{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,7,24]],"date-time":"2026-07-24T17:16:24Z","timestamp":1784913384993,"version":"3.55.0"},"reference-count":50,"publisher":"Springer Science and Business Media LLC","issue":"4","license":[{"start":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T00:00:00Z","timestamp":1740441600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T00:00:00Z","timestamp":1740441600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"the Key Project of Ningxia Natural Science Foundation","award":["2022AAC02043"],"award-info":[{"award-number":["2022AAC02043"]}]},{"name":"the Construction Project of First-class Subjects in Ningxia Higher Education","award":["NXYLXK2017B09"],"award-info":[{"award-number":["NXYLXK2017B09"]}]},{"name":"the Major Proprietary Funded Project of North Minzu University","award":["ZDZX201901"],"award-info":[{"award-number":["ZDZX201901"]}]},{"name":"the Basic Discipline Research Projects supported by Nanjing Securities","award":["NJZQJCXK20220"],"award-info":[{"award-number":["NJZQJCXK20220"]}]},{"DOI":"10.13039\/501100001809","name":"the National Natural Science Foundation of China","doi-asserted-by":"crossref","award":["61561001"],"award-info":[{"award-number":["61561001"]}],"id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"crossref"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2025,8]]},"DOI":"10.1007\/s10586-024-04856-y","type":"journal-article","created":{"date-parts":[[2025,2,25]],"date-time":"2025-02-25T01:24:09Z","timestamp":1740446649000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["An adaptive hybrid differential Grey Wolf Optimization algorithm for WSN coverage"],"prefix":"10.1007","volume":"28","author":[{"given":"Yuan","family":"Yuting","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Gao","family":"Yuelin","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,2,25]]},"reference":[{"key":"4856_CR1","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2023.103308","volume":"152","author":"Z Wang","year":"2024","unstructured":"Wang, Z., Huang, L., Yang, S., Luo, X., He, D., Chan, S.: Multi-strategy enhanced grey wolf algorithm for obstacle-aware WSNs coverage optimization. Ad Hoc Netw. 152, 103308 (2024)","journal-title":"Ad Hoc Netw."},{"issue":"1","key":"4856_CR2","doi-asserted-by":"publisher","first-page":"169","DOI":"10.1109\/JSEN.2016.2624739","volume":"17","author":"E Aguirre","year":"2016","unstructured":"Aguirre, E., Lopez-Iturri, P., Azpilicueta, L., Redondo, A., Astrain, J.J., Villadangos, J., Bahillo, A., Perallos, A., Falcone, F.: Design and implementation of context aware applications with wireless sensor network support in urban train transportation environments. IEEE Sens. J. 17(1), 169\u2013178 (2016)","journal-title":"IEEE Sens. J."},{"issue":"3","key":"4856_CR3","doi-asserted-by":"publisher","first-page":"575","DOI":"10.3390\/s19030575","volume":"19","author":"Y Gao","year":"2019","unstructured":"Gao, Y., Wang, J., Wu, W., Sangaiah, A.K., Lim, S.-J.: A hybrid method for mobile agent moving trajectory scheduling using ACO and PSO in WSNs. Sensors 19(3), 575 (2019)","journal-title":"Sensors"},{"issue":"6","key":"4856_CR4","first-page":"2644","volume":"12","author":"X Zhao","year":"2018","unstructured":"Zhao, X., Zhu, H., Aleksic, S., Gao, Q.: Energy-efficient routing protocol for wireless sensor networks based on improved grey wolf optimizer. KSII Trans. Internet Inf. Syst. 12(6), 2644\u20132657 (2018)","journal-title":"KSII Trans. Internet Inf. Syst."