{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,2]],"date-time":"2026-04-02T01:35:36Z","timestamp":1775093736763,"version":"3.50.1"},"reference-count":77,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2020,12,7]],"date-time":"2020-12-07T00:00:00Z","timestamp":1607299200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"DOI":"10.13039\/501100004515","name":"Universiti Kebangsaan Malaysia","doi-asserted-by":"publisher","award":["DIP-2018-041"],"award-info":[{"award-number":["DIP-2018-041"]}],"id":[{"id":"10.13039\/501100004515","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100004515","name":"Universiti Kebangsaan Malaysia","doi-asserted-by":"publisher","award":["FRGS\/1\/2018\/ICT04\/UKM\/02\/1"],"award-info":[{"award-number":["FRGS\/1\/2018\/ICT04\/UKM\/02\/1"]}],"id":[{"id":"10.13039\/501100004515","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>In this paper, a novel heuristic search algorithm called Smart Root Search (SRS) is proposed. SRS employs intelligent foraging behavior of immature, mature and hair roots of plants to explore and exploit the problem search space simultaneously. SRS divides the search space into several subspaces. It thereupon utilizes the branching and drought operations to focus on richer areas of promising subspaces while extraneous ones are not thoroughly ignored. To achieve this, the smart reactions of the SRS model are designed to act based on analyzing the heterogeneous conditions of various sections of different search spaces. In order to evaluate the performance of the SRS, it was tested on a set of known unimodal and multimodal test functions. The results were then compared with those obtained using genetic algorithms, particle swarm optimization, differential evolution and imperialist competitive algorithms and then analyzed statistically. The results demonstrated that the SRS outperformed comparative algorithms for 92% and 82% of the investigated unimodal and multimodal test functions, respectively. Therefore, the SRS is a promising nature-inspired optimization algorithm.<\/jats:p>","DOI":"10.3390\/sym12122025","type":"journal-article","created":{"date-parts":[[2020,12,10]],"date-time":"2020-12-10T22:15:36Z","timestamp":1607638536000},"page":"2025","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Smart Root Search (SRS): A Novel Nature-Inspired Search Algorithm"],"prefix":"10.3390","volume":"12","author":[{"given":"Narjes Khatoon","family":"Naseri","sequence":"first","affiliation":[{"name":"Centre of Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-2711-0659","authenticated-orcid":false,"given":"Elankovan A.","family":"Sundararajan","sequence":"additional","affiliation":[{"name":"Centre of Software Technology and Management, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Masri","family":"Ayob","sequence":"additional","affiliation":[{"name":"Data Mining and Optimization Research Group (DMO), Centre for Artificial Intelligent (CAIT), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amin","family":"Jula","sequence":"additional","affiliation":[{"name":"Data Mining and Optimization Research Group (DMO), Centre for Artificial Intelligent (CAIT), Universiti Kebangsaan Malaysia (UKM), Bangi 43600, Selangor, Malaysia"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2020,12,7]]},"reference":[{"key":"ref_1","unstructured":"Holland, J.H. (1975). Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, University of Michigan Press."},{"key":"ref_2","unstructured":"Kennedy, J., and Eberhart, R. (December, January 27). Particle swarm optimization. Proceedings of the ICNN\u201995\u2014International Conference on Neural Networks, Perth, WA, Australia."},{"key":"ref_3","doi-asserted-by":"crossref","unstructured":"Ma, Z.Y., Yuan, X., Han, S., Sun, D., and Ma, Y. (2019). Improved Chaotic Particle Swarm Optimization Algorithm with More Symmetric Distribution for Numerical Function Optimization. Symmetry, 11.","DOI":"10.3390\/sym11070876"},{"key":"ref_4","unstructured":"Dorigo, M. (1992). Optimization, Learning and Natural Algorithms. [Ph.D. Thesis, Politecnico di Milano]."