{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T18:11:53Z","timestamp":1773339113249,"version":"3.50.1"},"reference-count":64,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T00:00:00Z","timestamp":1742342400000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T00:00:00Z","timestamp":1742342400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"funder":[{"name":"National Undergraduate Training Program on Innovation and Entrepreneurship","award":["202410345054"],"award-info":[{"award-number":["202410345054"]}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["J Membr Comput"],"published-print":{"date-parts":[[2026,3]]},"DOI":"10.1007\/s41965-025-00186-z","type":"journal-article","created":{"date-parts":[[2025,3,19]],"date-time":"2025-03-19T17:29:43Z","timestamp":1742405383000},"page":"12-40","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["A coordinated pyramid model multi-strategy grey wolf optimization algorithm for Tsallis threshold segmentation"],"prefix":"10.1007","volume":"8","author":[{"given":"Jiaying","family":"Shen","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Leyi","family":"Wang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jialing","family":"Hu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xiaoyi","family":"Yu","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhaolong","family":"Ouyang","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2025,3,19]]},"reference":[{"issue":"12","key":"186_CR1","doi-asserted-by":"publisher","first-page":"2259","DOI":"10.1016\/S0031-3203(00)00149-7","volume":"34","author":"HD Cheng","year":"2001","unstructured":"Cheng, H. D., Jiang, X. H., Sun, Y., et al. (2001). Color image segmentation: Advances and prospects. Pattern Recognition, 34(12), 2259\u20132281.","journal-title":"Pattern Recognition"},{"issue":"1","key":"186_CR2","doi-asserted-by":"publisher","first-page":"33","DOI":"10.1007\/s11721-007-0002-0","volume":"1","author":"R Poli","year":"2007","unstructured":"Poli, R., Kennedy, J., & Blackwell, T. (2007). Particle swarm optimization. Swarm Intelligence, 1(1), 33\u201357.","journal-title":"Swarm Intelligence"},{"key":"186_CR3","doi-asserted-by":"publisher","first-page":"46","DOI":"10.1016\/j.advengsoft.2013.12.007","volume":"69","author":"S Mirjalili","year":"2014","unstructured":"Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in Engineering Software, 69, 46\u201361.","journal-title":"Advances in Engineering Software"},{"key":"186_CR4","doi-asserted-by":"publisher","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","volume":"95","author":"S Mirjalili","year":"2016","unstructured":"Mirjalili, S., & Lewis, A. (2016). The whale optimization algorithm. Advances in Engineering Software, 95, 51\u201367.","journal-title":"Advances in Engineering Software"},{"key":"186_CR5","doi-asserted-by":"crossref","unstructured":"Rao, R. V., Savsani, V. J., & Vakharia, D. P. (2011). Teaching\u2013learning-based optimization: a novel method for constrained mechanical design optimization problems. Computer-aided Design, 43(3), 303\u2013315.","DOI":"10.1016\/j.cad.2010.12.015"},{"issue":"1","key":"186_CR6","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. (2020). A novel swarm intelligence optimization approach: Sparrow search algorithm. Systems Science and Control Engineering, 8(1), 22\u201334.","journal-title":"Systems Science and Control Engineering"},{"key":"186_CR7","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2019.103300","volume":"87","author":"W Zhao","year":"2020","unstructured":"Zhao, W., Zhang, Z., & Wang, L. (2020). Manta ray foraging optimization: An effective bio-inspired optimizer for engineering applications. Engineering Applications of Artificial Intelligence, 87, 103300.","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"186_CR8","doi-asserted-by":"publisher","first-page":"121597","DOI":"10.1016\/j.eswa.2023.121597","volume":"237(PC)","author":"D