{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T13:03:57Z","timestamp":1779800637971,"version":"3.53.1"},"reference-count":76,"publisher":"Springer Science and Business Media LLC","issue":"13","license":[{"start":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T00:00:00Z","timestamp":1758240000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T00:00:00Z","timestamp":1758240000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100012166","name":"National Key R&D Program of China","doi-asserted-by":"crossref","award":["No.2023YFC2413301"],"award-info":[{"award-number":["No.2023YFC2413301"]}],"id":[{"id":"10.13039\/501100012166","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100018532","name":"Major Scientific and Technological Innovation Project of Shandong Province","doi-asserted-by":"publisher","award":["No.2023CXGC010207"],"award-info":[{"award-number":["No.2023CXGC010207"]}],"id":[{"id":"10.13039\/501100018532","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Cluster Comput"],"published-print":{"date-parts":[[2025,11]]},"DOI":"10.1007\/s10586-025-05558-9","type":"journal-article","created":{"date-parts":[[2025,9,19]],"date-time":"2025-09-19T20:07:03Z","timestamp":1758312423000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Improved Harris Hawk optimization for multilevel thresholding image segmentation"],"prefix":"10.1007","volume":"28","author":[{"given":"Xuwei","family":"Du","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Peng","family":"Yao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Qilin","family":"Wang","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xiang","family":"Liu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mingwu","family":"Hao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Dongkai","family":"Chu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shuoshuo","family":"Qu","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2025,9,19]]},"reference":[{"key":"5558_CR1","doi-asserted-by":"crossref","first-page":"109272","DOI":"10.1016\/j.compbiomed.2024.109272","volume":"183","author":"M Abdel-Salam","year":"2024","unstructured":"Abdel-Salam, M., Houssein, E.H., Emam, M.M.: An adaptive enhanced human memory algorithm for multi-level image segmentation for pathological lung cancer images. Comput. Biol. Med. 183, 109272 (2024)","journal-title":"Comput. Biol. Med."},{"issue":"1","key":"5558_CR2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-025-01065-1","volume":"12","author":"ZF Elsharkawy","year":"2025","unstructured":"Elsharkawy, Z.F., Kasban, H., Abbass, M.Y.: Efficient surface crack segmentation for industrial and civil applications based on an enhanced YOLOv8 model. J. Big Data. 12(1), 1\u201320 (2025)","journal-title":"J. Big Data"},{"key":"5558_CR3","first-page":"5015012","volume":"71","author":"LM Yang","year":"2022","unstructured":"Yang, L.M., Zhou, F.Q., W, L.: A scratch detection method based on deep learning and image segmentation. IEEE Trans. Instrum. Meas. 71, 5015012 (2022)","journal-title":"IEEE Trans. Instrum. Meas."},{"key":"5558_CR4","doi-asserted-by":"crossref","first-page":"2368","DOI":"10.1109\/TMM.2022.3146771","volume":"25","author":"DZ Peng","year":"2023","unstructured":"Peng, D.Z., Jin, L.W., Ma, W.H., Xie, C.Y., Zhang, H.S., Zhu, S.G., Li, J.: JingRecognition of handwritten Chinese text by segmentation: A Segment-Annotation-Free approach. IEEE Trans. Multimedia. 25, 2368\u20132381 (2023)","journal-title":"IEEE Trans. Multimedia"},{"issue":"11","key":"5558_CR5","first-page":"3606","volume":"24","author":"M Xiao","year":"2024","unstructured":"Xiao, M., Min, W., Yang, C., Song, Y.A.: Novel network framework on simultaneous road segmentation and vehicle detection for UAV aerial. Traffic Images Sens. 24(11), 3606 (2024)","journal-title":"Traffic Images Sens."