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Zhao, H.G., Gao, W., Deng, W., and Sun, M. (2018). Study on an Adaptive Co-Evolutionary ACO Algorithm for Complex Optimization Problems. Symmetry, 10.","DOI":"10.3390\/sym10040104"},{"key":"ref_6","first-page":"32","article-title":"An optimizing method based on autonomous animals: Fish-swarm algorithm","volume":"22","author":"Li","year":"2002","journal-title":"Syst. Eng. Theory Pract."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"187","DOI":"10.1016\/0167-2789(86)90240-X","article-title":"The immune system, adaptation, and machine learning","volume":"2","author":"Farmer","year":"1986","journal-title":"Phys. D"},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"52","DOI":"10.1109\/MCS.2002.1004010","article-title":"Biomimicry of bacterial foraging for distributed optimization and control","volume":"22","author":"Passino","year":"2002","journal-title":"IEEE Control Syst."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1016\/j.eswa.2017.04.019","article-title":"A novel bacterial foraging optimization algorithm for feature selection","volume":"83","author":"Chen","year":"2017","journal-title":"Expert Syst. Appl."},{"key":"ref_10","first-page":"65","article-title":"A New Metaheuristic Bat-Inspired Algorithm","volume":"Volume 284","author":"Yang","year":"2010","journal-title":"Nature Inspired Cooperative Strategies for Optimization, Studies in Computational Intelligence"},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"6350","DOI":"10.1016\/j.eswa.2015.04.026","article-title":"A novel bat algorithm with habitat selection and Doppler effect in echoes for optimization","volume":"42","author":"Meng","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_12","doi-asserted-by":"crossref","unstructured":"Atashpaz-Gargari, E., and Lucas, C. (2007, January 25\u201328). Imperialist competitive algorithm: An algorithm for optimization inspired by imperialistic competition. Proceedings of the 2007 IEEE Congress on Evolutionary Computation, Singapore.","DOI":"10.1109\/CEC.2007.4425083"},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"135","DOI":"10.1016\/j.eswa.2014.07.043","article-title":"Imperialist competitive algorithm with PROCLUS classifier for service time optimization in cloud computing service composition","volume":"42","author":"Jula","year":"2015","journal-title":"Expert Syst. Appl."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"305","DOI":"10.22436\/jmcs.001.04.07","article-title":"Gravitational Attraction Search with Virtual Mass (GASVM) to solve Static Grid Job scheduling Problem","volume":"1","author":"Jula","year":"2010","journal-title":"J. Math. Comput. Sci."},{"key":"ref_15","unstructured":"Webster, B., and Bernhard, P.J. (2003, January 23\u201326). A Local Search Optimization Algorithm Based on Natural Principles of Gravitation. Proceedings of the International Conference on Information and Knowledge Engineering, Las Vegas, NV, USA."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"55","DOI":"10.1016\/j.asoc.2006.10.012","article-title":"Genetic algorithm with ant colony optimization (GA-ACO) for multiple sequence alignment","volume":"8","author":"Lee","year":"2008","journal-title":"Appl. Soft Comput."},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"595","DOI":"10.1109\/TNN.2006.890809","article-title":"New Chaotic PSO-Based Neural Network Predictive Control for Nonlinear Process","volume":"18","author":"Ying","year":"2007","journal-title":"Neural Netw. IEEE Trans."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"2816","DOI":"10.1016\/j.eswa.2013.10.014","article-title":"Multi-satellite control resource scheduling based on ant colony optimization","volume":"41","author":"Zhang","year":"2014","journal-title":"Expert Syst. Appl."