{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T01:22:15Z","timestamp":1760145735803,"version":"build-2065373602"},"reference-count":69,"publisher":"MDPI AG","issue":"16","license":[{"start":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T00:00:00Z","timestamp":1724025600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"National Postdoctoral Program for Innovation Talents of China","award":["BX20230277","QTZX23019"],"award-info":[{"award-number":["BX20230277","QTZX23019"]}]},{"name":"Fundamental Research Funds for the Central Universities of China","award":["BX20230277","QTZX23019"],"award-info":[{"award-number":["BX20230277","QTZX23019"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>The design and optimization of sensor array configurations is a significant challenge for distributed SAR-GMTI radar systems because the system performance of distributed array radar is a comprehensive result of several conflicting evaluation indicators. This paper developed a multi-objective intelligent optimization method to solve the global optimal problem of array configurations in terms of achieving optimal GMTI performance. Firstly, to formulate the relationship between array configuration and GMTI performance, we established three objective functions derived from evaluating indicators of SAR-GMTI performance. Specifically, in the objective functions, we proposed a novel clutter covariance matrix model that added several typical non-ideal factors of the real-world detection environment. This provides a way to build a bridge between the array configuration, environment clutter, and GMTI performance. Then, we proposed an improved multi-objective snake optimization algorithm (IMOSOA) that combined the Pareto optimization mechanism with snake optimization to solve the multi-objective optimization problem while reconciling the conflicts between different objective functions. Meanwhile, some significant improvements were made to speed up convergence. That is, tent chaotic mapping-based initialization, multi-group coevolution, and individual mutation strategies were applied to solve the non-convergence problem of global searching. Finally, in the case of an airborne SAR-GMTI system, numerical experiments demonstrated that the proposed IMOSOA has superior performance than other contrast methods, especially in terms of GMTI applications.<\/jats:p>","DOI":"10.3390\/rs16163041","type":"journal-article","created":{"date-parts":[[2024,8,19]],"date-time":"2024-08-19T06:41:31Z","timestamp":1724049691000},"page":"3041","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["A Multi-Objective Intelligent Optimization Method for Sensor Array Optimization in Distributed SAR-GMTI Radar Systems"],"prefix":"10.3390","volume":"16","author":[{"given":"Xianghai","family":"Li","sequence":"first","affiliation":[{"name":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Rong","family":"Wang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gengchen","family":"Liang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhiwei","family":"Yang","sequence":"additional","affiliation":[{"name":"National Key Laboratory of Radar Signal Processing, Xidian University, Xi\u2019an 710071, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,8,19]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"373","DOI":"10.1109\/LGRS.2008.916067","article-title":"Ground Moving Target Indication Using an InSAR System with a Hybrid Baseline","volume":"5","author":"Yang","year":"2008","journal-title":"IEEE Trans. Geosci. Remote Sens. Lett."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"46","DOI":"10.1109\/MGRS.2019.2957600","article-title":"Along-Track Interferometric SAR Systems for Ground-Moving Target Indication: Achievements, Potentials, and Outlook","volume":"8","author":"Budillon","year":"2020","journal-title":"IEEE Geosci. Remote Sens. Mag."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"171","DOI":"10.1109\/JSTARS.2012.2210999","article-title":"TanDEM-X water indication mask: Generation and first evaluation results","volume":"6","author":"Wendleder","year":"2013","journal-title":"IEEE J. Sel. Top. Appl. Earth Observ. Remote Sens."},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"1554","DOI":"10.1109\/TGRS.2015.2483019","article-title":"Dual-Platform Large Along-Track Baseline GMTI","volume":"54","author":"Baumgartner","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"437","DOI":"10.1109\/LAWP.2009.2015899","article-title":"Sidelobe Reduction Through Element Phase Control in Uniform Subarrayed Array Antennas","volume":"8","author":"Rocca","year":"2009","journal-title":"IEEE Antennas Wirel. Propag. Lett."