},{"key":"4856_CR5","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1016\/j.future.2016.12.023","volume":"78","author":"T Adame","year":"2018","unstructured":"Adame, T., Bel, A., Carreras, A., Meli\u00e0-Segu\u00ed, J., Oliver, M., Pous, R.: Cuidats: an RFID-WSN hybrid monitoring system for smart health care environments. Future Gener. Comput. Syst. 78, 602\u2013615 (2018)","journal-title":"Future Gener. Comput. Syst."},{"key":"4856_CR6","doi-asserted-by":"publisher","first-page":"275","DOI":"10.1016\/j.compag.2018.01.004","volume":"145","author":"JG Caicedo-Ortiz","year":"2018","unstructured":"Caicedo-Ortiz, J.G., De-la-Hoz-Franco, E., Ortega, R.M., Pi\u00f1eres-Espitia, G., Combita-Ni\u00f1o, H., Est\u00e9vez, F., Cama-Pinto, A.: Monitoring system for agronomic variables based in WSN technology on cassava crops. Comput. Electron. Agric. 145, 275\u2013281 (2018)","journal-title":"Comput. Electron. Agric."},{"issue":"5","key":"4856_CR7","doi-asserted-by":"publisher","first-page":"150","DOI":"10.23919\/JCC.2022.05.003","volume":"19","author":"Z Zhou","year":"2022","unstructured":"Zhou, Z., Li, H., Yang, Y., Zhang, H., Fan, Z.: Real-time monitoring system for rotor temperature of a large turbogenerator based on smartmesh ip wireless network communication technology. China Commun. 19(5), 150\u2013163 (2022)","journal-title":"China Commun."},{"key":"4856_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.pmcj.2021.101504","volume":"79","author":"RK Yadav","year":"2022","unstructured":"Yadav, R.K., Mahapatra, R.P.: Hybrid metaheuristic algorithm for optimal cluster head selection in wireless sensor network. Pervasive Mob. Comput. 79, 101504 (2022)","journal-title":"Pervasive Mob. Comput."},{"issue":"22","key":"4856_CR9","doi-asserted-by":"publisher","first-page":"15557","DOI":"10.1007\/s00521-021-06178-1","volume":"33","author":"S Ebrahimi Mood","year":"2021","unstructured":"Ebrahimi Mood, S., Ding, M., Lin, Z., Javidi, M.M.: Performance optimization of UAV-based IoT communications using a novel constrained gravitational search algorithm. Neural Comput. Appl. 33(22), 15557\u201315568 (2021)","journal-title":"Neural Comput. Appl."},{"issue":"4","key":"4856_CR10","doi-asserted-by":"publisher","first-page":"575","DOI":"10.1007\/s12530-019-09264-x","volume":"11","author":"S Ebrahimi Mood","year":"2020","unstructured":"Ebrahimi Mood, S., Javidi, M.M.: Energy-efficient clustering method for wireless sensor networks using modified gravitational search algorithm. Evol. Syst. 11(4), 575\u2013587 (2020)","journal-title":"Evol. Syst."},{"key":"4856_CR11","doi-asserted-by":"publisher","first-page":"113141","DOI":"10.1109\/ACCESS.2019.2933150","volume":"7","author":"X Wang","year":"2019","unstructured":"Wang, X., Gu, H., Liu, Y., Zhang, H.: A two-stage RPSO-ACS based protocol: a new method for sensor network clustering and routing in mobile computing. IEEE Access 7, 113141\u2013113150 (2019)","journal-title":"IEEE Access"},{"issue":"19","key":"4856_CR12","doi-asserted-by":"publisher","first-page":"4320","DOI":"10.3390\/s19194320","volume":"19","author":"D Wang","year":"2019","unstructured":"Wang, D., Wang, H., Ban, X., Qian, X., Ni, J.: An adaptive, discrete space oriented wolf pack optimization algorithm for a movable wireless sensor network. Sensors 19(19), 4320 (2019)","journal-title":"Sensors"},{"issue":"1","key":"4856_CR13","doi-asserted-by":"publisher","first-page":"19377","DOI":"10.1038\/s41598-023-45039-w","volume":"13","author":"W Lai","year":"2023","unstructured":"Lai, W., Kuang, M., Wang, X., Ghafariasl, P., Sabzalian, M.H., Lee, S.: Skin cancer diagnosis (SCD) using artificial neural network (ANN) and improved gray wolf optimization (IGWO). Sci. Rep. 13(1), 19377 (2023)","journal-title":"Sci. Rep."