},{"issue":"17","key":"5558_CR6","doi-asserted-by":"crossref","first-page":"4180","DOI":"10.3390\/rs15174180","volume":"15","author":"H Liang","year":"2023","unstructured":"Liang, H., Zheng, C., Liu, X., Tian, Y., Zhang, J., Cui, W.: Super-Resolution reconstruction of remote sensing data based on multiple satellite sources for forest fire smoke. Segmentation Remote Sens. 15(17), 4180 (2023)","journal-title":"Segmentation Remote Sens."},{"key":"5558_CR7","doi-asserted-by":"crossref","unstructured":"Hu, Q., Wei, Y., Li, H.W.S.: SVF-Net: spatial and visual feature enhancement network for brain structure segmentation[J].Applied Intelligence: The International Journal of Artificial Intelligence, Neural Networks, and Complex Problem-Solving Technologies, 53(4), 4180\u20134200 (2023)","DOI":"10.1007\/s10489-022-03706-x"},{"key":"5558_CR8","doi-asserted-by":"crossref","first-page":"108780","DOI":"10.1016\/j.compbiomed.2024.108780","volume":"178","author":"G Hu","year":"2024","unstructured":"Hu, G., Zheng, Y., Houssein, E.H., Wei, G.: DRPSO: A multi-strategy fusion particle swarm optimization algorithm with a replacement mechanisms for colon cancer pathology image segmentation. Comput. Biol. Med. 178, 108780 (2024)","journal-title":"Comput. Biol. Med."},{"issue":"5","key":"5558_CR9","doi-asserted-by":"crossref","first-page":"3597","DOI":"10.1007\/s00521-020-05561-8","volume":"35","author":"X Zheng","year":"2023","unstructured":"Zheng, X., Chen, T.: High Spatial resolution remote sensing image segmentation based on the multiclassification model and the binary classification model. Neural Comput. Applic. 35(5), 3597\u20133604 (2023)","journal-title":"Neural Comput. Applic"},{"issue":"5","key":"5558_CR10","first-page":"1","volume":"31","author":"A Das","year":"2024","unstructured":"Das, A., Sasmal, B., Dhal, K.G., Hussien, A.G., Naskar, P.K.: Particle swarm optimizer variants for Multi-level thresholding: Theory, performance enhancement and evaluation. Arch. Comput. Methods Eng. 31(5), 1\u201336 (2024)","journal-title":"Arch. Comput. Methods Eng."},{"issue":"2","key":"5558_CR11","doi-asserted-by":"crossref","first-page":"385","DOI":"10.1007\/s11760-017-1170-z","volume":"12","author":"S Pare","year":"2018","unstructured":"Pare, S., Bhandari, A.K., Kumar, A., Bajaj, V.: Backtracking search algorithm for color image multilevel thresholding. Signal. Image Video Process. 12(2), 385\u2013392 (2018)","journal-title":"Signal. Image Video Process."},{"key":"5558_CR12","doi-asserted-by":"crossref","first-page":"102799","DOI":"10.1016\/j.displa.2024.102799","volume":"84","author":"J Shi","year":"2024","unstructured":"Shi, J., Chen, Y., Wang, C., Heidari, A.A., Liu, L., Chen, H., Sun, L.: Multi-threshold image segmentation using new strategies enhanced Whale optimization for lupus nephritis pathological images. Displays. 84, 102799 (2024)","journal-title":"Displays"},{"issue":"18","key":"5558_CR13","doi-asserted-by":"crossref","first-page":"24097","DOI":"10.1007\/s11042-018-5697-y","volume":"77","author":"H Yu","year":"2018","unstructured":"Yu, H., He, F., Pan, Y.: A novel region-based active contour model via local patch similarity measure for image segmentation. Multimedia Tools Appl. 77(18), 24097\u201324119 (2018)","journal-title":"Multimedia Tools Appl."},{"key":"5558_CR14","doi-asserted-by":"crossref","unstructured":"Dhal, K.G., Das, A., Sasmal, B.: Eagle strategy in Nature-Inspired optimization: Theory, analysis, applications, and comparative study. Arch. Comput. Methods Eng. 31(3) (2024)","DOI":"10.1007\/s11831-023-10014-1"},{"issue":"12","key":"5558_CR15","doi-asserted-by":"crossref","first-page":"3983","DOI":"10.1007\/s00500-017-2608-5","volume":"22","author":"ZC Zhang","year":"2018","unstructured":"Zhang, Z.C.: A fast weak-supervised pulmonary nodule segmentation method based on modified self-adaptive FCM algorithm. Soft. Comput. 