},{"key":"ref_6","first-page":"1","article-title":"A Novel Knowledge-aided Training Samples Selection Method for Terrain Clutter Suppression in Hybrid Baseline Radar Systems","volume":"60","author":"Li","year":"2022","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"103282","DOI":"10.1016\/j.dsp.2021.103282","article-title":"Nonhomogeneous clutter suppression based on terrain elevation interferometric phase compensation in multi-satellite formation systems","volume":"121","author":"Li","year":"2022","journal-title":"Digit. Signal Process."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/LGRS.2024.3438623","article-title":"A Closed-Form Expression of STAP Performance for Distributed Aperture Coherence MIMO Radar","volume":"21","author":"Li","year":"2024","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"3401","DOI":"10.1109\/TAP.2010.2050425","article-title":"A Hybrid Optimization Algorithm and Its Application for Conformal Array Pattern Synthesis","volume":"58","author":"Li","year":"2010","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"646","DOI":"10.1049\/iet-map.2011.0330","article-title":"Optimisation method on conformal array element positions for low sidelobe pattern synthesis","volume":"6","author":"Yang","year":"2012","journal-title":"IET Microw. Antennas Propag."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"77429","DOI":"10.1109\/ACCESS.2018.2883042","article-title":"Low-Sidelobe Pattern Synthesis for Sparse Conformal Arrays Based on PSO-SOCP Optimization","volume":"6","author":"Li","year":"2018","journal-title":"IEEE Access"},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"2912","DOI":"10.1109\/TAP.2004.835130","article-title":"A hybrid approach for the optimal synthesis of pencil beams through array antennas","volume":"52","author":"Isernia","year":"2004","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"372","DOI":"10.1109\/29.1534","article-title":"On properties and design of nonuniformly spaced linear arrays (antennas)","volume":"36","author":"Jarske","year":"1988","journal-title":"IEEE Trans. Acoust. Speech Signal Process."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3840","DOI":"10.1109\/TAP.2016.2586490","article-title":"Maximally sparse, steerable, and nonsuperdirective array antennas via convex optimizations","volume":"64","author":"Prisco","year":"2016","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"1498","DOI":"10.1109\/LAWP.2021.3088492","article-title":"Synthesis of sparse antenna arrays subject to constraint on directivity via iterative convex optimization","volume":"20","author":"Yang","year":"2021","journal-title":"IEEE Antennas Wirel. Propag. Lett."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"1587","DOI":"10.1109\/LAWP.2021.3091613","article-title":"Synthesis of multiplepattern planar arrays by the multitask Bayesian compressive sensing","volume":"20","author":"Gong","year":"2021","journal-title":"IEEE Antennas Wirel. Propag. Lett."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"1677","DOI":"10.1109\/TWC.2019.2956146","article-title":"Joint antenna selection and hybrid beamformer design using unquantized and quantized deep learning network","volume":"19","author":"Elbir","year":"2020","journal-title":"IEEE Trans. Wirel. Commun."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"133","DOI":"10.1109\/TAES.2023.3285201","article-title":"Sparse Array Design for Optimum Beamforming Using Deep Learning","volume":"60","author":"Hamza","year":"2024","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"1067","DOI":"10.1109\/TAP.2007.893375","article-title":"Synthesis of sparse planar arrays using modified real genetic algorithm","volume":"55","author":"Chen","year":"2007","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"1124","DOI":"10.1109\/LAWP.2015.2496173","article-title":"Synthesis of uniformly excited concentric ring arrays using the improved integer GA","volume":"15","author":"Jiang","year":"2016","journal-title":"IEEE Antennas Wirel. Propag. Lett."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"783","DOI":"10.1049\/el:20081045","article-title":"Ant colony optimization for tree-searching based synthesis of monopulse array antenna","volume":"44","author":"Rocca","year":"2008","journal-title":"Electron. Lett."