},{"key":"4856_CR14","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110791","volume":"147","author":"SM Ebrahimi","year":"2023","unstructured":"Ebrahimi, S.M., Hasanzadeh, S., Khatibi, S.: Parameter identification of fuel cell using repairable grey wolf optimization algorithm. Appl. Soft Comput. 147, 110791 (2023)","journal-title":"Appl. Soft Comput."},{"issue":"2","key":"4856_CR15","doi-asserted-by":"publisher","first-page":"72","DOI":"10.1504\/IJAHUC.2023.131359","volume":"43","author":"SF Taleb","year":"2023","unstructured":"Taleb, S.F., Benalia, N.E.-H., Sadoun, R.: Fitness approximation with rf algorithm dedicated to WSN node deployment for a soil monitoring application. Int. J. Ad Hoc Ubiquitous Comput. 43(2), 72\u201386 (2023)","journal-title":"Int. J. Ad Hoc Ubiquitous Comput."},{"issue":"3","key":"4856_CR16","doi-asserted-by":"publisher","first-page":"960","DOI":"10.3390\/app14030960","volume":"14","author":"AM Kurian","year":"2024","unstructured":"Kurian, A.M., Onuorah, M.J., Ammari, H.M.: Optimizing coverage in wireless sensor networks: A binary ant colony algorithm with hill climbing. Appl. Sci. 14(3), 960 (2024)","journal-title":"Appl. Sci."},{"key":"4856_CR17","doi-asserted-by":"crossref","unstructured":"Wang, J., Zhu, Z., Zhang, F., Liu, Y.: An improved salp swarm algorithm for solving node coverage optimization problem in WSN. Peer-to-Peer Netw. Appl. 1\u201312 (2024)","DOI":"10.20944\/preprints202304.1025.v1"},{"issue":"3","key":"4856_CR18","doi-asserted-by":"publisher","first-page":"417","DOI":"10.1007\/s11235-021-00866-y","volume":"79","author":"M Toloueiashtian","year":"2022","unstructured":"Toloueiashtian, M., Golsorkhtabaramiri, M., Rad, S.Y.B.: An improved whale optimization algorithm solving the point coverage problem in wireless sensor networks. Telecommun. Syst. 79(3), 417\u2013436 (2022)","journal-title":"Telecommun. Syst."},{"issue":"3","key":"4856_CR19","doi-asserted-by":"publisher","first-page":"2101","DOI":"10.1007\/s11277-022-09647-5","volume":"125","author":"MA Angel","year":"2022","unstructured":"Angel, M.A., Jaya, T.: An enhanced emperor penguin optimization algorithm for secure energy efficient load balancing in wireless sensor networks. Wirel. Pers. Commun. 125(3), 2101\u20132127 (2022)","journal-title":"Wirel. Pers. Commun."},{"key":"4856_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.compeleceng.2021.107359","volume":"94","author":"R Deepa","year":"2021","unstructured":"Deepa, R., Venkataraman, R.: Enhancing whale optimization algorithm with l\u00e9vy flight for coverage optimization in wireless sensor networks. Comput. Electr. Eng. 94, 107359 (2021)","journal-title":"Comput. Electr. Eng."},{"key":"4856_CR21","doi-asserted-by":"publisher","unstructured":"Shao, X., Wang, B., Guo, D., Wang, G., Zhang, T., Yang, T.: Research on coverage of wireless sensor networks based on improved sparrow search algorithm. In: 2022 8th International Conference on Control, Automation and Robotics (ICCAR), pp. 323\u2013328 (2022). https:\/\/doi.org\/10.1109\/ICCAR55106.2022.9782633","DOI":"10.1109\/ICCAR55106.2022.9782633"},{"issue":"1","key":"4856_CR22","doi-asserted-by":"publisher","first-page":"22","DOI":"10.1080\/21642583.2019.1708830","volume":"8","author":"J Xue","year":"2020","unstructured":"Xue, J., Shen, B.: A novel swarm intelligence optimization approach: sparrow search algorithm. Syst. Sci. Control Eng. 8(1), 22\u201334 (2020)","journal-title":"Syst. Sci. Control Eng."