İnce, TürkerVuruşkan A.Bulgun E.Güzeliş C.2023-06-162023-06-1620139.78E+12https://doi.org/10.1109/SIU.2013.6531426https://hdl.handle.net/20.500.14365/35962013 21st Signal Processing and Communications Applications Conference, SIU 2013 -- 24 April 2013 through 26 April 2013 -- Haspolat -- 98109In this study, we present the development of an intelligent system solution for fashion style selection for various female body shapes. The proposed intelligent system combines binary genetic algorithm (GA) or binary version of the particle swarm optimization (PSO) with PSO-trained artificial neural network. The former is used to search the solution space for the optimal design parameters corresponding to a best fit for the desired target, and the task of the latter is to evaluate fitness (goodness) of each evolved new fashion style. With the goal of creating natural aesthetic relationship between the shape of the body and the shape of the garment for fashion styling, combinations of upper body related and lower body related garment pieces together with detailed attribute categories were created as a knowledge base. The encouraging results of preliminary experiments demonstrate the feasibility of applying intelligent systems to fashion styling. © 2013 IEEE.trinfo:eu-repo/semantics/closedAccessFemale body shapesGarment designGenetic algorithmIntelligent systemsParticle swarm optimizationBinary genetic algorithmBody shapesFashion stylesGarment designKnowledge baseOptimal design parametersSolution spaceUpper bodiesGenetic algorithmsKnowledge based systemsNeural networksParticle swarm optimization (PSO)Signal processingIntelligent systemsConference Object10.1109/SIU.2013.65314262-s2.0-84880891905