},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"279","DOI":"10.2528\/PIER10092008","article-title":"Optimal sub-arraying of compromise planar arrays through an innovative ACO-weighted procedure","volume":"109","author":"Oliveri","year":"2010","journal-title":"Prog. Electromag. Res."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1007\/s10845-015-1039-3","article-title":"An effective and distributed particle swarm optimization algorithm for flexible job-shop scheduling problem","volume":"29","author":"Nouiri","year":"2015","journal-title":"J. Intell. Manuf."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"1235","DOI":"10.1049\/iet-rsn.2016.0464","article-title":"Synthesis of conformal array antenna for hypersonic platform SAR using modified particle swarm optimization","volume":"11","author":"Zhou","year":"2017","journal-title":"IET Radar Sonar Navig."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"821","DOI":"10.1007\/s13042-016-0610-3","article-title":"An improved dynamic discrete firefly algorithm for blind image steganalysis","volume":"9","author":"Chhikara","year":"2016","journal-title":"Int. J. Mach. Learn. Cyber."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"2934","DOI":"10.1109\/TAP.2019.2902960","article-title":"Thin-Wire Antenna Design Using a Novel Branching Scheme and Genetic Algorithm Optimization","volume":"67","author":"Smith","year":"2019","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"100743","DOI":"10.1016\/j.swevo.2020.100743","article-title":"Multi-objective self-organizing optimization for constrained sparse array synthesis","volume":"58","author":"Li","year":"2020","journal-title":"Swarm Evol. Comput."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1109\/TMAG.2015.2481883","article-title":"An Improved Multi-Objective Genetic Algorithm for Large Planar Array Thinning","volume":"52","author":"Cheng","year":"2016","journal-title":"IEEE Trans. Magn."},{"key":"ref_29","doi-asserted-by":"crossref","unstructured":"Cao, A., Li, H., Ma, S., Jing, T., and Zhou, J. (2015, January 6\u20139). Sparse circular array pattern optimization based on MOPSO and convex optimization. Proceedings of the 2015 Asia-Pacific Microwave Conference (APMC), Nanjing, China.","DOI":"10.1109\/APMC.2015.7412993"},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"807","DOI":"10.1109\/TEVC.2015.2505784","article-title":"Pareto fronts of many objective degenerate test problems","volume":"20","author":"Ishibuchi","year":"2016","journal-title":"IEEE Trans. Evolut. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Lee, K.Y., and El-Sharkawi, M.A. (2008). Pareto Multi-objective Optimization. Modern Heuristic Optimization Techniques, John Wiley & Sons, Inc.","DOI":"10.1002\/9780470225868"},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"182","DOI":"10.1109\/4235.996017","article-title":"A fast and elitist multiobjective genetic algorithm: NSGA-II","volume":"6","author":"Deb","year":"2002","journal-title":"IEEE Trans. Evolut. Comput."},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"108283","DOI":"10.1016\/j.sigpro.2021.108283","article-title":"A Novel Sparse Reconstruction Method based on Multi-objective Artificial Bee Colony Algorithm","volume":"189","author":"Erkoc","year":"2021","journal-title":"Signal Process."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1007\/s10489-016-0825-8","article-title":"Multi-objective ant lion optimizer: A multi-objective optimization algorithm for solving engineering problems","volume":"46","author":"Mirjalili","year":"2016","journal-title":"Appl. Intell."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"106442","DOI":"10.1016\/j.asoc.2020.106442","article-title":"A Multi-Objective Artificial Butterfly Optimization Approach for Feature Selection","volume":"94","author":"Rodrigues","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"106294","DOI":"10.1016\/j.asoc.2020.106294","article-title":"A new combined model based on multi-objective salp swarm optimization for wind speed forecasting","volume":"92","author":"Cheng","year":"2020","journal-title":"Appl. Soft Comput."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1109\/TAES.1973.309792","article-title":"Theory of Adaptive Radar","volume":"AES-9","author":"Brennan","year":"1973","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"29","DOI":"10.1049\/ecej:19990106","article-title":"Space-time processing for multichannel synthetic aperture radar","volume":"11","author":"Ender","year":"1999","journal-title":"Electron. Commun. Eng. J."