},{"issue":"9","key":"4856_CR23","doi-asserted-by":"publisher","first-page":"3383","DOI":"10.3390\/s22093383","volume":"22","author":"Y Huang","year":"2022","unstructured":"Huang, Y., Zhang, J., Wei, W., Qin, T., Fan, Y., Luo, X., Yang, J.: Research on coverage optimization in a WSN based on an improved coot bird algorithm. Sensors 22(9), 3383 (2022)","journal-title":"Sensors"},{"key":"4856_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.adhoc.2023.103284","volume":"150","author":"J Wang","year":"2023","unstructured":"Wang, J., Liu, Y., Rao, S., Zhou, X., Hu, J.: A novel self-adaptive multi-strategy artificial bee colony algorithm for coverage optimization in wireless sensor networks. Ad Hoc Netw. 150, 103284 (2023)","journal-title":"Ad Hoc Netw."},{"issue":"12","key":"4856_CR25","doi-asserted-by":"publisher","first-page":"6607","DOI":"10.1177\/09544062211072389","volume":"236","author":"X Gu","year":"2022","unstructured":"Gu, X., Wang, G., Li, N., Chen, C., Zhang, Q.: Application of response surface optimization technology and fluid-structure interaction in the engineering design of torsional flow heat exchangers. Proc. Inst. Mech. Eng. C 236(12), 6607\u20136620 (2022)","journal-title":"Proc. Inst. Mech. Eng. C"},{"issue":"5","key":"4856_CR26","doi-asserted-by":"publisher","first-page":"190","DOI":"10.3390\/jrfm15050190","volume":"15","author":"RR Kumar","year":"2022","unstructured":"Kumar, R.R., Stauvermann, P.J., Samitas, A.: An application of portfolio mean-variance and semi-variance optimization techniques: a case of Fiji. J. Risk Financ. Manag. 15(5), 190 (2022)","journal-title":"J. Risk Financ. Manag."},{"key":"4856_CR27","doi-asserted-by":"crossref","unstructured":"Chatterjee, S., Shaw, V., Das, R.: Multi-stage intrusion detection system aided by grey wolf optimization algorithm. Clust. Comput. 1\u201318 (2023)","DOI":"10.21203\/rs.3.rs-2680915\/v1"},{"key":"4856_CR28","doi-asserted-by":"publisher","DOI":"10.1016\/j.est.2020.102006","volume":"32","author":"T Sriyakul","year":"2020","unstructured":"Sriyakul, T., Jermsittiparsert, K.: Optimal economic management of an electric vehicles aggregator by using a stochastic p-robust optimization technique. J. Energy Storage 32, 102006 (2020)","journal-title":"J. Energy Storage"},{"key":"4856_CR29","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.: Grey wolf optimizer. Adv. Eng. Softw. 69, 46\u201361 (2014)","journal-title":"Adv. Eng. Softw."},{"key":"4856_CR30","doi-asserted-by":"publisher","first-page":"252","DOI":"10.1016\/j.ijepes.2015.07.031","volume":"74","author":"N Jayakumar","year":"2016","unstructured":"Jayakumar, N., Subramanian, S., Ganesan, S., Elanchezhian, E.: Grey wolf optimization for combined heat and power dispatch with cogeneration systems. Int. J. Electr. Power Energy Syst. 74, 252\u2013264 (2016)","journal-title":"Int. J. Electr. Power Energy Syst."},{"key":"4856_CR31","unstructured":"Seth, J.K., Chandra, S.: Intrusion detection based on key feature selection using binary GWO. In: 2016 3rd International Conference on Computing for Sustainable Global Development (INDIACom), pp. 3735\u20133740 (2016). IEEE"},{"issue":"10","key":"4856_CR32","doi-asserted-by":"publisher","first-page":"3810","DOI":"10.3390\/s22103810","volume":"22","author":"Y Hou","year":"2022","unstructured":"Hou, Y., Gao, H., Wang, Z., Du, C.: Improved grey wolf optimization algorithm and application. Sensors 22(10), 3810 (2022)","journal-title":"Sensors"},{"issue":"12","key":"4856_CR33","doi-asserted-by":"publisher","first-page":"2735","DOI":"10.3390\/s19122735","volume":"19","author":"S Wang","year":"2019","unstructured":"Wang, S., Yang, X., Wang, X., Qian, Z.: A virtual force algorithm-l\u00e9vy-embedded grey wolf optimization algorithm for wireless sensor network coverage optimization. Sensors 19(12), 2735 (2019)","journal-title":"Sensors"},{"issue":"1","key":"4856_CR34","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1145\/972627.972631","volume":"3","author":"Y Zou","year":"2004","unstructured":"Zou, Y., Chakrabarty, K.: Sensor deployment and target localization in distributed sensor networks. ACM Trans. Embed. Comput. Syst. 3(1), 61\u201391 (2004)","journal-title":"ACM Trans. Embed. Comput. Syst."