Zhu","year":"2024","unstructured":"Zhu, D., Wang, S., Zhou, C., et al. (2024). Human memory optimization algorithm: A memory-inspired optimizer for global optimization problems. Expert Systems with Applications, 237(PC), 121597.","journal-title":"Expert Systems with Applications"},{"key":"186_CR9","doi-asserted-by":"publisher","first-page":"101737","DOI":"10.1016\/j.swevo.2024.101737","volume":"91","author":"D Zhu","year":"2024","unstructured":"Zhu, D., Shen, J., Zhang, Y., et al. (2024). Multi-strategy particle swarm optimization with adaptive forgetting for base station layout. Swarm and Evolutionary Computation, 91, 101737.","journal-title":"Swarm and Evolutionary Computation"},{"key":"186_CR10","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105015","volume":"139","author":"S Zhao","year":"2021","unstructured":"Zhao, S., Wang, P., Heidari, A. A., et al. (2021). Performance optimization of salp swarm algorithm for multi-threshold image segmentation: Comprehensive study of breast cancer microscopy. Computers in Biology and Medicine, 139, 105015.","journal-title":"Computers in Biology and Medicine"},{"key":"186_CR11","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.104960","volume":"113","author":"G Ma","year":"2022","unstructured":"Ma, G., & Yue, X. (2022). An improved whale optimization algorithm based on multilevel threshold image segmentation using the Otsu method. Engineering Applications of Artificial Intelligence, 113, 104960.","journal-title":"Engineering Applications of Artificial Intelligence"},{"issue":"23","key":"186_CR12","doi-asserted-by":"publisher","first-page":"33513","DOI":"10.1007\/s11042-022-13073-x","volume":"81","author":"D Wu","year":"2022","unstructured":"Wu, D., & Yuan, C. (2022). Threshold image segmentation based on improved sparrow search algorithm. Multimedia tools and applications, 81(23), 33513\u201333546.","journal-title":"Multimedia tools and applications"},{"key":"186_CR13","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.104941","volume":"139","author":"Q Zhang","year":"2021","unstructured":"Zhang, Q., Wang, Z., Heidari, A. A., et al. (2021). Gaussian barebone salp swarm algorithm with stochastic fractal search for medical image segmentation: A COVID-19 case study. Computers in Biology and Medicine, 139, 104941.","journal-title":"Computers in Biology and Medicine"},{"issue":"1","key":"186_CR14","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1016\/j.asej.2020.09.003","volume":"12","author":"R Srikanth","year":"2021","unstructured":"Srikanth, R., & Bikshalu, K. (2021). Multilevel thresholding image segmentation based on energy curve with harmony search algorithm. Ain Shams Engineering Journal, 12(1), 1\u201320.","journal-title":"Ain Shams Engineering Journal"},{"key":"186_CR15","doi-asserted-by":"publisher","DOI":"10.1016\/j.compbiomed.2021.105181","volume":"142","author":"H Su","year":"2022","unstructured":"Su, H., Zhao, D., Yu, F., et al. (2022). Horizontal and vertical search artificial bee colony for image segmentation of COVID-19 X-ray images. Computers in Biology and Medicine, 142, 105181.","journal-title":"Computers in Biology and Medicine"},{"issue":"17","key":"186_CR16","doi-asserted-by":"publisher","first-page":"10685","DOI":"10.1007\/s00521-020-04820-y","volume":"33","author":"M Abdel-Basset","year":"2021","unstructured":"Abdel-Basset, M., Chang, V., & Mohamed, R. (2021). A novel equilibrium optimization algorithm for multi-thresholding image segmentation problems. Neural Computing and Applications, 33(17), 10685\u201310718.","journal-title":"Neural Computing and Applications"},{"issue":"3","key":"186_CR17","doi-asserted-by":"publisher","first-page":"221","DOI":"10.1007\/s40747-016-0024-6","volume":"2","author":"A Anuse","year":"2016","unstructured":"Anuse, A., & Vyas, V. (2016). A novel training algorithm for convolutional neural network. Complex and Intelligent Systems, 2(3), 