Research Article ANovelApproachofComplexDualHesitantFuzzySetsandTheir ApplicationsinPatternRecognitionandMedicalDiagnosis UbaidUrRehman , 1 TahirMahmood , 1 ZeeshanAli , 1 andThammaratPanityakul 2 1 Department of Mathematics and Statistics, International Islamic University Islamabad, Islamabad, Pakistan 2 Division of Computational Science, Faculty of Science, Prince of Songkla University, Hat Yai, Songkhla 90110, ailand CorrespondenceshouldbeaddressedtoammaratPanityakul;thammarat.p@psu.ac.th Received 14 October 2020; Revised 10 November 2020; Accepted 28 November 2020; Published 28 April 2021 AcademicEditor:AhmedMostafaKhalil Copyright©2021UbaidUrRehmanetal.isisanopenaccessarticledistributedundertheCreativeCommonsAttribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Complexdualhesitantfuzzyset(CDHFS)isanassortmentofcomplexfuzzyset(CFS)anddualhesitantfuzzyset(DHFS).Inthis manuscript, the notion of the CDHFS is explored and its operational laws are discussed. e new methodology of the complex interval-valueddualhesitantfuzzyset(CIvDHFS)anditsnecessarylawsareintroducedandarealsodefensiblewiththehelpof examples.Further,theantilogarithmicandwith-outexponential-basedsimilaritymeasures,generalizedsimilaritymeasures,and theirimportantcharacteristicsarealsodeveloped.esesimilaritymeasuresareappliedintheenvironmentofpatternrecognition and medical diagnosis to evaluate the proficiency and feasibility of the established measures. We also solved some numerical examplesusingtheestablishedmeasurestoexaminethereliabilityandvalidityoftheproposedmeasuresbycomparingthesewith existingmeasures.Tostrengthentheproposedstudy,thecomparativeanalysisismadeanditisconferredthattheproposedstudy is much more superior to the existing studies. 1.Introduction Zadeh [1] presented the theory of fuzzy sets (FSs), which containthegradeoftruthbelongingtounitinterval.But,in some cases, the theory of FSs has been failed. For instance, when a decision-maker faced information in the form of truth and falsity grades, then the FSs are not able to cope withit.Inreality,thesesetshavegivendifferentapproaches toallottheparticipationdegreeorthenonmembershiplevel of a component to a given set portrayed by various prop- erties. IFSs [2], otherwise called IVFSs from a numerical perspective, can be demonstrated with two capacities that characterize a stretch to mirror some vulnerability on the enrollment work of the components. IVFSs are the specu- lationofFSsandcandemonstratevulnerabilityfortheneed ofdata,inwhichaclosedsubintervalof[0,1]isrelegatedto the participation degree. Atanassov and Gargov [3] dem- onstratedthatIFSsandIVFSsareequipollentspeculationsof FSs and proposed the thought of IVIFS, which has been examined and utilized broadly [4–8]. T2FSs,depictedbyenrollmentworkthatisportrayedby more boundaries, grant the fuzzy enrollment as a fuzzy set improving the demonstrating ability compared to the original one. Scientifically, IFSs can be viewed as a specific instanceofT2FSs,wheretheparticipant’sworkrestoresalot offreshstretches.InspiteofthewideusesofT2FSs[9–12], they experience issues in building up the optional enroll- ment capacities and troubles in control [13–15]. FMSs are also the extension of the FSs, which contains the grade of truthintheformofthefinitesubsetoftheunitinterval.Note thatinspiteofthefactthatthehighlightsofFMSspermitthe application to data recovery on the internet, where a web index recovers different events of the same subjects with conceivable various degrees of significance [16], they have issues with the fundamental tasks, for example, the defini- tions for association and crossing point, which do not sum uptheonesforFSs.Rickard[17]gaveanelectivedefinition thatunderlinesthevalueofacommutativepropertybetween a set activity and an α-cut, settling this issue. HFSs were initiallypresentedbyTorra[4].etheoryofhesitantfuzzy Hindawi Journal of Mathematics Volume 2021, Article ID 6611782, 31 pages https://doi.org/10.1155/2021/6611782