},{"key":"ref_19","unstructured":"David, C., Marco, D., Fred, G., Dipankar, D., Pablo, M., Riccardo, P., and Kenneth, V.P. (1999). Memetic algorithms: A short introduction. New Ideas in Optimization, McGraw-Hill Ltd."},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"464","DOI":"10.1109\/TSMCA.2011.2159585","article-title":"Heterogeneous Redundancy Allocation for Series-Parallel Multi-State Systems Using Hybrid Particle Swarm Optimization and Local Search","volume":"42","author":"Yong","year":"2012","journal-title":"Syst. Man Cybern. Part A Syst. Hum. Ieee Trans."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"376","DOI":"10.1016\/j.asoc.2014.03.033","article-title":"Optimal approach on net routing for VLSI physical design based on Tabu-ant colonies modeling","volume":"21","author":"Yang","year":"2014","journal-title":"Appl. Soft Comput."},{"key":"ref_22","doi-asserted-by":"crossref","unstructured":"Jula, A., Othman, Z., and Sundararajan, E. (2013, January 16\u201319). A Hybrid Imperialist Competitive-Gravitational Attraction Search Algorithm to Optimize Cloud Service Composition. Proceedings of the 2013 IEEE Workshop on Memetic Computing (MC), Singapore.","DOI":"10.1109\/MC.2013.6608205"},{"key":"ref_23","unstructured":"Jula, A., and Naseri, N.K. (2012, January 24\u201326). A Hybrid Genetic Algorithm-Gravitational Attraction Search algorithm (HYGAGA) to Solve Grid Task Scheduling Problem. Proceedings of the International Conference on Soft Computing and its Applications(ICSCA\u20192012), San Francisco, CA, USA."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"17803","DOI":"10.1007\/s11042-017-5556-2","article-title":"Multimedia summarization using social media content","volume":"77","author":"Amato","year":"2018","journal-title":"Multimed. Tools Appl."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"740","DOI":"10.1016\/j.engappai.2019.07.019","article-title":"Cuckoo search algorithm with onlooker bee search for modeling PEMFCs using T2FNN","volume":"85","author":"Zhu","year":"2019","journal-title":"Eng. Appl. Artif. Intell."},{"key":"ref_26","first-page":"155","article-title":"Plants: Adaptive behavior, root-brains, and minimal cognition","volume":"19","author":"Garz","year":"2011","journal-title":"Adapt. Behav. Anim. Animat. Softw. Agents Robot. Adapt. Syst."},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"641","DOI":"10.1007\/978-3-642-31588-6_82","article-title":"Root Growth Model for Simulation of Plant Root System and Numerical Function Optimization","volume":"Volume 7389","author":"Huang","year":"2012","journal-title":"Intelligent Computing Technology"},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"571","DOI":"10.1007\/978-3-642-39482-9_66","article-title":"An Idea Based on Plant Root Growth for Numerical Optimization","volume":"Volume 7996","author":"Huang","year":"2013","journal-title":"Intelligent Computing Theories and Technology"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"16","DOI":"10.1155\/2014\/471209","article-title":"A Novel Plant Root Foraging Algorithm for Image Segmentation Problems","volume":"2014","author":"Ma","year":"2014","journal-title":"Math. Probl. Eng."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"95","DOI":"10.1016\/j.asoc.2015.08.014","article-title":"A novel bionic algorithm inspired by plant root foraging behaviors","volume":"37","author":"Ma","year":"2015","journal-title":"Appl. Soft. Comput."