228 resultados para Limit theorems (Probability theory)

em University of Queensland eSpace - Australia


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Mineral processing plants use two main processes; these are comminution and separation. The objective of the comminution process is to break complex particles consisting of numerous minerals into smaller simpler particles where individual particles consist primarily of only one mineral. The process in which the mineral composition distribution in particles changes due to breakage is called 'liberation'. The purpose of separation is to separate particles consisting of valuable mineral from those containing nonvaluable mineral. The energy required to break particles to fine sizes is expensive, and therefore the mineral processing engineer must design the circuit so that the breakage of liberated particles is reduced in favour of breaking composite particles. In order to effectively optimize a circuit through simulation it is necessary to predict how the mineral composition distributions change due to comminution. Such a model is called a 'liberation model for comminution'. It was generally considered that such a model should incorporate information about the ore, such as the texture. However, the relationship between the feed and product particles can be estimated using a probability method, with the probability being defined as the probability that a feed particle of a particular composition and size will form a particular product particle of a particular size and composition. The model is based on maximizing the entropy of the probability subject to mass constraints and composition constraint. Not only does this methodology allow a liberation model to be developed for binary particles, but also for particles consisting of many minerals. Results from applying the model to real plant ore are presented. A laboratory ball mill was used to break particles. The results from this experiment were used to estimate the kernel which represents the relationship between parent and progeny particles. A second feed, consisting primarily of heavy particles subsampled from the main ore was then ground through the same mill. The results from the first experiment were used to predict the product of the second experiment. The agreement between the predicted results and the actual results are very good. It is therefore recommended that more extensive validation is needed to fully evaluate the substance of the method. (C) 2003 Elsevier Ltd. All rights reserved.

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Argumentation is modelled as a game where the payoffs are measured in terms of the probability that the claimed conclusion is, or is not, defeasibly provable, given a history of arguments that have actually been exchanged, and given the probability of the factual premises. The probability of a conclusion is calculated using a standard variant of Defeasible Logic, in combination with standard probability calculus. It is a new element of the present approach that the exchange of arguments is analysed with game theoretical tools, yielding a prescriptive and to some extent even predictive account of the actual course of play. A brief comparison with existing argument-based dialogue approaches confirms that such a prescriptive account of the actual argumentation has been almost lacking in the approaches proposed so far.

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We shall be concerned with the problem of determining quasi-stationary distributions for Markovian models directly from their transition rates Q. We shall present simple conditions for a mu-invariant measure m for Q to be mu-invariant for the transition function, so that if m is finite, it can be normalized to produce a quasi-stationary distribution. (C) 2000 Elsevier Science Ltd. All rights reserved.

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Cox's theorem states that, under certain assumptions, any measure of belief is isomorphic to a probability measure. This theorem, although intended as a justification of the subjectivist interpretation of probability theory, is sometimes presented as an argument for more controversial theses. Of particular interest is the thesis that the only coherent means of representing uncertainty is via the probability calculus. In this paper I examine the logical assumptions of Cox's theorem and I show how these impinge on the philosophical conclusions thought to be supported by the theorem. I show that the more controversial thesis is not supported by Cox's theorem. (C) 2003 Elsevier Inc. All rights reserved.

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The argument from fine tuning is supposed to establish the existence of God from the fact that the evolution of carbon-based life requires the laws of physics and the boundary conditions of the universe to be more or less as they are. We demonstrate that this argument fails. In particular, we focus on problems associated with the role probabilities play in the argument. We show that, even granting the fine tuning of the universe, it does not follow that the universe is improbable, thus no explanation of the fine tuning, theistic or otherwise, is required.

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Statistics is known to be an art as well as a science. The training of mathematical physicists predisposes them towards hypothesising plausible Bayesean priors. Tony Bracken and I were of that mind [1], but in our discussions we also recognised the Bayesean will-o'-the-wisp illustrated below.

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We consider a buying-selling problem when two stops of a sequence of independent random variables are required. An optimal stopping rule and the value of a game are obtained.

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Stochastic models based on Markov birth processes are constructed to describe the process of invasion of a fly larva by entomopathogenic nematodes. Various forms for the birth (invasion) rates are proposed. These models are then fitted to data sets describing the observed numbers of nematodes that have invaded a fly larval after a fixed period of time. Non-linear birthrates are required to achieve good fits to these data, with their precise form leading to different patterns of invasion being identified for three populations of nematodes considered. One of these (Nemasys) showed the greatest propensity for invasion. This form of modelling may be useful more generally for analysing data that show variation which is different from that expected from a binomial distribution.

