Yazar "Lotfi, F.H." seçeneğine göre listele

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    Introducing a trapezoidal interval type-2 fuzzy regression model
    (IOS Press, 2022) Mokhtari, M.; Allahviranloo, Tofigh; Behzadi, M.H.; Lotfi, F.H.
    The uncertainty is an important attribute about data that can arise from different sources including randomness and fuzziness, therefore in uncertain environments, especially, in modeling, planning, decision-making, and control under uncertainty, most data available contain some degree of fuzziness, randomness, or both, and at the same time, some of this data may be anomalous (outliers). In this regard, the new fuzzy regression approaches by creating a functional relationship between response and explanatory variables can provide efficient tools to explanation, prediction and possibly control of randomness, fuzziness, and outliers in the data obtained from uncertain environments. In the present study, we propose a new two-stage fuzzy linear regression model based on a new interval type-2 (IT2) fuzzy least absolute deviation (FLAD) method so that regression coefficients and dependent variables are trapezoidal IT2 fuzzy numbers and independent variables are crisp. In the first stage, to estimate the IT2 fuzzy regression coefficients and provide an initial model (by original dataset), we introduce two new distance measures for comparison of IT2 fuzzy numbers and propose a novel framework for solving fuzzy mathematical programming problems. In the second stage, we introduce a new procedure to determine the mild and extreme fuzzy outlier cutoffs and apply them to remove the outliers, and then provide the final model based on a clean dataset. Furthermore, to evaluate the performance of the proposed methodology, we introduce and employ suitable goodness of fit indices. Finally, to illustrate the theoretical results of the proposed method and explain how it can be used to derive the regression model with IT2 trapezoidal fuzzy data, as well as compare the performance of the proposed model with some well-known models using training data designed by Tanaka et al. [55], we provide two numerical examples. © 2022-IOS Press. All rights reserved.
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    New Approach for Solving Fully Interval-Value Fuzzy Transportation Problems
    (Springer Science and Business Media Deutschland GmbH, 2023) Ebrahimnejad, A.; Lotfi, F.H.; Allahviranloo, T.
    The transportation problem (TP) is one of the most broadly studied fields in the literature of linear programming problems used to a wide variety of practical applications. Conventional TPs generally assume that the values of transportation costs and the values of demand and supply are defined by real variables, though these values are unpredictable in TPs due to some uncontrollable factors. The present study formulates a TP when all parameters are interval-valued triangular fuzzy numbers and uses a novel optimization structure to find its optimal solution. The novelty of such an approach resides in requiring less computational effort compared to existing ones. The applicability of the proposed approach is illustrated through a numerical example. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.