},{"key":"ref_31","doi-asserted-by":"crossref","unstructured":"Qi, X., Zhu, Y., Zhang, H., Zhang, D., and Wu, J. (2016, January 27\u201329). A novel bio-inspired algorithm based on plant root growth model for data clustering. Proceedings of the 35th Control Conference (CCC), Chengdu, China.","DOI":"10.1109\/ChiCC.2016.7554819"},{"key":"ref_32","doi-asserted-by":"crossref","unstructured":"Naseri, N.K., Sundararajan, E., Ayob, M., and Jula, A. (2015, January 27\u201329). Smart Root Search (SRS): A New Search Algorithm to Investigate Combinatorial Problems. Proceedings of the 2015 Seventh International Conference on Computational Intelligence, Modelling and Simulation (CIMSim), Kuantan, Malaysia.","DOI":"10.1109\/CIMSim.2015.23"},{"key":"ref_33","doi-asserted-by":"crossref","unstructured":"Hill, P.S. (2008). Vibrational Communication in Animals, Harvard University Press.","DOI":"10.4159\/9780674273825"},{"key":"ref_34","unstructured":"Buhner, S.H. (2014). Plant Intelligence and the Imaginal Realm beyond the Doors of Perception into the Dreaming of Earth, Inner Traditions Bear and Company."},{"key":"ref_35","doi-asserted-by":"crossref","unstructured":"Jung, J.K.H., and McCouch, S.R. (2013). Getting to the roots of it: Genetic and hormonal control of root architecture. Front. Plant Sci., 4.","DOI":"10.3389\/fpls.2013.00186"},{"key":"ref_36","doi-asserted-by":"crossref","first-page":"805","DOI":"10.1104\/pp.018853","article-title":"Hydrotropism Interacts with Gravitropism by Degrading Amyloplasts in Seedling Roots of Arabidopsis and Radish","volume":"132","author":"Takahashi","year":"2003","journal-title":"Plant Physiol."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"25","DOI":"10.3732\/ajb.1200419","article-title":"Molecular mechanisms of hydrotropism in seedling roots of Arabidopsis thaliana (Brassicaceae)","volume":"100","author":"Moriwaki","year":"2013","journal-title":"Am. J. Bot."},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"804","DOI":"10.1071\/FP12070","article-title":"Hydraulic lift promotes selective root foraging in nutrient-rich soil patches","volume":"39","author":"Prieto","year":"2012","journal-title":"Funct. Plant Biol."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"353","DOI":"10.1093\/treephys\/23.5.353","article-title":"Hydraulic redistribution by deep roots of a Chihuahuan Desert phreatophyte","volume":"23","author":"Hultine","year":"2003","journal-title":"Tree Physiol."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Blum, A. (2011). Plant Water Relations, Plant Stress and Plant Production. Plant Breeding for Water-Limited Environments, Springer.","DOI":"10.1007\/978-1-4419-7491-4"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"280","DOI":"10.1016\/S1369-5266(03)00035-9","article-title":"The role of nutrient availability in regulating root architecture","volume":"6","year":"2003","journal-title":"Curr. Opin. Plant Biol."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"655","DOI":"10.1046\/j.1365-313x.2001.01185.x","article-title":"ABA plays a central role in mediating the regulatory effects of nitrate on root branching in Arabidopsis","volume":"28","author":"Signora","year":"2001","journal-title":"Plant J."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"185","DOI":"10.1007\/s11104-005-6837-5","article-title":"Possible Involvement of Cytokinin in Nitrate-mediated Root Growth in Maize","volume":"277","author":"Tian","year":"2005","journal-title":"Plant Soil"},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"751","DOI":"10.1046\/j.1365-313X.2002.01251.x","article-title":"Nitrate and phosphate availability and distribution have different effects on root system architecture of Arabidopsis","volume":"29","author":"Linkohr","year":"2002","journal-title":"Plant J."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"1460","DOI":"10.1104\/pp.107.103788","article-title":"Phosphate Starvation Root Architecture and Anthocyanin Accumulation Responses Are Modulated by the Gibberellin-DELLA Signaling Pathway in Arabidopsis","volume":"145","author":"Jiang","year":"2007","journal-title":"Plant Physiol."},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"958","DOI":"10.2307\/2656994","article-title":"Plant growth and phosphorus accumulation of wild type and two root hair mutants of Arabidopsis thaliana (Brassicaceae)","volume":"87","author":"Bates","year":"2000","journal-title":"Am. J. Bot."