},{"key":"4856_CR35","doi-asserted-by":"publisher","first-page":"57229","DOI":"10.1109\/ACCESS.2020.2982441","volume":"8","author":"Z Wang","year":"2020","unstructured":"Wang, Z., Xie, H.: Wireless sensor network deployment of 3d surface based on enhanced grey wolf optimizer. IEEE Access 8, 57229\u201357251 (2020)","journal-title":"IEEE Access"},{"key":"4856_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2023.121917","volume":"238","author":"X Yu","year":"2024","unstructured":"Yu, X., Duan, Y., Cai, Z., Luo, W.: An adaptive learning grey wolf optimizer for coverage optimization in WSNs. Expert Syst. Appl. 238, 121917 (2024)","journal-title":"Expert Syst. Appl."},{"key":"4856_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106602","volume":"96","author":"Z Miao","year":"2020","unstructured":"Miao, Z., Yuan, X., Zhou, F., Qiu, X., Song, Y., Chen, K.: Grey wolf optimizer with an enhanced hierarchy and its application to the wireless sensor network coverage optimization problem. Appl. Soft Comput. 96, 106602 (2020)","journal-title":"Appl. Soft Comput."},{"key":"4856_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2019.105658","volume":"83","author":"FB Ozsoydan","year":"2019","unstructured":"Ozsoydan, F.B.: Effects of dominant wolves in grey wolf optimization algorithm. Appl. Soft Comput. 83, 105658 (2019)","journal-title":"Appl. Soft Comput."},{"key":"4856_CR39","doi-asserted-by":"publisher","first-page":"63","DOI":"10.1016\/j.engappai.2017.10.024","volume":"68","author":"W Long","year":"2018","unstructured":"Long, W., Jiao, J., Liang, X., Tang, M.: An exploration-enhanced grey wolf optimizer to solve high-dimensional numerical optimization. Eng. Appl. Artif. Intell. 68, 63\u201380 (2018)","journal-title":"Eng. Appl. Artif. Intell."},{"issue":"1","key":"4856_CR40","first-page":"7950348","volume":"2016","author":"N Mittal","year":"2016","unstructured":"Mittal, N., Singh, U., Sohi, B.S.: Modified grey wolf optimizer for global engineering optimization. Appl. Comput. Intell. Soft Comput. 2016(1), 7950348 (2016)","journal-title":"Appl. Comput. Intell. Soft Comput."},{"key":"4856_CR41","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107139","volume":"226","author":"X Yu","year":"2021","unstructured":"Yu, X., Xu, W., Li, C.: Opposition-based learning grey wolf optimizer for global optimization. Knowl.-Based Syst. 226, 107139 (2021)","journal-title":"Knowl.-Based Syst."},{"key":"4856_CR42","doi-asserted-by":"crossref","unstructured":"Ravi, T., Kumar, K.S.: Detection and classification of power quality disturbances using stock well transform and improved grey wolf optimization-based kernel extreme learning machine. IEEE Access (2023)","DOI":"10.1109\/ACCESS.2023.3286308"},{"key":"4856_CR43","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2023.110031","volume":"135","author":"H Pan","year":"2023","unstructured":"Pan, H., Chen, S., Xiong, H.: A high-dimensional feature selection method based on modified gray wolf optimization. Appl. Soft Comput. 135, 110031 (2023)","journal-title":"Appl. Soft Comput."