22(12), 3983\u20133995 (2018)","journal-title":"Soft. Comput."},{"key":"5558_CR16","doi-asserted-by":"crossref","unstructured":"Zheng, X.L., Chen, T., Liu, F., Lin, G., Shen, C.: High Spatial resolution remote sensing image segmentation based on the multiclassification model and the binary classification model. Pattern Recogn. 35(5), 3597\u20133604 (20232015)","DOI":"10.1007\/s00521-020-05561-8"},{"key":"5558_CR17","doi-asserted-by":"crossref","unstructured":"Eberhart, Shi, Y.: Particle swarm optimization: developments, applications and resources Proceedings of the 2001 congress on evolutionary computation, 1, 81\u201386, IEEE, (2001)","DOI":"10.1109\/CEC.2001.934374"},{"issue":"2","key":"5558_CR18","doi-asserted-by":"crossref","first-page":"85","DOI":"10.1016\/S0165-1684(98)00167-4","volume":"72","author":"PY Yin","year":"1999","unstructured":"Yin, P.Y.: A fast scheme for optimal thresholding using genetic algorithms. Sig. Process. 72(2), 85\u201395 (1999)","journal-title":"Sig. Process."},{"key":"5558_CR19","doi-asserted-by":"crossref","first-page":"4","DOI":"10.1109\/TEVC.2010.2059031","volume":"15","author":"S Das","year":"2011","unstructured":"Das, S., Suganthan, P.N.: Differential evolution: A survey of the State-of-the-Art. IEEE Trans. Evol. Comput. 15, 4\u201331 (2011)","journal-title":"IEEE Trans. Evol. Comput."},{"key":"5558_CR20","doi-asserted-by":"crossref","unstructured":"Liang, Y.C., Chen, H.L., Chyu, C.C.: Application of a hybrid ant colony optimization for the multilevel thresholding in image processing. International Conference on Neural Information Processing, pp. 1183\u20131192. Springer, (2006)","DOI":"10.1007\/11893257_129"},{"issue":"13","key":"5558_CR21","doi-asserted-by":"crossref","first-page":"2232","DOI":"10.1016\/j.ins.2009.03.004","volume":"179","author":"E Rashedi","year":"2009","unstructured":"Rashedi, E., Nezamabadi-Pour, H., Saryazdi, S.: Gsa, a gravitational search algorithm. Inf. Sci. 179(13), 2232\u20132248 (2009)","journal-title":"Inf. Sci."},{"key":"5558_CR22","doi-asserted-by":"crossref","first-page":"80","DOI":"10.1016\/j.advengsoft.2015.01.010","volume":"83","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili, S.: The ant Lion optimizer. Adv. Eng. Softw. 83, 80\u201398 (2015)","journal-title":"Adv. Eng. Softw."},{"key":"5558_CR23","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S., Lewis, A.: The Whale optimization algorithm. Adv. Eng. Softw. 95, 51\u201367 (2016)","journal-title":"Adv. Eng. Softw."},{"key":"5558_CR24","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.knosys.2015.07.006","volume":"89","author":"S Mirjalili","year":"2015","unstructured":"Mirjalili, S.: Moth-flame optimization algorithm, A novel nature-inspired heuristic paradigm. Knowl. Based Syst. 89, 228\u2013249 (2015)","journal-title":"Knowl. Based Syst."},{"issue":"4","key":"5558_CR25","doi-asserted-by":"crossref","first-page":"1053","DOI":"10.1007\/s00521-015-1920-1","volume":"27","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S.: Dragonfly algorithm, a new meta-heuristic optimization technique for solving single-objective, discrete, and multi-objective problems. Neural Comput. Appl. 27(4), 1053\u20131073 (2016)","journal-title":"Neural Comput. Appl."},{"key":"5558_CR26","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1016\/j.knosys.2017.12.037","volume":"145","author":"M Mafarja","year":"2018","unstructured":"Mafarja, M., Aljarah, I., Heidari, A.A., Hammouri, H., Faris, A.-Z., Ala\u2019M, S., Mirjalili: Evolutionary population dynamics and grasshopper optimization approaches for feature selection problems. Knowl. Based Syst. 145, 25\u201345 (2018)","journal-title":"Knowl. Based Syst."