3,950 research outputs found

    Multi-Dimensional Analysis of Poverty in Ghana Using Fuzzy Sets Theory

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    The paper studies the multidimensional aspects of poverty and living conditions in Ghana. The aim is to fill the vacuum that has been left by traditional uni-dimensional measures of deprivation based on poverty lines, exclusively estimated on the basis of monetary variables such as income or consumption expenditure. It combines monetary and non-monetary, and qualitative and quantitative indicators, including housing conditions, the possession of durable goods, equivalent disposable income, and equivalent expenditure, with a number of composite human welfare measures. The study employs the fuzzy-set theoretic framework to compare levels of deprivation in Ghana over time usig micro data from the last two rounds of the Ghana Living Standard Surveys (1991/1992 and 1998/1999). The estimation results of the membership functions, depicting the levels of deprivation for the various categories of deprivation indicators, show a composite deprivation degree of 0.2137 for the whole country in 1998/99 as compared to 0.2123 in 1991/92. This deprivation trend reveals that poverty levels hard scarcely changed in Ghana. In fact, it even rose slightly during the nineties, contrary to the uni-dimensional analytical GLSS 4 report of an overall broadly favourable trend in poverty in Ghana during the 1990s.Ghana, fuzzy set, multi-dimensional poverty, composite deprivation or poverty index

    Target threat assessment using fuzzy sets theory

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    The threat evaluation is significant component in target classification process and is significant in military and non military applications. Small errors or mistakes in threat evaluation and target classification especial in military applications can result in huge damage of life and property. Threat evaluation helps in case of weapon assignment, and intelligence sensor support system. It is very important factor to analyze the behavior of enemy tactics as well as our surveillance. This paper represented a precise description of the threat evaluation process using fuzzy sets theory. A review has been carried out regarding which parameters that have been suggested for threat value calculation. For the first time in this paper, eleven parameters are introduced for threat evaluation so that this parameters increase the accuracy in designed system. The implemented threat evaluation system has been applied to a synthetic air defense scenario and four real time dynamic air defense scenarios. The simulation results show the correctness, accuracy, reliability and minimum errors in designing of threat evaluation syste

    Fuzzy sets predict flexural strength and density of silicon nitride ceramics

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    In this work, we utilize fuzzy sets theory to evaluate and make predictions of flexural strength and density of NASA 6Y silicon nitride ceramic. Processing variables of milling time, sintering time, and sintering nitrogen pressure are used as an input to the fuzzy system. Flexural strength and density are the output parameters of the system. Data from 273 Si3N4 modulus of rupture bars tested at room temperature and 135 bars tested at 1370 C are used in this study. Generalized mean operator and Hamming distance are utilized to build the fuzzy predictive model. The maximum test error for density does not exceed 3.3 percent, and for flexural strength 7.1 percent, as compared with the errors of 1.72 percent and 11.34 percent obtained by using neural networks, respectively. These results demonstrate that fuzzy sets theory can be incorporated into the process of designing materials, such as ceramics, especially for assessing more complex relationships between the processing variables and parameters, like strength, which are governed by randomness of manufacturing processes

    Informational Paradigm, management of uncertainty and theoretical formalisms in the clustering framework: A review

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    Fifty years have gone by since the publication of the first paper on clustering based on fuzzy sets theory. In 1965, L.A. Zadeh had published “Fuzzy Sets” [335]. After only one year, the first effects of this seminal paper began to emerge, with the pioneering paper on clustering by Bellman, Kalaba, Zadeh [33], in which they proposed a prototypal of clustering algorithm based on the fuzzy sets theory

    Fuzzy systems and applications in innovation and sustainability

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    One of the main characteristics of humankind is the ability to interpret via natural language incomplete, imprecise, vague, subjective, fragmentary, or scarce information i.e. information in uncertainty and transform it to actions, reason and decision-making [9]. Fuzzy sets theory firstly introduced the treatment of such concepts in 1965 with the foremost influential paper "Fuzzy Sets" [29]. The groundbreaking standpoint of fuzzy systems allows the treatment of uncertain information with the utilization of a strict mathematical framework [8]. Ever since the publication of the pivotal paper from Zadeh, a plethora of contributions have shaped the fuzzy sets theory scope and applications, from developments in engineering, mathematics, computer, decision, life, physical, health, social sciences and humanities [17 (...

    Risk quantification of an option portfolio through the introduction of the fuzzy Black-Scholes formula

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    Treballs Finals del Màster de Ciències Actuarials i Financeres, Facultat d'Economia i Empresa, Universitat de Barcelona, Curs: 2018-2019, Tutor: Ana María Gil LafuenteThe aim of this thesis is to quantify the market risk of an option portfolio under uncertainty. The fuzzy sets theory is introduced to model the parameters of the Black-Scholes option-pricing formula. Since the option price is calculated through the fuzzy Black-Scholes formula, we can compute the Value-at-Risk as a fuzzy number. By doing so, we aim to capture extra information that is lost in traditional models given the uncertainty derived from the fluctuations of financial markets. Finally, we want to conclude whether the introduction of the fuzzy sets theory is useful in order to improve the risk management

    Fuzzy cellular model for on-line traffic simulation

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    This paper introduces a fuzzy cellular model of road traffic that was intended for on-line applications in traffic control. The presented model uses fuzzy sets theory to deal with uncertainty of both input data and simulation results. Vehicles are modelled individually, thus various classes of them can be taken into consideration. In the proposed approach, all parameters of vehicles are described by means of fuzzy numbers. The model was implemented in a simulation of vehicles queue discharge process. Changes of the queue length were analysed in this experiment and compared to the results of NaSch cellular automata model.Comment: The original publication is available at http://www.springerlink.co

    Оптимизация систем терморегулирования космических аппаратов с использованием нечетких множеств

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    It was proposed to carry out a thermal control system of spacecrafts optimization using fuzzy sets theory, that allowing to provide a global efficiency factor forming on the base of particular efficiency factors in the case of them fuzzy setting
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