},{"key":"4856_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113389","volume":"151","author":"S Dhargupta","year":"2020","unstructured":"Dhargupta, S., Ghosh, M., Mirjalili, S., Sarkar, R.: Selective opposition based grey wolf optimization. Expert Syst. Appl. 151, 113389 (2020)","journal-title":"Expert Syst. Appl."},{"key":"4856_CR45","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114676","volume":"173","author":"X Meng","year":"2021","unstructured":"Meng, X., Jiang, J., Wang, H.: AGWO: advanced GWO in multi-layer perception optimization. Expert Syst. Appl. 173, 114676 (2021)","journal-title":"Expert Syst. Appl."},{"issue":"2","key":"4856_CR46","doi-asserted-by":"publisher","first-page":"1749","DOI":"10.1007\/s00521-022-07836-8","volume":"35","author":"M Mafarja","year":"2023","unstructured":"Mafarja, M., Thaher, T., Too, J., Chantar, H., Turabieh, H., Houssein, E.H., Emam, M.M.: An efficient high-dimensional feature selection approach driven by enhanced multi-strategy grey wolf optimizer for biological data classification. Neural Comput. Appl. 35(2), 1749\u20131775 (2023)","journal-title":"Neural Comput. Appl."},{"key":"4856_CR47","doi-asserted-by":"publisher","first-page":"849","DOI":"10.1016\/j.future.2019.02.028","volume":"97","author":"AA Heidari","year":"2019","unstructured":"Heidari, A.A., Mirjalili, S., Faris, H., Aljarah, I., Mafarja, M., Chen, H.: Harris hawks optimization: algorithm and applications. Future Gener. Comput. Syst. 97, 849\u2013872 (2019)","journal-title":"Future Gener. Comput. Syst."},{"key":"4856_CR48","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2022.109215","volume":"251","author":"C Zhong","year":"2022","unstructured":"Zhong, C., Li, G., Meng, Z.: Beluga whale optimization: a novel nature-inspired metaheuristic algorithm. Knowl.-Based Syst. 251, 109215 (2022)","journal-title":"Knowl.-Based Syst."},{"issue":"4","key":"4856_CR49","doi-asserted-by":"publisher","first-page":"2627","DOI":"10.1007\/s00366-022-01604-x","volume":"39","author":"A Seyyedabbasi","year":"2023","unstructured":"Seyyedabbasi, A., Kiani, F.: Sand cat swarm optimization: a nature-inspired algorithm to solve global optimization problems. Eng. Comput. 39(4), 2627\u20132651 (2023)","journal-title":"Eng. Comput."},{"key":"4856_CR50","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116470","volume":"194","author":"A Saxena","year":"2022","unstructured":"Saxena, A.: An efficient harmonic estimator design based on augmented crow search algorithm in noisy environment. Expert Syst. Appl. 194, 116470 (2022)","journal-title":"Expert Syst. Appl."}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-04856-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-024-04856-y\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-024-04856-y.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,9,6]],"date-time":"2025-09-06T07:31:28Z","timestamp":1757143888000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-024-04856-y"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,2,25]]},"references-count":50,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2025,8]]}},"alternative-id":["4856"],"URL":"https:\/\/doi.org\/10.1007\/s10586-024-04856-y","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,2,25]]},"assertion":[{"value":"24 June 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"22 October 2024","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 October 2024","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 February 2025","order":4,"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 no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}],"article-number":"229"}}