},{"key":"5558_CR27","doi-asserted-by":"crossref","first-page":"105884","DOI":"10.1016\/j.asoc.2019.105884","volume":"86","author":"H Chen","year":"2020","unstructured":"Chen, H., Zhang, Q., Luo, J., Xu, Y., Zhang, X.: An enhanced bacterial foraging optimization and its application for training kernel extreme learning machine. Appl. Soft Comput. 86, 105884 (2020)","journal-title":"Appl. Soft Comput."},{"key":"5558_CR28","doi-asserted-by":"crossref","first-page":"113609","DOI":"10.1016\/j.cma.2020.113609","volume":"376","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., Diabat, A., Mirjalili, S., Abd Elaziz, M., Gandomi, A.H.: The arithmetic optimization algorithm. Comput. Methods Appl. Mech. Eng. 376, 113609 (2021)","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"5558_CR29","doi-asserted-by":"crossref","first-page":"107250","DOI":"10.1016\/j.cie.2021.107250","volume":"157","author":"L Abualigah","year":"2021","unstructured":"Abualigah, L., Yousri, D., Elaziz, M., Ewees, E.G., Gandomi, A.H.: Matlab code of Aquila optimizer: A novel meta-heuristic optimization algorithm. Comput. Ind. Eng. 157, 107250 (2021)","journal-title":"Comput. Ind. Eng."},{"key":"5558_CR30","doi-asserted-by":"crossref","first-page":"16150","DOI":"10.1109\/ACCESS.2022.3147821","volume":"10","author":"O Olaide","year":"2022","unstructured":"Olaide, O., Ezugwu, E.S., Mohamed, T.I.A., Abualigah, L.: Ebola optimization search algorithm, A new Nature-Inspired metaheuristic optimization algorithm. IEEE Access. 10, 16150\u201316177 (2022)","journal-title":"IEEE Access."},{"key":"5558_CR31","doi-asserted-by":"crossref","first-page":"114570","DOI":"10.1016\/j.cma.2022.114570","volume":"391","author":"JO Agushaka","year":"2022","unstructured":"Agushaka, J.O., Ezugwu, A.E., Abualigah, L.: Dwarf mongoose optimization algorithm. Comput. Methods Appl. Mech. Eng. 391, 114570 (2022)","journal-title":"Comput. Methods Appl. Mech. Eng."},{"key":"5558_CR32","doi-asserted-by":"crossref","first-page":"116158","DOI":"10.1016\/j.eswa.2021.116158","volume":"191","author":"L Abualigah","year":"2022","unstructured":"Abualigah, L., Elaziz, M.A., Sumari, P., Geem, Z.W., Gandomi, A.H.: Reptile search algorithm (RSA), A natureinspired meta-heuristic optimizer. Expert Syst. Appl. 191, 116158 (2022)","journal-title":"Expert Syst. Appl."},{"key":"5558_CR33","doi-asserted-by":"crossref","first-page":"20017","DOI":"10.1007\/s00521-022-07530-9","volume":"34","author":"AE Ezugwu","year":"2022","unstructured":"Ezugwu, A.E., Agushaka, J.O., Abualigah, L., Mirjalili, S., Gandomi, A.H.: Prairie dog optimization algorithm. Neural Comput. Applic. 34, 20017\u201320065 (2022)","journal-title":"Neural Comput. Applic"},{"key":"5558_CR34","doi-asserted-by":"crossref","first-page":"4099","DOI":"10.1007\/s00521-022-07854-6","volume":"35","author":"JO Agushaka","year":"2023","unstructured":"Agushaka, J.O., Ezugwu, A.E., Abualigah, L.: Gazelle optimization algorithm, a novel nature-inspired metaheuristic optimizer. Neural Comput. Applic. 35, 4099\u20134131 (2023)","journal-title":"Neural Comput. Applic"},{"key":"5558_CR35","doi-asserted-by":"crossref","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. Futur Gener Comput. Syst. 97, 849\u2013872 (2019)","journal-title":"Futur Gener Comput. Syst."},{"key":"5558_CR36","doi-asserted-by":"crossref","unstructured":"Salam, M.A., Alzahrani, A.I., Alblehai, F., Zitar, R.A., Abualigah: l.: An improved Genghis Khan optimizer based on enhanced solution quality strategy for global optimization and feature selection problems. 302,112347 (2024)","DOI":"10.1016\/j.knosys.2024.112347"},{"key":"5558_CR37","doi-asserted-by":"crossref","first-page":"124882","DOI":"10.1016\/j.eswa.2024.124882","volume":"256","author":"MA Salam","year":"2024","unstructured":"Salam, M.A., Askr, H., Hassanien, A.E.: Adaptive chaotic dynamic learning-based gazelle optimization algorithm for feature selection problems. Expert Syst. Appl. 256, 124882 (2024)","journal-title":"Expert Syst. Appl."