In order to control the systematic divergence among decision makers (DMs) and preserve the original decision preference, this paper proposes a novel decision information fusion framework under the hesitant fuzzy envir...
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In order to control the systematic divergence among decision makers (DMs) and preserve the original decision preference, this paper proposes a novel decision information fusion framework under the hesitant fuzzy environment. First, a maximum compactness-based normalization method is presented to normalize hesitant fuzzy elements (HFEs) as pretreatment of decision data. Second, prospect theory is introduced to assign the optimal aggregation weights to maximize the efficiency of the preference aggregation process, in which the expected consensus threshold is viewed as a reference point estimated through statistic inference to distinguish DMs' status. Third, an effective feedback mechanism is designed to improve group consensus, and the dichotomy algorithm is utilized to search optimal feedback weight to preserve original decision information. Finally, a case study and comparison analysis are illustrated to show the efficiency of the proposed hesitant fuzzy information fusion method.
Addition-min fuzzy relation inequalities were introduced for describing the quantitative relationship in the peer-to-peer (P2P) file sharing system. In order to reduce the network congress, the system manager has to m...
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Addition-min fuzzy relation inequalities were introduced for describing the quantitative relationship in the peer-to-peer (P2P) file sharing system. In order to reduce the network congress, the system manager has to minimize the variables in the addition-min fuzzy relation inequalities. The corresponding min-max programming has been established in the existing works. However in such model, all the variables are viewed equally. In this paper, considering the different important degrees of the variables, we propose and investigate the weighted min-max programming subject to the addition-min fuzzy relation inequalities. Due to the different objective function, the existing methods are no longer effective for our proposed problem. dichotomy algorithm has been developed in this paper for searching the approximate optimal solution of the weighted min-max programming. The feasibility and effectiveness of the dichotomy algorithm is illustrated by numerical example.
This work presents the calibration of a low-cost analog sun sensor essential for satellite attitude determination, focusing on measuring azimuth and elevation angles. A dedicated test bench including an optical table,...
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ISBN:
(纸本)9798350388497;9798350388480
This work presents the calibration of a low-cost analog sun sensor essential for satellite attitude determination, focusing on measuring azimuth and elevation angles. A dedicated test bench including an optical table, dark room, solar emulator, and rotating table was established to evaluate sensor performance under realistic conditions. The calibration employed the dichotomy method to address the complexities of a multi-input multi-output (MIMO) system, ensuring accurate modeling of sensor outputs against solar angles. Results demonstrated the algorithm's robustness, achieving precise angle identification even with measurement uncertainties. Additionally, an intuitive graphical interface was developed to facilitate the calibration process and enhance the efficiency. This work significantly advances the reliability and affordability of sun sensors in satellite attitude control systems.
As a three-way approximation of fuzzy sets, shadowed sets have attracted extensive attention in recent years. A fundamental issue in the process of constructing shadowed sets is the interpretation and determination of...
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As a three-way approximation of fuzzy sets, shadowed sets have attracted extensive attention in recent years. A fundamental issue in the process of constructing shadowed sets is the interpretation and determination of the threshold pair (alpha, beta), and the uncertainty consistency, that is, the consistency of fuzzy entropy. However, there may be a large fuzzy entropy loss between a fuzzy set and its corresponding game theoretic shadowed sets (GTSS), and the GTSS model is also accompanied by a large time cost when the precision of (alpha, beta) is improved. Therefore, the fuzzy-entropy-based GTSS (FeGTSS) is proposed in this article from the perspective of fuzzy entropy loss. First, based on the compromise principle of game theory, the fuzzy entropy loss of shadowed sets is analyzed in this article. Second, in the process of calculating (alpha, beta), the optimal game strategy is searched based on the dichotomy algorithm. Third, the FeGTSS model is extended and discussed based on the analysis of different data distribution types. Finally, the rationality and validity of the FeGTSS model are illustrated through instances and experimental analysis.
Here, we present an automatic data generation method which is fully computer-based for a variate X with an absolutely continuous probability density function ( pdf ) f exactly computable. The method uses computer-base...
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Here, we present an automatic data generation method which is fully computer-based for a variate X with an absolutely continuous probability density function ( pdf ) f exactly computable. The method uses computer-based on calculations of integrals (trapezoidal and/or the Monte-carlo method) for approximating the cumulative distribution function and next, the dichotomy algorithm to get the quantile function from which we obtain data from f . We apply the method to generate gig(a,b,c) data. The comparison with analogues, as in R Software is very successful. The method may work where the rejection method fails because of a lack of pdf bound which can be generated. The method might be slower but the area of more and more powerful computer is favorable to it. The implementation for gamma and/or gig laws in R codes are presented. Dans ce papier, nous proposons une méthode automatique de génération aléatoire de données basée sur l’évaluation des intégrales par la méthode trapezoidale ou par la méthode Monte-Carlo et l’algorithme de dichotomie pour le calcul des fonctions des quantiles. Cette méthode à été utilisée pour la génération de données gamma et gig.
Opportunistic spectrum access (OSA) is a key technique enabling the secondary users (SUs) in a cognitive radio (CR) network to transmit over the “spectrum holes” unoccupied by the primary users (PUs). In contrast to...
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ISBN:
(纸本)9781510802704
Opportunistic spectrum access (OSA) is a key technique enabling the secondary users (SUs) in a cognitive radio (CR) network to transmit over the “spectrum holes” unoccupied by the primary users (PUs). In contrast to OSA, with spectrum sharing (SS) is allowed to transmit regardless of the PU's on/off status, provided that the resulting interference to PU is kept below a predefined threshold. In this paper, we focus on the maximum interference temperature of the primary users for secondary users' spectrum access in spectrum sharing, which aims to get the minimum signal-to-noise ratio (SNR) of the PUs as quickly and precisely as possible. We propose a dichotomy algorithm with lower complexity and higher speed in contrast to the traditional full search algorithm. Numerous simulation results are provided to validate the proposed algorithm.
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