221\u2013234.","journal-title":"Complex and Intelligent Systems"},{"key":"186_CR18","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2020.106996","volume":"100","author":"A Altan","year":"2021","unstructured":"Altan, A., Karasu, S., & Zio, E. (2021). A new hybrid model for wind speed forecasting combining long short-term memory neural network, decomposition methods and grey wolf optimizer. Applied Soft Computing, 100, 106996.","journal-title":"Applied Soft Computing"},{"key":"186_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.csite.2021.101250","volume":"27","author":"M Ghalambaz","year":"2021","unstructured":"Ghalambaz, M., Yengejeh, R. J., & Davami, A. H. (2021). Building energy optimization using grey wolf optimizer (GWO). Case Studies in Thermal Engineering, 27, 101250.","journal-title":"Case Studies in Thermal Engineering"},{"key":"186_CR20","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107113","volume":"102","author":"BH Abed-Alguni","year":"2021","unstructured":"Abed-Alguni, B. H., & Alawad, N. A. (2021). Distributed grey wolf optimizer for scheduling of workflow applications in cloud environments. Applied Soft Computing, 102, 107113.","journal-title":"Applied Soft Computing"},{"issue":"21","key":"186_CR21","doi-asserted-by":"publisher","first-page":"14583","DOI":"10.1007\/s00521-021-06099-z","volume":"33","author":"B Sathiyabhama","year":"2021","unstructured":"Sathiyabhama, B., Kumar, S. U., Jayanthi, J., et al. (2021). A novel feature selection framework based on grey wolf optimizer for mammogram image analysis. Neural Computing and Applications, 33(21), 14583\u201314602.","journal-title":"Neural Computing and Applications"},{"key":"186_CR22","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107379","volume":"230","author":"RM Adnan","year":"2021","unstructured":"Adnan, R. M., Mostafa, R. R., Kisi, O., et al. (2021). Improving streamflow prediction using a new hybrid ELM model combined with hybrid particle swarm optimization and grey wolf optimization. Knowledge-Based Systems, 230, 107379.","journal-title":"Knowledge-Based Systems"},{"key":"186_CR23","doi-asserted-by":"publisher","DOI":"10.1016\/j.chemosphere.2021.131980","volume":"287","author":"F Musharavati","year":"2022","unstructured":"Musharavati, F., Khoshnevisan, A., Alirahmi, S. M., et al. (2022). Multi-objective optimization of a biomass gasification to generate electricity and desalinated water using grey wolf optimizer and artificial neural network. Chemosphere, 287, 131980.","journal-title":"Chemosphere"},{"key":"186_CR24","doi-asserted-by":"publisher","DOI":"10.1016\/j.measurement.2021.110272","volume":"187","author":"G Vashishtha","year":"2022","unstructured":"Vashishtha, G., & Kumar, R. (2022). An amended grey wolf optimization with mutation strategy to diagnose bucket defects in Pelton wheel. Measurement, 187, 110272.","journal-title":"Measurement"},{"issue":"4","key":"186_CR25","doi-asserted-by":"publisher","first-page":"447","DOI":"10.3390\/electronics10040447","volume":"10","author":"SN Makhadmeh","year":"2021","unstructured":"Makhadmeh, S. N., Al-Betar, M. A., Alyasseri, Z. A. A., et al. (2021). Smart home battery for the multi-objective power scheduling problem in a smart home using grey wolf optimizer. Electronics, 10(4), 447.","journal-title":"Electronics"},{"issue":"16","key":"186_CR26","doi-asserted-by":"publisher","first-page":"7732","DOI":"10.3390\/app11167732","volume":"11","author":"H Kraiem","year":"2021","unstructured":"Kraiem, H., Aymen, F., Yahya, L., et al. (2021). A comparison between particle swarm and grey wolf optimization algorithms for improving the battery autonomy in a photovoltaic system. Applied Sciences, 11(16), 7732.","journal-title":"Applied Sciences"},{"issue":"2","key":"186_CR27","doi-asserted-by":"publisher","first-page":"721","DOI":"10.1007\/s11276-021-02866-x","volume":"28","author":"M