Estimating manufacturing value-added via hybrid ANFIS-GA and PSO optimization: A macro-analysis of European OECD economies

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dc.authorid0000-0002-6591-2858
dc.authorid0000-0001-8755-5743
dc.contributor.authorÖzdemir, Mustafa
dc.contributor.authorÖzkul, Metin
dc.date.accessioned2026-07-14T12:20:37Z
dc.date.available2026-07-14T12:20:37Z
dc.date.issued2025
dc.departmentAÇÜ, Arhavi Meslek Yüksekokulu, Dış Ticaret Bölümü
dc.description.abstractIn recent years, artificial intelligence-based hybrid methods have gained increasing attention for addressing complex and nonlinear problems in engineering and economic systems. This study proposes an innovative approach to estimate manufacturing value-added at the macro level by integrating innovation, entrepreneurship, and environmental indicators. An Adaptive Neuro-Fuzzy Inference System (ANFIS) model is optimized using Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) to improve estimation accuracy. The proposed hybrid models are tested across different population sizes and benchmarked against the standard ANFIS model. Comparative performance evaluation reveals that the ANFIS-GA model with a population size of 25 outperforms other models, achieving the most consistent and accurate estimation results with R2= 0.9080, MAE= 0.1455, MSE= 0.0325, RMSE= 0.1801, and PBIAS= 0.7960. The findings demonstrate the robustness and applicability of the ANFIS-GA model for manufacturing value-added prediction, offering valuable insights for policy makers and industrial decision-makers in enhancing production performance and sustainable development strategies.
dc.identifier.doi10.1016/j.nxsust.2025.100241
dc.identifier.urihttps://hdl.handle.net/11494/6335
dc.identifier.volume7
dc.identifier.wosWOS:001651553300001
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.institutionauthorÖzdemir, Mustafa
dc.institutionauthorÖzkul, Metin
dc.institutionauthorid0000-0002-6591-2858
dc.institutionauthorid0000-0001-8755-5743
dc.language.isoen
dc.publisherELSEVIER
dc.relation.ispartofNEXT SUSTAINABILITY
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectManufacturing
dc.subjectValue added
dc.subjectInnovation
dc.subjectEntrepreneurship
dc.subjectEnvironment
dc.subjectANFIS-GA
dc.subjectANFIS-PSO
dc.titleEstimating manufacturing value-added via hybrid ANFIS-GA and PSO optimization: A macro-analysis of European OECD economies
dc.typeArticle

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