},{"key":"5558_CR38","doi-asserted-by":"crossref","first-page":"108803","DOI":"10.1016\/j.compbiomed.2024.108803","volume":"179","author":"MA Salam","year":"2024","unstructured":"Salam, M.A., Gang, H., Celik, E., Soleimanian, G.F., Hasnonyibrahim, M.E.: Chaotic RIME optimization algorithm with adaptive mutualism for feature selection problems. Comput. Biol. Med. 179, 108803 (2024)","journal-title":"Comput. Biol. Med."},{"key":"5558_CR39","doi-asserted-by":"crossref","first-page":"111725","DOI":"10.1016\/j.knosys.2024.111725","volume":"295","author":"M Elhoseny","year":"2024","unstructured":"Elhoseny, M., Salam, M.A., Hasnony, I.E.: An improved multi-strategy golden Jackal algorithm for real world engineering problems. Knowl. Based Syst. 295, 111725 (2024)","journal-title":"Knowl. Based Syst."},{"key":"5558_CR40","doi-asserted-by":"publisher","unstructured":"Sharma, S., Kumar, V.: Cheetah Optimizer for Multi-objective Optimization Problems, available at Research Square [https:\/\/doi.org\/https:\/\/doi.org\/10.21203\/rs.3.rs-3240236\/v1]","DOI":"10.21203\/rs.3.rs-3240236\/v1]"},{"key":"5558_CR41","doi-asserted-by":"crossref","unstructured":"Nayak, G., Barisal, S.K., Ray, M.C.G.W.O.: An improved grey Wolf optimization technique for test case Prioritization[J].Programming and computer software. 49(8) 942\u2013953 (2023)","DOI":"10.1134\/S0361768823080169"},{"issue":"33","key":"5558_CR42","doi-asserted-by":"crossref","first-page":"20723","DOI":"10.1007\/s00521-024-10226-x","volume":"36","author":"MA Salam","year":"2024","unstructured":"Salam, M.A., Kumar, N., Mahajan, S.: A proposed framework for crop yield prediction using hybrid feature selection approach and optimized machine learning. Neural Comput. Appl. 36(33), 20723\u201320750 (2024)","journal-title":"Neural Comput. Appl."},{"key":"5558_CR43","doi-asserted-by":"crossref","unstructured":"Salam, A., Hassanien, M.: A, E.: A novel dynamic chaotic golden Jackal optimization algorithm for Sensor-Based human activity recognition using smartphones for sustainable smart cities. Artificial intelligence for environmental sustainability and green initiatives. 542, 273\u2013296 (2024)","DOI":"10.1007\/978-3-031-63451-2_16"},{"issue":"6","key":"5558_CR44","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1002\/itl2.516","volume":"7","author":"S Sharma","year":"2024","unstructured":"Sharma, S., Kumar, V., Dutta, K.: Multi-objective prairie dog optimization algorithm for IoT-based intrusion detection. Internet Technol. Lett. 7(6), 1\u20136 (2024)","journal-title":"Internet Technol. Lett."},{"key":"5558_CR45","doi-asserted-by":"crossref","first-page":"114122","DOI":"10.1016\/j.eswa.2020.114122","volume":"167","author":"D Zhao","year":"2021","unstructured":"Zhao, D., Liu, L., Yu, F.H., Heidari, A.A., Wang, M.J., Oliva, D., Muhammad, K., Chen, H.L.: Ant colony optimization with horizontal and vertical crossover search, fundamental visions for multi-threshold image segmentation. Expert Syst. Appl. 167, 114122 (2021)","journal-title":"Expert Syst. Appl."},{"issue":"3","key":"5558_CR46","doi-asserted-by":"crossref","first-page":"1573","DOI":"10.1016\/j.eswa.2014.09.049","volume":"42","author":"AK Bhandari","year":"2015","unstructured":"Bhandari, A.K., Kumar, A., Singh, G.K.: Modified artificial bee colony based computationallyefficient multilevel thresholding for satellite imagesegmentation using kapur\u2019s, Otsu and Tsallis functions. Expert Syst. Appl. 42(3), 1573\u20131601 (2015)","journal-title":"Expert Syst. Appl."},{"key":"5558_CR47","doi-asserted-by":"crossref","unstructured":"Ouyang, C.T., Zhu, D.L., Qiu, Y.X.: Lens learning sparrow search algorithm.Computational Intelligence and Neuroscience. 