Otair","year":"2022","unstructured":"Otair, M., Ibrahim, O. T., Abualigah, L., et al. (2022). An enhanced grey wolf optimizer based particle swarm optimizer for intrusion detection system in wireless sensor networks. Wireless Networks, 28(2), 721\u2013744.","journal-title":"Wireless Networks"},{"key":"186_CR28","doi-asserted-by":"publisher","first-page":"174830261988949","DOI":"10.1177\/1748302619889498","volume":"13","author":"Z Wang","year":"2019","unstructured":"Wang, Z., Xie, H., Hu, Z., et al. (2019). Node coverage optimization algorithm for wireless sensor networks based on improved grey wolf optimizer. Journal of Algorithms and Computational Technology, 13, 1748302619889498\u20131748302619889498.","journal-title":"Journal of Algorithms and Computational Technology"},{"issue":"7","key":"186_CR29","doi-asserted-by":"publisher","first-page":"8689","DOI":"10.1007\/s11063-023-11173-9","volume":"55","author":"N Maryam","year":"2023","unstructured":"Maryam, N., Azar, M., & Mohammad, K. (2023). Active sonar image classification using deep convolutional neural network evolved by robust comprehensive grey wolf optimizer. Neural Processing Letters, 55(7), 8689\u20138712.","journal-title":"Neural Processing Letters"},{"issue":"7","key":"186_CR30","doi-asserted-by":"publisher","first-page":"1078","DOI":"10.3390\/atmos14071078","volume":"14","author":"V Todorov","year":"2023","unstructured":"Todorov, V., & Dimov, I. (2023). Unveiling the power of stochastic methods: Advancements in air pollution sensitivity analysis of the digital twin. Atmosphere, 14(7), 1078.","journal-title":"Atmosphere"},{"key":"186_CR31","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107297","volume":"228","author":"Z Zhang","year":"2021","unstructured":"Zhang, Z., & Hong, W. C. (2021). Application of variational mode decomposition and chaotic grey wolf optimizer with support vector regression for forecasting electric loads. Knowledge-Based Systems, 228, 107297.","journal-title":"Knowledge-Based Systems"},{"key":"186_CR32","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2020.106684","volume":"213","author":"J Hu","year":"2021","unstructured":"Hu, J., Chen, H., Heidari, A. A., et al. (2021). Orthogonal learning covariance matrix for defects of grey wolf optimizer: Insights, balance, diversity, and feature selection. Knowledge-Based Systems, 213, 106684.","journal-title":"Knowledge-Based Systems"},{"key":"186_CR33","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107139","volume":"226","author":"X Yu","year":"2021","unstructured":"Yu, X., Xu, W. Y., & Li, C. L. (2021). Opposition-based learning grey wolf optimizer for global optimization. Knowledge-Based Systems, 226, 107139.","journal-title":"Knowledge-Based Systems"},{"key":"186_CR34","doi-asserted-by":"publisher","DOI":"10.1016\/j.jocs.2022.101636","volume":"61","author":"MH Nadimi-Shahraki","year":"2022","unstructured":"Nadimi-Shahraki, M. H., Taghian, S., Mirjalili, S., et al. (2022). GGWO: Gaze cues learning-based grey wolf optimizer and its applications for solving engineering problems. Journal of Computational Science, 61, 101636.","journal-title":"Journal of Computational Science"},{"key":"186_CR35","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.114920","volume":"177","author":"S Khalilpourazari","year":"2021","unstructured":"Khalilpourazari, S., Doulabi, H. H., \u00c7ift\u00e7io\u011flu, A. \u00d6., et al. (2021). Gradient-based grey wolf optimizer with Gaussian walk: Application in modelling and prediction of the COVID-19 pandemic. Expert Systems with Applications, 177, 114920.","journal-title":"Expert Systems with Applications"},{"key":"186_CR36","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2020.113917","volume":"166","author":"MH Nadimi-Shahraki","year":"2021","unstructured":"Nadimi-Shahraki, M. H., Taghian, S., & Mirjalili, S. (2021). An improved grey wolf optimizer for solving engineering problems. Expert Systems with Applications, 