Results 261 to 270 of about 224,996 (312)
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2020
The description of a physical system requires the knowledge of some information, for example the prediction of the motion of a point particle in classical mechanics requires the knowledge of its initial position and momentum besides, of course, the system of forces acting upon it. In the case of a great quantity of particles, i.e.
Vito Dario Camiola +2 more
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The description of a physical system requires the knowledge of some information, for example the prediction of the motion of a point particle in classical mechanics requires the knowledge of its initial position and momentum besides, of course, the system of forces acting upon it. In the case of a great quantity of particles, i.e.
Vito Dario Camiola +2 more
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Maximum entropy principle revisited
Continuum Mechanics and Thermodynamics, 1998The authors study the effect of the maximum entropy principle (MEP) on the thermodynamic behaviour of gases. The MEP relies on the kinetic theory of gases, and yields local constitutive equations of extended thermodynamics. There are two extreme cases in the kinetic theory: dominance of particle interactions, and free flight.
Kunik, Matthias, Dreyer, Wolfgang
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1997
The concept of information can be successfully utilized for the adaptation of a probability distribution to empirical data. In order to proceed to the formulation of the corresponding principle, let us first recall the expression for the empirical probability density for the case when all the samples are distinct $$fe\left( x \right) = \frac{1}{N ...
Igor Grabec, Wolfgang Sachse
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The concept of information can be successfully utilized for the adaptation of a probability distribution to empirical data. In order to proceed to the formulation of the corresponding principle, let us first recall the expression for the empirical probability density for the case when all the samples are distinct $$fe\left( x \right) = \frac{1}{N ...
Igor Grabec, Wolfgang Sachse
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The generalized maximum entropy principle
IEEE Transactions on Systems, Man, and Cybernetics, 1989Generalizations of the maximum entropy principle (MEP) of E.T. Jaynes (1957) and the minimum discrimination information principle (MDIP) of S. Kullback (1959) are described. The generalizations have been achieved by enunciating the entropy maximization postulate and examining its consequences.
H.K. Kesavan, J.N. Kapur
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MAXIMUM ENTROPY PRINCIPLE FOR TRANSPORTATION
AIP Conference Proceedings, 2008In this work we deal with modeling of the transportation phenomenon for use in the transportation planning process and policy‐impact studies. The model developed is based on the dependence concept, i.e., the notion that the probability of a trip starting at origin i is dependent on the probability of a trip ending at destination j given that the ...
F. Bilich +4 more
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1989
In Section 1.1, we alluded to the principle that titles this chapter. The idea of this principle, as we said there, is to assign probabilities in such a way that the resulting distribution contains no more information than is inherent in the data. The first attempt to do this was by Laplace and was called the “Principle of Insufficient Reason.” This ...
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In Section 1.1, we alluded to the principle that titles this chapter. The idea of this principle, as we said there, is to assign probabilities in such a way that the resulting distribution contains no more information than is inherent in the data. The first attempt to do this was by Laplace and was called the “Principle of Insufficient Reason.” This ...
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Analysis of the maximum entropy principle ?debate?
Foundations of Physics, 1978Jaynes's maximum entropy principle (MEP) is analyzed by considering in detail a recent controversy. Emphasis is placed on the inductive logical interpretation of “probability” and the concept of “total knowledge.” The relation of the MEP to relative frequencies is discussed, and a possible realm of its fruitful application is noted.
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The principle of maximum entropy
The Mathematical Intelligencer, 1985The authors point out that the ''principle of maximum entropy'' can be considered as a variational principle which has applications in statistical mechanics, in decision theory, in pattern-recognition and in time-series analysis. They explain this principle as follows: From the set of all probability distributions (for instance, the possible ...
Guiasu, Silviu, Shenitzer, Abe
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Nonsymmetric entropy and maximum nonsymmetric entropy principle
Chaos, Solitons & Fractals, 2009zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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Entropy and Principle of Maximum Entropy
1998Clausius coined the term ‘entropy’ from the Greek meaning transformation. Thus, entropy originated in physics and occupies an exceptional position among physical quantities. It does not appear in the fundamental equations of motion. Its nature is, rather, a statistical or probabilistic one, for it can be interpreted as a measure of the amount of chaos ...
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