"Abudayor A, Nalbantolu \u00d6U. A NOVEL HYBRID ALGORITHM BASED ON CROW SEARCH ALGORITHM AND WHALE OPTIMIZATION ALGORITHM FOR HIGH-DIMENSIONAL OPTIMIZATION AND FEATURE SELECTION. Indian J Comput Sci Eng. 2023;14(2):255\u201373.","journal-title":"Indian J Comput Sci Eng"},{"issue":"4","key":"9878_CR27","volume":"95","author":"M Wan","year":"2024","unstructured":"Wan M, Xiao Y, Zhang J. Research on fault diagnosis of rolling bearing based on improved convolutional neural network with sparrow search algorithm. Rev Sci Instrum. 2024;95(4):045115.","journal-title":"Rev Sci Instrum"},{"issue":"1","key":"9878_CR28","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1007\/s44163-025-00428-0","volume":"5","author":"AK Singh","year":"2025","unstructured":"Singh AK, Kumar A. Multi-objective: hybrid particle swarm optimization with firefly algorithm for feature selection with leaky ReLU. Discover Artif Intell. 2025;5(1):192.","journal-title":"Discover Artif Intell"}],"container-title":["Discover Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10791-025-09878-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10791-025-09878-7","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10791-025-09878-7.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,23]],"date-time":"2025-12-23T15:24:24Z","timestamp":1766503464000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10791-025-09878-7"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,12,23]]},"references-count":28,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2025,12]]}},"alternative-id":["9878"],"URL":"https:\/\/doi.org\/10.1007\/s10791-025-09878-7","relation":{},"ISSN":["2948-2992"],"issn-type":[{"value":"2948-2992","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,12,23]]},"assertion":[{"value":"18 September 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 December 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"23 December 2025","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"This study did not involve human or animal subjects; therefore, ethical approval was not required. Written informed consent was obtained from all participants prior to data collection.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval and consent to participate"}},{"value":"Participants consented to the publication of anonymized data in the informed consent documentation.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}},{"value":"The authors declare no competing interests.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}],"article-number":"319"}}