166, 113917.","journal-title":"Expert Systems with Applications"},{"key":"186_CR37","doi-asserted-by":"publisher","DOI":"10.1016\/j.asoc.2021.107328","volume":"106","author":"M Banaie-Dezfouli","year":"2021","unstructured":"Banaie-Dezfouli, M., Nadimi-Shahraki, M. H., & Beheshti, Z. (2021). R-GWO: representative-based grey wolf optimizer for solving engineering problems. Applied Soft Computing, 106, 107328.","journal-title":"Applied Soft Computing"},{"key":"186_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117629","volume":"205","author":"C Ma","year":"2022","unstructured":"Ma, C., Huang, H., Fan, Q., et al. (2022). Grey wolf optimizer based on Aquila exploration method. Expert Systems with Applications, 205, 117629.","journal-title":"Expert Systems with Applications"},{"key":"186_CR39","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2021.116450","volume":"194","author":"S Singh","year":"2022","unstructured":"Singh, S., & Bansal, J. C. (2022). Mutation-driven grey wolf optimizer with modified search mechanism. Expert Systems with Applications, 194, 116450.","journal-title":"Expert Systems with Applications"},{"key":"186_CR40","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.117864","volume":"206","author":"K Deep","year":"2022","unstructured":"Deep, K. (2022). A random walk Grey wolf optimizer based on dispersion factor for feature selection on chronic disease prediction. Expert Systems with Applications, 206, 117864.","journal-title":"Expert Systems with Applications"},{"issue":"8","key":"186_CR41","doi-asserted-by":"publisher","first-page":"4864","DOI":"10.1002\/int.22744","volume":"37","author":"J Hu","year":"2022","unstructured":"Hu, J., Heidari, A. A., Zhang, L., et al. (2022). Chaotic diffusion-limited aggregation enhanced grey wolf optimizer: Insights, analysis, binarization, and feature selection. International Journal of Intelligent Systems, 37(8), 4864\u20134927.","journal-title":"International Journal of Intelligent Systems"},{"key":"186_CR42","doi-asserted-by":"publisher","DOI":"10.1016\/j.engappai.2022.105088","volume":"114","author":"J Wang","year":"2022","unstructured":"Wang, J., Lin, D., Zhang, Y., et al. (2022). An adaptively balanced grey wolf optimization algorithm for feature selection on high-dimensional classification. Engineering Applications of Artificial Intelligence, 114, 105088.","journal-title":"Engineering Applications of Artificial Intelligence"},{"key":"186_CR43","doi-asserted-by":"crossref","unstructured":"Yu, J., & Yang, J. (2021). Adaptive multi-strategy learning particle swarm optimization with evolutionary state estimation. In International conference on bio-inspired computing: theories and applications (pp. 174\u2013186). Singapore: Springer.","DOI":"10.1007\/978-981-19-1256-6_13"},{"key":"186_CR44","doi-asserted-by":"publisher","DOI":"10.1016\/j.radphyschem.2021.109932","volume":"192","author":"DMA Saib","year":"2022","unstructured":"Saib, D. M. A., Azman, N. Z. N., Said, M. A., et al. (2022). Evaluation of butterworth post-filtering effects on contrast and signal noise to ratio values for SPECT images reconstruction. Radiation Physics and Chemistry, 192, 109932.","journal-title":"Radiation Physics and Chemistry"},{"key":"186_CR45","doi-asserted-by":"crossref","unstructured":"Yuan, T., Deng, W., & Tang, J., et al. (2019). Signal-to-noise ratio: A robust distance metric for deep metric learning. In Proceedings of the IEEE\/CVF conference on computer vision and pattern recognition (pp. 4815\u20134824).","DOI":"10.1109\/CVPR.2019.00495"},{"key":"186_CR46","doi-asserted-by":"publisher","first-page":"1066","DOI":"10.1016\/j.ins.2022.07.165","volume":"612","author":"J Yang","year":"2022","unstructured":"Yang, J., Yu, J., & Huang, C. (2022). Adaptive multistrategy ensemble particle swarm optimization with signal-to-noise ratio distance metric. Information Sciences, 612, 1066\u20131094.","journal-title":"Information