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In the absence of an external frame of reference-i.e., in background independent theories such as general relativity-physical degrees of freedom must describe relations between systems. Using a simple model, we investigate how such a relational quantum theory naturally arises by promoting reference systems to the status of dynamical entities. Our goal is twofold. First, we demonstrate using elementary quantum theory how any quantum mechanical experiment admits a purely relational description at a fundamental. Second, we describe how the original non-relational theory approximately emerges from the fully relational theory when reference systems become semi-classical. Our technique is motivated by a Bayesian approach to quantum mechanics, and relies on the noiseless subsystem method of quantum information science used to protect quantum states against undesired noise. The relational theory naturally predicts a fundamental decoherence mechanism, so an arrow of time emerges from a time-symmetric theory. Moreover, our model circumvents the problem of the collapse of the wave packet as the probability interpretation is only ever applied to diagonal density operators. Finally, the physical states of the relational theory can be described in terms of spin networks introduced by Penrose as a combinatorial description of geometry, and widely studied in the loop formulation of quantum gravity. Thus, our simple bottom-up approach (starting from the semiclassical limit to derive the fully relational quantum theory) may offer interesting insights on the low energy limit of quantum gravity.

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Polytomous Item Response Theory Models provides a unified, comprehensive introduction to the range of polytomous models available within item response theory (IRT). It begins by outlining the primary structural distinction between the two major types of polytomous IRT models. This focuses on the two types of response probability that are unique to polytomous models and their associated response functions, which are modeled differently by the different types of IRT model. It describes, both conceptually and mathematically, the major specific polytomous models, including the Nominal Response Model, the Partial Credit Model, the Rating Scale model, and the Graded Response Model. Important variations, such as the Generalized Partial Credit Model are also described as are less common variations, such as the Rating Scale version of the Graded Response Model. Relationships among the models are also investigated and the operation of measurement information is described for each major model. Practical examples of major models using real data are provided, as is a chapter on choosing an appropriate model. Figures are used throughout to illustrate important elements as they are described.

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Adsorption of binary hydrocarbon mixtures involving methane in carbon slit pores is theoretically studied here from the viewpoints of separation and of the effect of impurities on methane storage. It is seen that even small amounts of ethane, propane, or butane can significantly reduce the methane capacity of carbons. Optimal pore sizes and pressures, depending on impurity concentration, are noted in the present work, suggesting that careful adsorbent and process design can lead to enhanced separation. These results are consistent with earlier literature studies for the infinite dilution limit. For methane storage applications a carbon micropore width of 11.4 Angstrom (based on distance between centers of carbon atoms on opposing walls) is found to be the most suitable from the point of view of lower impurity uptake during high-pressure adsorption and greater impurity retention during low-pressure delivery. The results also theoretically confirm unusual recently reported observations of enhanced methane adsorption in the presence of a small amount of heavier hydrocarbon impurity.

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Modulational instability in optical Bragg gratings with a quadratic nonlinearity is studied. The electric field in such structures consists of forward and backward propagating components at the fundamental frequency and its second harmonic. Analytic continuous wave (CW) solutions are obtained, and the intricate complexity of their stability, due to the large number of equations and number of free parameters, is revealed. The stability boundaries are rich in structures and often cannot be described by a simple relationship. In most cases, the CW solutions are unstable. However, stable regions are found in the nonlinear Schrodinger equation limit, and also when the grating strength for the second harmonic is stronger than that of the first harmonic. Stable CW solutions usually require a low intensity. The analysis is confirmed by directly simulating the governing equations. The stable regions found have possible applications in second-harmonic generation and dark solitons, while the unstable regions maybe useful in the generation of ultrafast pulse trains at relatively low intensities. [S1063-651X(99)03005-6].

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This paper presents a personal view of the interaction between the analysis of choice under uncertainty and the analysis of production under uncertainty. Interest in the foundations of the theory of choice under uncertainty was stimulated by applications of expected utility theory such as the Sandmo model of production under uncertainty. This interest led to the development of generalized models including rank-dependent expected utility theory. In turn, the development of generalized expected utility models raised the question of whether such models could be used in the analysis of applied problems such as those involving production under uncertainty. Finally, the revival of the state-contingent approach led to the recognition of a fundamental duality between choice problems and production problems.