3946958 (2021) (2021)","DOI":"10.1155\/2021\/3946958"},{"issue":"24","key":"5558_CR48","doi-asserted-by":"crossref","first-page":"4817","DOI":"10.1016\/j.ijleo.2015.09.127","volume":"126","author":"HY Li","year":"2015","unstructured":"Li, H.Y., He, H.Z., Wen, Y.G.: Dynamic particle swarm optimization and K-means clustering algorithm for image segmentation. Optik. 126(24), 4817\u20134822 (2015)","journal-title":"Optik"},{"key":"5558_CR49","first-page":"100680","volume":"35","author":"T Jiang","year":"2022","unstructured":"Jiang, T., Zhu, H., Liu, L., Gong, Q.: Energy-conscious flexible Job-Shop scheduling problem considering transportation time and deterioration effect simultaneously. Sustainable Comput. Inf. Syst. 35, 100680 (2022)","journal-title":"Sustainable Comput. Inf. Syst."},{"key":"5558_CR50","doi-asserted-by":"crossref","first-page":"186638","DOI":"10.1109\/ACCESS.2020.3029728","volume":"8","author":"ZM Elgamal","year":"2020","unstructured":"Elgamal, Z.M., Binti, N., Tubishat, M., Alswaitti, M., Mirjalili, S.: An improved Harris Hawks optimization algorithm with simulated annealing for feature selection in the medical field. IEEE Access. 8, 186638\u2013186652 (2020)","journal-title":"IEEE Access."},{"issue":"2","key":"5558_CR51","doi-asserted-by":"crossref","first-page":"1555","DOI":"10.1007\/s00366-020-01258-7","volume":"38","author":"A Kaveh","year":"2022","unstructured":"Kaveh, A., Rahmani, P., Eslamlou, A.D.: An efficient hybrid approach based on Harris Hawks optimization and imperialist competitive algorithm for structural optimization. Eng. Comput. 38(2), 1555\u20131583 (2022)","journal-title":"Eng. Comput."},{"key":"5558_CR52","doi-asserted-by":"crossref","first-page":"800","DOI":"10.1049\/el:20080522","volume":"44","author":"Q Huynh-Thu","year":"2008","unstructured":"Huynh-Thu, Q., Ghanbari, M.: Scope of validity of PSNR in image\/video quality assessment. Electron. Lett. 44, 800\u201380154 (2008)","journal-title":"Electron. Lett."},{"key":"5558_CR53","doi-asserted-by":"crossref","first-page":"600","DOI":"10.1109\/TIP.2003.819861","volume":"13","author":"Z Wang","year":"2004","unstructured":"Wang, Z., Bovik, A.C., Sheikh, H.R., Simoncelli, E.P.: Image quality assessment, from error visibility to structural similarity. IEEE Trans. Image Process. 13, 600\u2013612 (2004)","journal-title":"IEEE Trans. Image Process."},{"issue":"8","key":"5558_CR54","doi-asserted-by":"crossref","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"Zhang, L., Zhang, L., Mou, X., Zhang, D.: FSIM, A feature similarity index for image quality assessment. IEEE Trans. Image Process. 20(8), 2378\u20132386 (2011)","journal-title":"IEEE Trans. Image Process."},{"key":"5558_CR55","doi-asserted-by":"crossref","first-page":"33","DOI":"10.1016\/j.image.2017.11.001","volume":"61","author":"R Reisenhofer","year":"2018","unstructured":"Reisenhofer, R., Bosse, S., Kutyniok, G., Wiegand, T.: A Haar wavelet-based perceptual similarity index for image quality assessment. Signal. Process. Image Communication. 61, 33\u201343 (2018)","journal-title":"Signal. Process. Image Communication"},{"key":"5558_CR56","doi-asserted-by":"crossref","unstructured":"Aja-Fernandez, S., Estepar, R.S.J., Alberola-Lopez, C., Westin, C.F.: Image quality assessment based on local variance, in, 2006 International Conference of the Ieee Engineering in Medicine and Biology Society, IEEE,. 4815\u20134818 (2006)","DOI":"10.1109\/IEMBS.2006.259516"},{"issue":"3","key":"5558_CR57","doi-asserted-by":"crossref","first-page":"81","DOI":"10.1109\/97.995823","volume":"9","author":"Z Wang","year":"2002","unstructured":"Wang, Z., Bovik, A.C.: A universal image quality index. IEEE Signal. Process. Lett. 9(3), 81\u201384 (2002)","journal-title":"IEEE Signal. Process. Lett."