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In heterogeneous wireless networks, an important task for mobile terminals is network selection. A main challenge of network selection is to represent the uncertainty. Concerning this challenge, we investigate intuitionistic fuzzy multi-attribute decision making (IFMADM) and discuss its application in network selection. Objectively determining attribute weights and aggregating intuitionistic fuzzy...
The model is based on the criteria of cost-effectiveness and information uncertainty. The created model has a fundamental difference from the current classical economic-mathematical models. It is proposed to use the mathematical expressions of the information entropy determination of two states of the system: operable and non-operable as the constraints. These expressions are the constraints imposed...
Leakage of personal information is a problem with free usage of social networks. In the face of enhanced connectivity reaching out to friends of friends, it is becoming increasingly difficult to prevent unwanted users from seeing personal posts. Various automated means of abatement measures are being taken in this regard and the present work is an attempt in that direction. Conventionally, the trust...
This article considers several measures of uncertainty, which are based on entropy approach by using basic belief assignment and belief, plausibility or pignistic probability functions. These measures are used to identify different types of conflict arising from the interaction of focal elements inside the group of evidence, and allow to estimate the quality of the evidence. The interrelation between...
For many decision making problems, all the possible alternatives are treated equally before one find the most desirable alternative. But, it is a little unreasonable if all alternatives are treated equally. So, in this paper by taking the aggregation operator into account, the weights of criteria can be determined successfully. There in to, the parameters for aggregation operator are the decision...
Image classification is a hot topic of pattern recognition in computer vision. In order to achieve high accuracy of classification, a certain amount of high quality pictures are needed. As a matter of fact, high quality pictures are scarce. Active learning can solve such a problem. Label dependences play an important role in multi-label active learning for image classification. The interdependences...
Comprehensive evaluation is an important part of systems engineering but its evaluation results remains uncertainty. The chief aim of this paper is to develop a novel model which could be used to obtain the drought degree reasonably and accurately. It requires a great deal of further research effort in the systems evaluation because of the uncertainty which is regarded in terms of information entropy...
Aim of document similarity is to retrieve the list of ranked documents based on a query document. In the literature, it has been shown that document similarity method first compute similarity scores between the query and the documents based on a score function. Thereafter, documents are ranked according to their similarity scores. In the literature, TextTiling algorithm shown was basically done in...
The article shows a technique to quantify information within the structure of a technical system. The structure indicators are accepted as probability states of the system elements that are differentiated into two opposite states according to a qualitative attribute. The author gives mathematical expressions to present calculation aimed at quantification of informational entropy. The technique is...
In this paper, we discover a novel approach for defining information transfer in a linear network dynamical system. We provide entropy based characterization of the information transfer where the information transfer from state x to state y is measured by the amount of entropy/uncertainty that is transferred from state x to y over one time step. Our proposed definition of information transfer is based...
The methods of constructing shadowed sets have been developed to conserve the amount of uncertainty for fuzzy sets. The shadowed sets designed by such methods usually maintain one type of uncertainty for fuzzy sets. Moreover, such techniques are considered inappropriate for higher types of fuzzy sets. This paper proposes a new approach for inducing shadowed sets from intuitionistic fuzzy numbers....
In the light of the parameters interrelated characteristics in the process of chaos phase space reconstruction, this paper proposed a new way to determine embedding dimension and delay time simultaneously, that is, symbolic analysis-based multi-component conditional entropy method. Conditional entropy was introduced to characterize information increment and served as the measurement of complexity...
Measurements of various properties of the process models in the last few years become relatively widely explored area. These are properties such as uncertainty, complexity, readability or cohesion of process models. Quantification of these properties can provide better insight in term of, for instance, user-friendliness, predictability, clarity, etc. of the process model. The aim of this work is to...
Cryptography is used to protect information content communicated over a network from being accessed by adversaries. This is achieved by transforming (encrypting) plain text before transmission in such a way so that its contents can only be disclosed upon application of a reverse transformation (decryption). Transformations often involve some key used in the process. This paper focuses on estimating...
Although many state-of-the-art visual SLAM algorithms use keyframes to help alleviate the computational requirements of performing online bundle adjustment, little consideration is taken for specific keyframe selection. In this work, we propose two entropy based methods which aim to insert keyframes that will directly improve the system's ability to localize. The first approach inserts keyframes based...
selecting relevant features for machine learning modeling improves the performance of the learning methods. Mutual information (MI) is known to be used as relevant criterion for selecting feature subsets from input dataset with a nonlinear relationship to the predicting attribute. However, mutual information estimator suffers the following limitation; it depends on smoothing parameters, the feature...
Dynamics of non-stationary processes that follow the MaxEnt principle for differential entropy is considered. A set of equations describing the dynamics of probability density function (pdf) for such processes is proposed. Equations are derived based on the Speed-Gradient principle originated in the control theory. The uniqueness of the limit pdf and asymptotic convergence of pdf are examined under...
Information theory concept was created by Claude Shannon in 1948. Entropy i.e. uncertainty measure informs how much information is there in an event. The more uncertain the event the more information it gives. In order to resolve this uncertainty, software testing is done and by running it, knowledge of a software system is gained. In this paper, a benchmark for modeling of bug prediction using different...
With the development of web technologies, there is lots of information on the web. For effective web searching, the recommendation systems appear on the web. The recommendation systems provide customized information for the personal users. The conventional processes of the recommendation are generally based on the user preferences for the items. This leads to the cold-start problems for new items...
Data Assimilation is central to Dynamic Data Driven Applications (DDDAS). The limitations of current techniques in the presence of nonlinearity and dimensionality can, in principle, be ameliorated by effective non-Gaussian high-dimensional inference in many areas within DDDAS, but particularly environmental applications. This paper presents an inference algorithm based on maximization of a quadratic...
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