},{"key":"ref_47","doi-asserted-by":"crossref","first-page":"603","DOI":"10.1016\/j.plantsci.2007.09.002","article-title":"Stressful \u201cmemories\u201d of plants: Evidence and possible mechanisms","volume":"173","author":"Bruce","year":"2007","journal-title":"Plant Sci."},{"key":"ref_48","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1016\/j.envexpbot.2010.10.020","article-title":"Do plants remember drought? Hints towards a drought-memory in grasses","volume":"71","author":"Walter","year":"2011","journal-title":"Environ. Exp. Bot."},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1016\/S0168-9452(98)00010-7","article-title":"Electrical signaling and gas exchange in maize plants of drying soil","volume":"132","author":"Fromm","year":"1998","journal-title":"Plant Sci."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"237","DOI":"10.1016\/S0168-9452(00)00378-2","article-title":"Electrical signal from root to shoot in Sorghum bicolor: Induction of leaf opening and evidence for fast extracellular propagation","volume":"160","author":"Mishra","year":"2001","journal-title":"Plant Sci."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"521","DOI":"10.1007\/s00500-013-1073-z","article-title":"Root growth model: A novel approach to numerical function optimization and simulation of plant root system","volume":"18","author":"Zhang","year":"2014","journal-title":"Soft Comput."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"60","DOI":"10.1177\/003754970107600201","article-title":"A new heuristic optimization algorithm: Harmony search","volume":"76","author":"Geem","year":"2001","journal-title":"Simulation"},{"key":"ref_53","unstructured":"Neapolitan, R., and Naimipour, K. (2010). Foundations of Algorithms, Jones & Bartlett Learning, LLC."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"361","DOI":"10.1007\/s11103-008-9380-y","article-title":"Plant hormones and nutrient signaling","volume":"69","author":"Rubio","year":"2009","journal-title":"Plant Mol. Biol."},{"key":"ref_55","doi-asserted-by":"crossref","first-page":"244","DOI":"10.1104\/pp.010934","article-title":"Phosphate Availability Alters Architecture and Causes Changes in Hormone Sensitivity in the Arabidopsis Root System","volume":"129","author":"Simpson","year":"2002","journal-title":"Plant Physiol."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"2061","DOI":"10.1104\/pp.105.060061","article-title":"A Role for Auxin Redistribution in the Responses of the Root System Architecture to Phosphate Starvation in Arabidopsis","volume":"138","author":"Nacry","year":"2005","journal-title":"Plant Physiol."},{"key":"ref_57","unstructured":"(2011). Siyavula: Life Sciences Grade 10, Connexions Rice University."},{"key":"ref_58","doi-asserted-by":"crossref","unstructured":"Vafaee, F., Turan, G., Nelson, P.C., and Berger-Wolf, T.Y. (2014, January 6\u201311). Balancing the Exploration and Exploitation in an Adaptive Diversity Guided Genetic Algorithm. Proceedings of the 2014 IEEE Congress on Evolutionary Computation (CEC), Beijing, China.","DOI":"10.1109\/CEC.2014.6900257"},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"680","DOI":"10.1109\/TSMCA.2009.2012436","article-title":"Optimal Contraction Theorem for Exploration-Exploitation Tradeoff in Search and Optimization","volume":"39","author":"Chen","year":"2009","journal-title":"IEEE Trans. Syst. Man Cybern. Part A Syst. Hum."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"2193","DOI":"10.1016\/j.physa.2011.12.004","article-title":"Roulette-wheel selection via stochastic acceptance","volume":"391","author":"Lipowski","year":"2012","journal-title":"Phys. A Stat. Mech. Its Appl."},{"key":"ref_61","unstructured":"Rudolph, G. (1997). Convergence Properties of Evolutionary Algorithms, Verlag Dr. Kovac."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"316","DOI":"10.1109\/TEVC.2015.2444793","article-title":"Average Convergence Rate of Evolutionary Algorithms","volume":"20","author":"He","year":"2016","journal-title":"IEEE Trans. Evol. Comput."