Strict intuitionistic fuzzy distance/similarity measures based on Jensen-Shannon divergence

Information Sciences, Год журнала: 2024, Номер 661, С. 120144 - 120144

Опубликована: Янв. 18, 2024

Язык: Английский

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Location selection for offshore wind power station using interval-valued intuitionistic fuzzy distance measure-RANCOM-WISP method

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Фев. 27, 2024

Abstract The development opportunities and high-performance capacity of offshore wind energy project depends on the selection suitable power station (OWPS) location. present study aims to introduce a decision-making model for assessing locations OWPS from multiple criteria uncertainty perspectives. In this regard, concept interval-valued intuitionistic fuzzy set (IVIFS) is utilized express uncertain information. To quantify degree difference between IVIFSs, an improved distance measure proposed further deriving objective weights criteria. Numerical examples are discussed illustrate usefulness introduced IVIF-distance measure. RANking COMparison (RANCOM) based information presented determine subjective With combination criteria, integrated weighting tool find numeric under IVIFS environment. Further, hybrid Weighted Sum Product (WISP) approach developed prioritize This combines benefits two normalization tools four utility measures, which approves effect beneficial non-beneficial by means weighted sum product measures. applied location problem Gujarat, India. Sensitivity comparative analyses confirm robustness stability WISP approach. provides innovative decision analysis framework, makes significant contribution assessment

Язык: Английский

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Data-driven MPPT techniques for optimizing vehicular fuel cell performance in hybrid DC microgrid

International Journal of Hydrogen Energy, Год журнала: 2024, Номер 79, С. 715 - 727

Опубликована: Июль 10, 2024

Язык: Английский

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Intuitionistic fuzzy time series forecasting method based on dendrite neuron model and exponential smoothing

Granular Computing, Год журнала: 2024, Номер 9(2)

Опубликована: Апрель 25, 2024

Abstract Methods based on artificial neural networks for intuitionistic fuzzy time series forecasting can produce successful results. In the literature, exponential smoothing methods are hybridised with due to their simple and efficient structures improve performance. The contribution of this paper is propose a new approach combining series. study, algorithm dendrite neuron model proposed modelling fuzzification stage method, c-means method used. modular using two separate grey wolf optimisation used estimate all parameters method. performance applied four different random obtained Index Coin Market Cap compared some other methods. As result analyses, it concluded that has better results than

Язык: Английский

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A Resarch on the Factors Affecting the Outcomes of Child Abuse Cases Using Machine Learning Methods

Turkish Journal of Forecasting, Год журнала: 2025, Номер 9(1), С. 17 - 29

Опубликована: Март 24, 2025

Modern information technology makes it possible to collect and store scientific social research data. Some statistical methods can provide quite reliable results when the necessary assumptions are met in uncovering existing or hidden relationships between However, since data collected from real life often do not meet these assumptions, mining that require fewer be applied flexible complex sets have been developed for prediction. The use of machine learning methods, which include techniques, process produce meaningful has become widespread recent years. In this study, techniques such as CHAID algorithm, an application decision trees, support vector machines, were compared with logistic regression analysis method. study’s sample consists 61 child abuse cases UCIM Saadet Öğretmen Association Struggling Child Abuse requested participation. dependent variable study is whether defendant received a sentence at end trial, while independent variables five identified by leveraging expert (lawyer) opinions. As result, was found algorithm machines provided more accurate classification.

Язык: Английский

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HFS-based computational method for weighted fuzzy time series forecasting model using techniques of adaptive radius clustering and grey wolf optimization

Granular Computing, Год журнала: 2023, Номер 9(1)

Опубликована: Дек. 27, 2023

Язык: Английский

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Group decision making based on linguistic interval-valued Atanassov intuitionistic fuzzy Yager weighted arithmetic aggregation operator of linguistic interval-valued Atanassov intuitionistic fuzzy numbers

Information Sciences, Год журнала: 2024, Номер 670, С. 120517 - 120517

Опубликована: Март 26, 2024

Язык: Английский

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Fermatean fuzzy distance and Sugeno–Weber operators-based SPC-MARCOS approach for sustainable supplier evaluation in the healthcare supply chain

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Ноя. 9, 2024

The present work proposes a new decision support tool for assessing the sustainable suppliers in healthcare supply chain. For this purpose, classical Measurement of Alternatives and Ranking according to Compromise Solution (MARCOS) model is integrated with Sugeno-Weber weighted averaging operators, modified symmetry point criterion (SPC) model, rank sum (RS) Fermatean fuzzy sets (FFSs), named as 'FF-SPC-RS-MARCOS' framework. developed firstly determines experts' weights through RS model. Second, novel operators are introduced combine opinions. Third, unified weighting procedure presented based on combination SPC approach objective weight method subjective attributes. To aim, distance measure FFSs further applied compute between aggregated numbers value an attribute approach. Further, hybrid FF-SPC-RS-MARCOS proposed tackle decision-making problems setting. elucidate efficacy method, it case study supplier selection problem paper conducts sensitivity investigation comparison existent approaches test stability robustness ranking outcomes. This shows how MARCOS models can be used prioritize alternative provides methodology, which help practitioners academics evaluate uncertain information also employed other areas facing similar types problems.

Язык: Английский

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A hybrid deep recurrent artificial neural network with a simple exponential smoothing feedback mechanism

Information Sciences, Год журнала: 2024, Номер 686, С. 121356 - 121356

Опубликована: Авг. 23, 2024

Язык: Английский

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Explainability of Machine Learning Using Shapley Additive exPlanations (SHAP): CatBoost, XGBoost and LightGBM for Total Dissolved Gas Prediction

Studies in big data, Год журнала: 2024, Номер unknown, С. 1 - 25

Опубликована: Янв. 1, 2024

Язык: Английский

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