Results 11 to 20 of about 7,576 (227)
Hybrid Metaheuristics Using Rough Sets for QoS-Aware Service Composition
IEEE Access, 2022 Quality of Service (QoS)-aware service composition plays an increasingly important role in various computational paradigms and delivery models, predominantly cloud computing.
Hadi Naghavipour +4 more
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Mathematics, 2021 The rough Heston model is a form of a stochastic Volterra equation, which was proposed to model stock price volatility. It captures some important qualities that can be observed in the financial market—highly endogenous, statistical arbitrages prevention,
Siow Woon Jeng, Adem Kiliçman
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On I-statistically rough convergence
Publications de l'Institut Mathematique, 2019 We introduce rough I-statistical convergence as an extension of rough convergence. We define the set of rough I-statistical limit points of a sequence and analyze the results with proofs.
Savaş, Ekrem +2 more
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Rough statistical convergence on triple sequences [PDF]
Proyecciones (Antofagasta), 2017 In this paper, using the concept of natural density, we introduce the notion of rough statistical convergence of triple sequences. We define the set of rough statistical limit points of a triple sequence and obtain rough statistical convergence criteria associated with this set.
Debnath, Shyamal, Subramanian, N.
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On Generalized Difference Rough Ideal Statistical Convergence in Neutrosophic Normed Spaces [PDF]
Neutrosophic Sets and SystemsThis article’s main goal is to provide and investigate a novel statistical convergence generalisation for generalized difference sequences in Neutrosophic Normed Spaces (NNS) called rough ideal statistical convergence.
Manpreet Kaur, Meenakshi Chawla
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On deferred I-statistical rough convergence of difference sequences in neutrosophic normed spaces [PDF]
Neutrosophic Sets and SystemsIn this study, using the concepts of deferred density and the notion of the ideal I, we extend the idea of rough convergence by introducing the notion of deferred I–statistical rough convergence via difference operators in the framework of neutrosophic ...
Mukhtar Ahmad +2 more
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IEEE Access, 2019 It is very interesting and important to determine the function model for remote-sensing data. The existing statistical and artificial intelligence models still have some defects.
Changan Yuan +4 more
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Reliability problem of extreme value statistical inference for hydrology and meteorology
Shui kexue jinzhan, 2012 This paper discusses the unreliability of extreme value statistical inference,its presentation,causes and ways of improving the reliability,practical methods and reliability evaluation.It advances the possibility of applying the phenomenon of super ...
DONG Shuang-lin
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Rough statistical convergence in neutrosophic normed spaces
Annals of Communications in Mathematics, 2023 Neutrosophic normed spaces, one of the recent hot issues in mathematics, are covered in this paper. The Neutrosophic approach is based on the idea that the degree of uncertainty should be taken into consideration and that it is insufficient to categorise problems in daily life as either right or wrong.
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A Hybrid Probabilistic-Neutrosophic Adaptive Convergence Model for Analyzing Innovative Performance of Agricultural Technology Enterprises in the Digital Economy [PDF]
Neutrosophic Sets and SystemsThis paper introduces a novel mathematical framework that integrates hybrid probabilistic-neutrosophic logic with adaptive rough ideal statistical convergence (AR-I st) to model and analyze the dynamic performance of innovative agricultural technology ...
Hongyan Xie
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