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To increase the learning effectiveness and willingness of students became the most important issue for the Universities in Taiwan. Therefore, we must find the important factors of the learning effectiveness to improve the learn willingness of students. However, it is not easy to measure the learning effectiveness because the subjective judgment of evaluators and the attributes of factors are always...
Fuzzy clustering is an important problem which is the subject of active research in several real world applications. Fuzzy c-means (FCM) algorithm is one of the most popular fuzzy clustering techniques because it is efficient, straightforward, and easy to implement. However FCM is sensitive to initialization and is easily trapped in local optima. Particle swarm optimization (PSO) is a stochastic global...
In recent decade, DRM (digital rights management) has focused on security techniques for solving the issues as the malicious copy, free dissemination and unrestricted abuse of digital contents or assets. Whereas some increasingly enhanced security policies, which were implemented at contents provider-side or user-side, have not brought about optimal utilities for participants in the contents value...
To deal with the estimation problem for systems subject to constraints while the corresponding noise processes are not completely known, the adaptive constraint-filtering method is proposed in this paper. The constraint-filtering method developed previously can accommodate the constraint in the filtering process for a nonlinear dynamic system. However, the assumption that the modelling noise and the...
Trustworthy software has attracted increasing concern both in academia and industry. How to effectively evaluate the trustworthiness is becoming a closed question. This paper models the software trustworthiness evaluation (STE) problem as a multi-criteria decision-making (MCDM) problem, and proposes both an evaluation framework and a practical approach to evaluate the software trustworthiness based...
The concept of (classical) complete preorder can be characterized in several ways. In previous works we have studied whether complete fuzzy preorders can be characterized by the same properties as in the crisp case. We have proven that this is not usually the case. We have studied five possible characterizations and we have proven that only one still characterizes a fuzzy preorder. In this work we...
Relative position of object description are widely used in event understanding and computer vision tasks especially in object recognition. Use of low level features cannot give satisfactory results when high level concepts is not easily expressible in low level contents. Mostly researchers are concentrating on spatio- temporal relationship between objects or regions of an object in images. Object...
The aim of the present work is to provide a reliable decision-making tool to enterprise managers that helps them to understand the available acquired competence resources network and to take the right decision to promote and ameliorate this network. For that purpose, a novel competence evaluation approach based on a fuzzy linguistic information model, named the 2-tuple linguistic representation model,...
An expert teacher's assessment of new skills can achieve a suitable total score without having to consider to every sub-item. In addition, while completing a skill assessment there are the formal weighting arrangements of every sub-item. This study proposed two new methods using the technique for fuzzy decomposition analysis, which arranges weightings, quickly and exactly. The maximum solution of...
Intelligent transportation systems (ITS) have received increasing attention in academy and in industry. Being able to handle uncertainties and complexity, fuzzy systems are applied in vast areas of real life including intelligent transportation systems. In this paper, a comprehensive survey of the research on the application of fuzzy systems in various traffic control engineering domains and its surroundings...
The methods estimating vulnerability of perimeter security systems are developed in the current study. Appropriate estimations are based on the fuzzy inference methods of intruder undetection risks on security zones set in territory's perimeter.
Vendor selection is a strategic issue in supply chain management for any organization to identify the right supplier. Such selection in most cases is based on the analysis of some specific criteria. Most of the researches so far concentrate on multi-criteria decision-making analysis. Though many approaches have been proposed, analytic hierarchy process (AHP) is the most well known as it can deal with...
The typical algorithm of text clustering is a ldquoHard Partitionrdquo one, Actually, Chinese text is better to treat with ldquoSoft Partitionrdquo for its diversity and largeness. The fuzzy-set theory supply a powerful analyzing tool to this ldquoSoft partitionrdquo. Traditional fuzzy text clustering methods mostly are getting the fuzzy equivalent matrix or fuzzy division by iterating the matrix...
In recent years, more and more teachers and learners have used e-learning system as the site to teach and study. Therefore, how to improve the efficiency in e-learning system has become a very important topic. This research combines Hopfield-Tank neural network and fuzzy ranking theories to analyze the learning efficiency and the useful nodes in learning path. After that, the researcher can improve...
This paper proposes a distributed wireless sensor network (WSN) data stream clustering algorithm to minimize sensor nodes energy consumption and consequently extend the network lifetime. The paper follows the strategy of trading-off communication for computation through distributed clustering and successive transmission of local clusters. We present an energy efficient algorithm we developed, subtractive...
The convergence theory not only is a significantly basic theory of fuzzy topology and fuzzy analysis but also has wide applications in fuzzy inference and some other aspects. In this paper we introduce the notions of fuzzy beta-upper limit, fuzzy beta-lower limit and the fuzzy beta-convergent nets of fuzzy sets. We also study the properties of fuzzy beta-upper limit, fuzzy beta-lower limit and the...
This paper introduces a method of learning kernel by fuzzy equivalence relation (FER) based on prior knowledge. Firstly, prior knowledge is represented through fuzzy membership functions and fuzzy inference rules. Consequently features of prior knowledge are obtained by proper inference methods. Secondly, the learning rules of FER-kernel are obtained in terms of FER semantic interpretation and fuzzy...
A kind of unrelated parallel machines scheduling problem with fuzzy due dates was discussed. The memberships of fuzzy due dates denoted the grades of satisfaction of decision-maker with respect to completion times with jobs. Objectives of scheduling is to maximize the minimum grade of satisfaction while makespan is minimized in the meantime. Niched Pareto genetic algorithm (NPGA) was employed to search...
Fuzzy description logics are a family of logics which allow the representation of (and the reasoning within) structured knowledge affected by uncertainty and vagueness. A well studied solution is to extend description logics with fuzzy sets theory. To solve implication problems in this kind of fuzzy description logics, Boolean lattice based fuzzy description logics is revisited. This paper shows that...
Based on random fuzzy theory, this paper presents a new class of two-stage random fuzzy programming model, and gives three solution concepts, which are wait-and-see solution, here and now solution and expected value solution. Since the value of information and uncertainties plays an important role in the studies of uncertainty optimization problem, this paper gives two optimal indexes based on the...
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