},{"key":"ref_63","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. Glob. Optim."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"242","DOI":"10.1177\/003754979406200405","article-title":"Constrained optimization via genetic algorithms","volume":"62","author":"Homaifar","year":"1994","journal-title":"Simulation"},{"key":"ref_65","unstructured":"Kennedy, J., Kennedy, J.F., Eberhart, R.C., and Shi, Y. (2001). Swarm Intelligence, Morgan Kaufmann."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"108","DOI":"10.1016\/j.amc.2009.03.090","article-title":"A comparative study of Artificial Bee Colony algorithm","volume":"214","author":"Karaboga","year":"2009","journal-title":"Appl. Math. Comput."},{"key":"ref_67","unstructured":"Adorio, E.P., and Diliman, U. (2005). Mvf-Multivariate Test Functions Library in C for Unconstrained Global Optimization, University of the Philippines Diliman."},{"key":"ref_68","unstructured":"Gavana, A. (2016, April 27). Test Functions Index. Available online: http:\/\/infinity77.net\/global_optimization\/test_functions.html."},{"key":"ref_69","first-page":"150","article-title":"A literature survey of benchmark functions for global optimisation problems","volume":"4","author":"Jamil","year":"2013","journal-title":"Int. J. Math. Model. Numer. Optim."},{"key":"ref_70","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1002\/9780470640425.app1","article-title":"Appendix A: Test problems in optimization","volume":"1","author":"Yang","year":"2010","journal-title":"Eng. Optim."},{"key":"ref_71","doi-asserted-by":"crossref","unstructured":"Jula, A., Nilsaz, H., Sundararajan, E., and Othman, Z. (2014, January 27\u201329). A new dataset and benchmark for cloud computing service composition. Proceedings of the 2014 5th International Conference on Intelligent Systems, Modelling and Simulation, Langkawi, Malaysia.","DOI":"10.1109\/ISMS.2014.22"},{"key":"ref_72","doi-asserted-by":"crossref","unstructured":"Everitt, B.S. (2005). Cluster analysis of subjects, hierarchical methods. Encycl. Biostat., 2.","DOI":"10.1002\/0470011815.b2a13008"},{"key":"ref_73","doi-asserted-by":"crossref","first-page":"7","DOI":"10.1007\/BF01890115","article-title":"Efficient algorithms for agglomerative hierarchical clustering methods","volume":"1","author":"Day","year":"1984","journal-title":"J. Classif."},{"key":"ref_74","doi-asserted-by":"crossref","unstructured":"Cali\u0143ski, T. (2014). Dendrogram. Wiley Statsref Stat. Ref. Online.","DOI":"10.1002\/9781118445112.stat05624"},{"key":"ref_75","doi-asserted-by":"crossref","unstructured":"Salkind, N.J. (2010). Encyclopedia of Research Design. Encyclopedia of Research Design, SAGE Publications, Inc.","DOI":"10.4135\/9781412961288"},{"key":"ref_76","doi-asserted-by":"crossref","first-page":"74","DOI":"10.5395\/rde.2014.39.1.74","article-title":"Analysis of variance (ANOVA) comparing means of more than two groups","volume":"39","author":"Kim","year":"2014","journal-title":"Restor. Dent. Endod."},{"key":"ref_77","doi-asserted-by":"crossref","first-page":"143","DOI":"10.11613\/BM.2013.018","article-title":"The Chi-square test of independence","volume":"23","author":"McHugh","year":"2013","journal-title":"Biochem. Med."}],"container-title":["Symmetry"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2073-8994\/12\/12\/2025\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T10:42:07Z","timestamp":1760179327000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2073-8994\/12\/12\/2025"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,12,7]]},"references-count":77,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2020,12]]}},"alternative-id":["sym12122025"],"URL":"https:\/\/doi.org\/10.3390\/sym12122025","relation":{},"ISSN":["2073-8994"],"issn-type":[{"value":"2073-8994","type":"electronic"}],"subject":[],"published":{"date-parts":[[2020,12,7]]}}}