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"3868","DOI":"10.1109\/TGRS.2012.2186637","article-title":"Optimum SAR\/GMTI Processing and Its Application to the Radar Satellite RADARSAT-2 for Traffic Monitoring","volume":"50","author":"Sikaneta","year":"2012","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_40","doi-asserted-by":"crossref","first-page":"605","DOI":"10.1016\/j.dsp.2012.03.001","article-title":"Detection of heterogeneous samples based on loaded generalized inner product method","volume":"22","author":"Tang","year":"2012","journal-title":"Digit. Signal Process."},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.dsp.2017.10.008","article-title":"A generalized sample weighting method in heterogeneous environment for space-time adaptive processing","volume":"72","author":"Xu","year":"2018","journal-title":"Digit. Signal Process."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"1021","DOI":"10.1109\/TAES.2006.248216","article-title":"An approach to knowledge-aided covariance estimation","volume":"42","author":"Melvin","year":"2006","journal-title":"IEEE Trans. Aerosp. Electron. Syst."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"262","DOI":"10.1016\/j.dsp.2016.10.005","article-title":"Enhanced knowledge-aided space-time adaptive processing exploiting inaccurate prior knowledge of the array manifold","volume":"60","author":"Yang","year":"2016","journal-title":"Digit. Signal Process"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"045013","DOI":"10.1117\/1.JRS.11.045013","article-title":"Robust nonhomogeneous training samples detection method for space-time adaptive processing radar using sparse-recovery with knowledge-aided","volume":"11","author":"Li","year":"2017","journal-title":"J. Appl. Remote Sens."},{"key":"ref_45","unstructured":"Bento, M., Ramon, P., and Luis, C. (2004, January 5\u20138). Considerations About Forward Fuselage Aerodynamic Design of a Transport Aircraft. Proceedings of the 42nd AIAA Aerospace Sciences Meeting and Exhibit, Reno, NV, USA."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"2385","DOI":"10.1109\/TGRS.2015.2500918","article-title":"Multichannel Analysis and Suppression of Sea Clutter for Airborne Microwave Radar Systems","volume":"54","author":"Gracheva","year":"2016","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_47","unstructured":"Ward, J. (1994). Space-Time Adaptive Processing for Airborne Radar, MIT Lincoln Lab."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"1581","DOI":"10.1109\/TAP.2008.923354","article-title":"Grating lobe reduction in a phased array of limited scanning","volume":"56","author":"Wang","year":"2008","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"716","DOI":"10.1109\/TGRS.2009.2034980","article-title":"Development of the TanDEM-X Calibration Concept: Analysis of Systematic Errors","volume":"48","author":"Gonzalez","year":"2010","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"1829","DOI":"10.1109\/LGRS.2019.2911735","article-title":"A Novel Baseline Estimation Method for Multichannel HRSW SAR System","volume":"16","author":"Huang","year":"2019","journal-title":"IEEE Trans. Geosci. Remote Sens. Lett."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"977","DOI":"10.1109\/78.752596","article-title":"Theory and application of covariance matrix tapers for robust adaptive beamforming","volume":"47","author":"Guerci","year":"1999","journal-title":"IEEE Trans. Signal Process."},{"key":"ref_52","first-page":"1","article-title":"A Spectral Model for Multilook InSAR Phase Noise Due to Geometric Decorrelation","volume":"61","author":"Chen","year":"2023","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_53","doi-asserted-by":"crossref","first-page":"950","DOI":"10.1109\/36.175330","article-title":"Decorrelation in interferometric radar echoes","volume":"30","author":"Zebker","year":"1992","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"30","DOI":"10.1016\/j.isprsjprs.2012.06.004","article-title":"Relative height error analysis of TanDEM-X elevation data","volume":"73","author":"Rizzoli","year":"2012","journal-title":"ISPRS J. Photogramm. Remote Sens."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"1808","DOI":"10.1109\/TCYB.2013.2295886","article-title":"Hybridization of decomposition and local search for multiobjective optimization","volume":"44","author":"Ke","year":"2014","journal-title":"IEEE Trans. Cybern."