},{"key":"5558_CR58","unstructured":"Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics. IEEE International Conference on Computer Vision.IEEE, (2002)"},{"issue":"6","key":"5558_CR59","doi-asserted-by":"crossref","first-page":"929","DOI":"10.1109\/TPAMI.2007.1046","volume":"29","author":"R Unnikrishnan","year":"2007","unstructured":"Unnikrishnan, R., Pantofaru, C., Hebert, M.:.Toward objective evaluation of image segmentation algorithms. IEEE Trans. Pattern Anal. Mach. Intell. 29(6), 929\u2013944 (2007)","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"key":"5558_CR60","doi-asserted-by":"crossref","first-page":"1146","DOI":"10.1109\/ACCESS.2019.2961811","volume":"8","author":"AS Menesy","year":"2020","unstructured":"Menesy, A.S., Sultan, H.M., Selim, A., Ashmawy, M.G., Kamel, S.: Developing and applying chaotic Harris Hawks optimization technique for extracting parameters of several proton exchange membrane fuel cell stacks. IEEE Access. 8, 1146\u20131159 (2020)","journal-title":"IEEE Access."},{"key":"5558_CR61","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/j.eswa.2017.02.035","volume":"79","author":"R Salgotra","year":"2017","unstructured":"Salgotra, R., Singh, U.: Application of mutation operators to flower pollination algorithm. Expert Syst. Appl. 79, 112\u2013129 (2017)","journal-title":"Expert Syst. Appl."},{"key":"5558_CR62","doi-asserted-by":"crossref","unstructured":"Wang, H., Li, H., Liu, Y., Li, C.H., Zeng, S.Y.: Opposition-based Particle Swarm Algorithm with Cauchy Mutation. The 2007 IEEE Congress on Evolutionary Computation. IEEE (2007)","DOI":"10.1109\/SIS.2007.367959"},{"key":"5558_CR63","doi-asserted-by":"crossref","unstructured":"Tizhoosh, H.R.: Opposition-Based Learning: A New Scheme for Machine Intelligence. International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce (CIMCA-IAWTIC\u201906). 695\u2013701 (2006)","DOI":"10.1109\/CIMCA.2005.1631345"},{"issue":"07","key":"5558_CR64","first-page":"1558","volume":"36","author":"Q He","year":"2021","unstructured":"He, Q., Lin, J., Xu, H.: Hybrid cauchy mutation and uniform distribution of grasshopper optimization algorithm. Control Decis. 36(07), 1558\u20131568 (2021)","journal-title":"Control Decis."},{"key":"5558_CR65","doi-asserted-by":"crossref","first-page":"59","DOI":"10.1016\/j.plrev.2015.03.002","volume":"14","author":"A Reynolds","year":"2015","unstructured":"Reynolds, A.: L\u00e9vy walk research from the shackles of optimal foraging. Phys. Life Rev. 14, 59\u201383 (2015)","journal-title":"Phys. Life Rev."},{"key":"5558_CR66","doi-asserted-by":"crossref","first-page":"654","DOI":"10.1016\/j.apm.2018.07.044","volume":"64","author":"J Luo","year":"2018","unstructured":"Luo, J., Chen, H., Zhang, Q., Xu, Y., Huang, H., Zhao, X.: An improved grasshopper optimization algorithm with application to financial stress prediction appl. Math. Model. 64, 654\u2013668 (2018)","journal-title":"Math. Model."},{"issue":"4","key":"5558_CR67","doi-asserted-by":"crossref","first-page":"617","DOI":"10.1016\/0031-3203(93)90115-D","volume":"26","author":"CH Li","year":"1993","unstructured":"Li, C.H., Lee, C.K.: Minimum cross entropy thresholding. Pattern Recognit. 26(4), 617\u2013625 (1993)","journal-title":"Pattern Recognit."},{"key":"5558_CR68","doi-asserted-by":"crossref","unstructured":"Martin, D., Fowlkes, C., Tal, D., Malik, J.: A database of human segmented natural images and its application to evaluating segmentation algorithms and measuring ecological statistics, in, Proceedings Eighth IEEE International Conference on Computer Vision. ICCV. 416\u2013423 (2001)","DOI":"10.1109\/ICCV.2001.937655"},{"key":"5558_CR69","doi-asserted-by":"crossref","unstructured":"Saha, C., Hossain, M.F.: MRI brain tumor images classification using K-means clustering, NSCT and SVM. IEEE Uttar Pradesh Section International Conference on Electrical, Computer and Electronics. 