Sciences"},{"key":"186_CR47","doi-asserted-by":"publisher","first-page":"241","DOI":"10.1016\/j.apenergy.2019.01.008","volume":"237","author":"K Yu","year":"2019","unstructured":"Yu, K., Qu, B., Yue, C., et al. (2019). A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module. Applied Energy, 237, 241\u2013257.","journal-title":"Applied Energy"},{"issue":"15","key":"186_CR48","doi-asserted-by":"publisher","first-page":"6617","DOI":"10.1007\/s00500-018-3310-y","volume":"23","author":"Z Teng","year":"2019","unstructured":"Teng, Z., Lv, J., & Guo, L. (2019). An improved hybrid grey wolf optimization algorithm. Soft computing, 23(15), 6617\u20136631.","journal-title":"Soft computing"},{"key":"186_CR49","doi-asserted-by":"crossref","unstructured":"Sharma, S., Kapoor, R., & Dhiman, S. (2021). A novel hybrid metaheuristic based on augmented grey wolf optimizer and cuckoo search for global optimization. In 2021 2nd international conference on secure cyber computing and communications (ICSCCC) (pp. 376\u2013381). IEEE.","DOI":"10.1109\/ICSCCC51823.2021.9478142"},{"issue":"13","key":"186_CR50","doi-asserted-by":"publisher","first-page":"499","DOI":"10.1049\/ell2.12176","volume":"57","author":"E Akbari","year":"2021","unstructured":"Akbari, E., Rahimnejad, A., & Gadsden, S. A. (2021). A greedy non-hierarchical grey wolf optimizer for real-world optimization. Electronics Letters, 57(13), 499\u2013501.","journal-title":"Electronics Letters"},{"key":"186_CR51","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., et al. (2020). Selective opposition based grey wolf optimization. Expert Systems with Applications, 151, 113389.","journal-title":"Expert Systems with Applications"},{"issue":"3","key":"186_CR52","doi-asserted-by":"publisher","first-page":"351","DOI":"10.3390\/math10030351","volume":"10","author":"F Rezaei","year":"2022","unstructured":"Rezaei, F., Safavi, H. R., Abd Elaziz, M., et al. (2022). An enhanced grey wolf optimizer with a velocity-aided global search mechanism. Mathematics, 10(3), 351.","journal-title":"Mathematics"},{"key":"186_CR53","doi-asserted-by":"publisher","first-page":"1","DOI":"10.5555\/1248547.1248548","volume":"7","author":"J Dem\u0161ar","year":"2006","unstructured":"Dem\u0161ar, J. (2006). Statistical comparisons of classifiers over multiple data sets. The Journal of Machine learning research, 7, 1\u201330. https:\/\/doi.org\/10.5555\/1248547.1248548","journal-title":"The Journal of Machine learning research"},{"key":"186_CR54","doi-asserted-by":"publisher","first-page":"16188","DOI":"10.1109\/ACCESS.2022.3146374","volume":"10","author":"N Khodadadi","year":"2022","unstructured":"Khodadadi, N., Snasel, V., & Mirjalili, S. (2022). Dynamic arithmetic optimization algorithm for truss optimization under natural frequency constraints. IEEE Access, 10, 16188\u201316208.","journal-title":"IEEE Access"},{"key":"186_CR55","doi-asserted-by":"publisher","DOI":"10.1016\/j.knosys.2021.107555","volume":"233","author":"Y Zhang","year":"2021","unstructured":"Zhang, Y., Chi, A., & Mirjalili, S. (2021). Enhanced Jaya algorithm: A simple but efficient optimization method for constrained engineering design problems. Knowledge-Based Systems, 233, 107555.","journal-title":"Knowledge-Based Systems"},{"key":"186_CR56","doi-asserted-by":"publisher","first-page":"147596","DOI":"10.1109\/ACCESS.2019.2946664","volume":"7","author":"K Hussain","year":"2019","unstructured":"Hussain, K., Zhu, W., & Salleh, M. N. M. (2019). Long-term memory Harris\u2019 hawk optimization for high dimensional and optimal power flow problems. IEEE Access, 7, 147596\u2013147616.","journal-title":"IEEE Access"},{"key":"186_CR57","doi-asserted-by":"publisher","unstructured":"Mirjalili, S., & Hashim, S. Z. M. (2010). A new hybrid PSOGSA algorithm for function optimization. In 2010 international conference on computer and information application (pp. 