Entropy is a measurement of the degree of uncertainty. Meanentropy method can be used for modeling the choice among uncertain outcomes. In this paper, we consider the portfolio selection problem under the assumption that security returns are characterized by type-2 fuzzy variables. Since the expectation and entropy of type-2 fuzzy variables haven’t been well defined, type-2 fuzzy variables need...

In this paper, we propose the use of the Maximum Entropy approach for the task of automatic image annotation. Given labeled training data, Maximum Entropy is a statistical technique which allows one to predict the probability of a label given test data. The techniques allow for relationships between features to be effectively captured. and has been successfully applied to a number of language t...

In this paper we apply entropy in transportation model using maximum entropy method introduced by Shannon. A transportation model for trip distribution describes the number of trips between two zones where generalized cost is usually some combination of the travel, the distance traveled and the actual monetary cots. If the transportation model is of the power form and if the total number of ori...

the estimate of entropy (sample entropy), has been introduced by vasicek (1976), for the first time. in this paper, we provide an estimate of entropy of order statistics, that is the extention of the entropy estimate. then we present an application of the entropy estimate of order statistics as a test statistic for symmetry of distribution versus skewness. the proposed test has been compared wi...

the solubility of naproxen in binary mixtures of polyethylene glycol 200 (peg 200) + water at the temperature range from 298.0 k to 318.0 k were reported. the combinations of jouyban-acree model + van’t hoff and jouyban-acree model + partial solubility parameters were used to predict the solubility of naproxen in peg 200 + water mixtures at different temperatures. combination of jouyban-acree m...

In this paper, a maximum likelihood estimation and a minimum entropy estimation for the expected value and variance of normal fuzzy variable are discussed within the framework of credibility theory. As an application, a credibilistic portfolio selection model is proposed, which is an improvement over the traditional models as it only needs the predicted values on the security returns instead of...

Based on the Markov model and the basic theory of information entropy, this paper puts forward a new method for optimizing the location of observation points in order to obtain more information from limited geological investigation. According to the existing data from observation points data, classification of tunnel geological lithology was performed, and various lithology distribution were de...

In this paper we develop a maximum-entropy based method for annotating spontaneous conversational speech with punctuation. The goal of this task is to make automatic transcriptions more readable by humans, and to render them into a form that is useful for subsequent natural language processing and discourse analysis. Our basic approach is to view the insertion of punctuation as a form of taggin...

Yager’s entropy was proposed to compute the information of fuzzy indiscernibility relation. In this paper we present a novel interpretation of Yager’s entropy in discernibility power of a relation point of view. Then some basic definitions in Shannon’s information theory are generalized based on Yager’s entropy. We introduce joint entropy, conditional entropy, mutual information and relative en...