Başaran, Murat AlperSimonetti, Biagio2026-01-242026-01-24202197835408808443540268995978364215605297835403435619783540374190978354089483497835402537929783642147548978364212051035403888341434-9922https://doi.org/10.1007/978-3-030-61334-1_21https://hdl.handle.net/20.500.12868/4582The parameter estimation methods of fuzzy linear regression available in the literature have adapted several techniques ranging from mathematical programming to fuzzy least squares which is based on distance notion. Therefore, the literature is vast. However, researchers still try to look for a method that is expected to have estimated spreads as small as possible and good predictions. Each parameter estimation method proposed in the literature has treated fuzzy numbers based on how it implements the data. Namely, the proposed methods somehow restrict the usage of the fuzzy data. In this chapter, a novel method consisting of new notions and calculation procedures is proposed in order to find the parameter estimates of fuzzy linear regression. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.eninfo:eu-repo/semantics/closedAccessFuzzy arithmeticFuzzy identity matrixFuzzy inverse matrixFuzzy one numberFuzzy zero numberParameter estimation in fuzzy regressionBook Chapter10.1007/978-3-030-61334-1_214044214312-s2.0-85101094230Q3