374\u2013377). IEEE. https:\/\/doi.org\/10.1109\/ICCIA.2010.6141614","DOI":"10.1109\/ICCIA.2010.6141614"},{"issue":"5","key":"186_CR58","doi-asserted-by":"publisher","first-page":"1311","DOI":"10.1007\/s00500-014-1345-2","volume":"19","author":"Y Liu","year":"2015","unstructured":"Liu, Y., Mu, C., Kou, W., et al. (2015). Modified particle swarm optimization-based multilevel thresholding for image segmentation. Soft computing, 19(5), 1311\u20131327.","journal-title":"Soft computing"},{"issue":"24","key":"186_CR59","doi-asserted-by":"publisher","first-page":"4817","DOI":"10.1016\/j.ijleo.2015.09.127","volume":"126","author":"H Li","year":"2015","unstructured":"Li, H., He, H., & Wen, Y. (2015). Dynamic particle swarm optimization and K-means clustering algorithm for image segmentation. Optik, 126(24), 4817\u20134822.","journal-title":"Optik"},{"issue":"3","key":"186_CR60","doi-asserted-by":"publisher","first-page":"318","DOI":"10.3390\/e21030318","volume":"21","author":"C Lang","year":"2019","unstructured":"Lang, C., & Jia, H. (2019). Kapur\u2019s entropy for color image segmentation based on a hybrid whale optimization algorithm. Entropy, 21(3), 318.","journal-title":"Entropy"},{"key":"186_CR61","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2022.118267","volume":"209","author":"X Yu","year":"2022","unstructured":"Yu, X., & Wu, X. (2022). Ensemble grey wolf optimizer and its application for image segmentation. Expert Systems with Applications, 209, 118267.","journal-title":"Expert Systems with Applications"},{"key":"186_CR62","doi-asserted-by":"publisher","first-page":"55","DOI":"10.5815\/ijigsp.2014.10.07","volume":"10","author":"D Poobathy","year":"2014","unstructured":"Poobathy, D., & Chezian, R. M. (2014). Edge detection operators: Peak signal to noise ratio based comparison. IJ Image, Graphics and Signal Processing, 10, 55\u201361.","journal-title":"IJ Image, Graphics and Signal Processing"},{"issue":"4","key":"186_CR63","doi-asserted-by":"publisher","first-page":"1488","DOI":"10.1109\/TIP.2011.2173206","volume":"21","author":"D Brunet","year":"2011","unstructured":"Brunet, D., Vrscay, E. R., & Wang, Z. (2011). On the mathematical properties of the structural similarity index. IEEE Transactions on Image Processing, 21(4), 1488\u20131499.","journal-title":"IEEE Transactions on Image Processing"},{"issue":"8","key":"186_CR64","doi-asserted-by":"publisher","first-page":"2378","DOI":"10.1109\/TIP.2011.2109730","volume":"20","author":"L Zhang","year":"2011","unstructured":"Zhang, L., Zhang, L., Mou, X., et al. (2011). FSIM: A feature similarity index for image quality assessment. IEEE transactions on Image Processing, 20(8), 2378\u20132386.","journal-title":"IEEE transactions on Image Processing"}],"container-title":["Journal of Membrane Computing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s41965-025-00186-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s41965-025-00186-z","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s41965-025-00186-z.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,3,12]],"date-time":"2026-03-12T08:06:30Z","timestamp":1773302790000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s41965-025-00186-z"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,3,19]]},"references-count":64,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,3]]}},"alternative-id":["186"],"URL":"https:\/\/doi.org\/10.1007\/s41965-025-00186-z","relation":{},"ISSN":["2523-8906","2523-8914"],"issn-type":[{"value":"2523-8906","type":"print"},{"value":"2523-8914","type":"electronic"}],"subject":[],"published":{"date-parts":[[2025,3,19]]},"assertion":[{"value":"19 September 2024","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"13 February 2025","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"19 March 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":"The authors declare no competing interests.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}}]}}