329\u2013333, IEEE, (2017)","DOI":"10.1109\/UPCON.2017.8251069"},{"key":"5558_CR70","doi-asserted-by":"crossref","unstructured":"Awad, N.H., Ali, M.Z., Suganthan, P.N.: Ensemble sinusoidal differential covariance matrix adaptation with Euclidean neighborhood for solving CEC 2017 benchmark problems. 2017 IEEE Congress on Evolutionary Computation (CEC). 372\u2013379, IEEE, (2017)","DOI":"10.1109\/CEC.2017.7969336"},{"key":"5558_CR71","doi-asserted-by":"crossref","first-page":"113428","DOI":"10.1016\/j.eswa.2020.113428","volume":"155","author":"RE Erick","year":"2020","unstructured":"Erick, R.E., Zanella, L.A., Oliva, D., Heidari, A.A., Foong, L.K.: An efficient Harris Hawks-inspired image segmentation method. Expert Syst. Appl. 155, 113428 (2020)","journal-title":"Expert Syst. Appl."},{"key":"5558_CR72","doi-asserted-by":"crossref","first-page":"107468","DOI":"10.1016\/j.knosys.2021.107468","volume":"232","author":"R Bandyopadhyay","year":"2021","unstructured":"Bandyopadhyay, R., Kundu, R., Oliva, D., Sarkar, R.: Segmentation of brain MRI using an altruistic Harris hawks\u2019 optimization algorithm. Knowl. Based Syst. 232, 107468 (2021)","journal-title":"Knowl. Based Syst."},{"key":"5558_CR73","doi-asserted-by":"crossref","first-page":"144665","DOI":"10.1109\/ACCESS.2020.3014309","volume":"8","author":"W Xie","year":"2020","unstructured":"Xie, W., Xing, C., Wang, J., Guo, S.S., Guo, M.W., Zhu, L.F.: Hybrid Henry gas solubility optimization algorithm based on the Harris Hawk optimization. IEEE Access. 8, 144665\u2013144692 (2020)","journal-title":"IEEE Access."},{"key":"5558_CR74","doi-asserted-by":"crossref","unstructured":"Mohamed, A.W., Hadi, A.A., Mohamed, A.K., Awad, N.H.: Evaluating the performance of adaptive gainingsharing knowledge based algorithm on cec 2020 benchmark problems. 2020 IEEE Congress on Evolutionary Computation (CEC). 1\u20138, IEEE, (2020)","DOI":"10.1109\/CEC48606.2020.9185901"},{"issue":"4","key":"5558_CR75","doi-asserted-by":"crossref","first-page":"257","DOI":"10.1080\/00031305.1988.10475580","volume":"42","author":"Y Benjamini","year":"1988","unstructured":"Benjamini, Y.: Opening the box of a boxplot. Am. Stat. 42(4), 257\u2013262 (1988)","journal-title":"Am. Stat."},{"key":"5558_CR76","doi-asserted-by":"crossref","first-page":"183","DOI":"10.1002\/polc.5070060121","volume":"100","author":"HL Friedman","year":"1964","unstructured":"Friedman, H.L.: Kinetics of thermal degradation of charforming plastic from thermogravimetry. J. Polym. Symposia. 100, 183\u2013195 (1964)","journal-title":"J. Polym. Symposia"}],"container-title":["Cluster Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05558-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10586-025-05558-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10586-025-05558-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,5,26]],"date-time":"2026-05-26T12:15:39Z","timestamp":1779797739000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10586-025-05558-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,9,19]]},"references-count":76,"journal-issue":{"issue":"13","published-print":{"date-parts":[[2025,11]]}},"alternative-id":["5558"],"URL":"https:\/\/doi.org\/10.1007\/s10586-025-05558-9","relation":{},"ISSN":["1386-7857","1573-7543"],"issn-type":[{"value":"1386-7857","type":"print"},{"value":"1573-7543","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,9,19]]},"assertion":[{"value":"11 November 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 May 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 June 2025","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 September 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 conflict of interest. All authors declare that there are no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This content has been made available to all.","name":"free","label":"Free to read"}],"article-number":"841"}}