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"3703","DOI":"10.1007\/s12205-020-0504-5","article-title":"Modified Whale Optimization Algorithm Based on Tent Chaotic Mapping and Its Application in Structural Optimization","volume":"24","author":"Li","year":"2020","journal-title":"KSCE J. Civ. Eng."},{"key":"ref_57","doi-asserted-by":"crossref","first-page":"4406","DOI":"10.1109\/TAP.2020.2969741","article-title":"Synthesis of large unequally spaced planar arrays utilizing differential evolution with new encoding mechanism and Cauchy mutation","volume":"68","author":"Liu","year":"2020","journal-title":"IEEE Trans. Antennas Propag."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Deb, K. (2011). Multi-objective optimisation using evolutionary algorithms: An introduction. Multi-Objective Evolutionary Optimisation for Product Design and Manufacturing, Springer.","DOI":"10.1007\/978-0-85729-652-8_1"},{"key":"ref_59","unstructured":"Knowles, J., and Corne, D. (1999, January 6\u20139). The Pareto archived evolution strategy: A new baseline algorithm for Pareto multiobjective optimisation. Proceedings of the 1999 Congress on Evolutionary Computation (CEC99), Washington, DC, USA."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"32","DOI":"10.1016\/j.swevo.2011.03.001","article-title":"Multiobjective evolutionary algorithms: A survey of the state of the art","volume":"1","author":"Zhou","year":"2011","journal-title":"Swarm Evol. Comput."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"28","DOI":"10.1109\/MCI.2006.329691","article-title":"Ant colony optimization","volume":"1","author":"Dorigo","year":"2006","journal-title":"IEEE Comput. Intell. Mag."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"459","DOI":"10.1007\/s10898-007-9149-x","article-title":"A powerful and efficient algorithm for numerical function optimization: Artificial bee colony (ABC) algorithm","volume":"39","author":"Karaboga","year":"2007","journal-title":"J. Global Optim."},{"key":"ref_63","doi-asserted-by":"crossref","first-page":"78","DOI":"10.1504\/IJBIC.2010.032124","article-title":"Firefly algorithm, stochastic test functions and design optimization","volume":"2","author":"Yang","year":"2010","journal-title":"Int. J. Bio-Inspired Comput."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"51","DOI":"10.1016\/j.advengsoft.2016.01.008","article-title":"The whale optimization algorithm","volume":"95","author":"Mirjalili","year":"2016","journal-title":"Adv. Eng. Softw."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"163","DOI":"10.1016\/j.advengsoft.2017.07.002","article-title":"Salp swarm algorithm: A bio-inspired optimizer for engineering design problems","volume":"114","author":"Mirjalili","year":"2017","journal-title":"Adv. Eng. Softw."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"77746","DOI":"10.1109\/ACCESS.2020.2990338","article-title":"Ant lion optimization: Variants, hybrids, and applications","volume":"8","author":"Assiri","year":"2020","journal-title":"IEEE Access"},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"309","DOI":"10.1007\/s13042-021-01326-4","article-title":"A self-adaptive harris hawks optimization algorithm with opposition-based learning and chaotic local search strategy for global optimization and feature selection","volume":"13","author":"Hussien","year":"2021","journal-title":"Int. J. Mach. Learn. Cybern."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"1935","DOI":"10.1007\/s00366-021-01542-0","article-title":"Boosting whale optimization with evolution strategy and gaussian random walks: An image segmentation method","volume":"39","author":"Hussien","year":"2022","journal-title":"Eng. Comput."},{"key":"ref_69","doi-asserted-by":"crossref","first-page":"108320","DOI":"10.1016\/j.knosys.2022.108320","article-title":"Snake Optimizer: A novel meta-heuristic optimization algorithm","volume":"242","author":"Hashim","year":"2022","journal-title":"Knowl. Based Syst."}],"container-title":["Remote Sensing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/16\/3041\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,10]],"date-time":"2025-10-10T15:38:56Z","timestamp":1760110736000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2072-4292\/16\/16\/3041"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,8,19]]},"references-count":69,"journal-issue":{"issue":"16","published-online":{"date-parts":[[2024,8]]}},"alternative-id":["rs16163041"],"URL":"https:\/\/doi.org\/10.3390\/rs16163041","relation":{},"ISSN":["2072-4292"],"issn-type":[{"type":"electronic","value":"2072-4292"}],"subject":[],"published":{"date-parts":[[2024,8,19]]}}}