991 resultados para inverse probability weighted


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Here we present the first radiometric age data and a comprehensive geochemical data set (including major and trace element and Sr-Nd-Pb-Hf isotope ratios) for samples from the Hikurangi Plateau basement and seamounts on and adjacent to the plateau obtained during the R/V Sonne 168 cruise, in addition to age and geochemical data from DSDP Site 317 on the Manihiki Plateau. The 40Ar/39Ar age and geochemical data show that the Hikurangi basement lavas (118-96 Ma) have surprisingly similar major and trace element and isotopic characteristics to the Ontong Java Plateau lavas (ca. 120 and 90 Ma), primarily the Kwaimbaita-type composition, whereas the Manihiki DSDP Site 317 lavas (117 Ma) have similar compositions to the Singgalo lavas on the Ontong Java Plateau. Alkalic, incompatible-element-enriched seamount lavas (99-87 Ma and 67 Ma) on the Hikurangi Plateau and adjacent to it (Kiore Seamount), however, were derived from a distinct high time-integrated U/Pb (HIMU)-type mantle source. The seamount lavas are similar in composition to similar-aged alkalic volcanism on New Zealand, indicating a second wide-spread event from a distinct source beginning ca. 20 Ma after the plateau-forming event. Tholeiitic lavas from two Osbourn seamounts on the abyssal plain adjacent to the northeast Hikurangi Plateau margin have extremely depleted incompatible element compositions, but incompatible element characteristics similar to the Hikurangi and Ontong Java Plateau lavas and enriched isotopic compositions intermediate between normal mid-ocean-ridge basalt (N-MORB) and the plateau basement. These younger (~52 Ma) seamounts may have formed through remelting of mafic cumulate rocks associated with the plateau formation. The similarity in age and geochemistry of the Hikurangi, Ontong Java and Manihiki Plateaus suggest derivation from a common mantle source. We propose that the Greater Ontong Java Event, during which ?1% of the Earth's surface was covered with volcanism, resulted from a thermo-chemical superplume/dome that stalled at the transition zone, similar to but larger than the structure imaged presently beneath the South Pacific superswell. The later alkalic volcanism on the Hikurangi Plateau and the Zealandia micro-continent may have been part of a second large-scale volcanic event that may have also triggered the final breakup stage of Gondwana, which resulted in the separation of Zealandia fragments from West Antarctica.

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The focus of the present work is the well-known feature of the probability density function (PDF) transport equations in turbulent flows-the inverse parabolicity of the equations. While it is quite common in fluid mechanics to interpret equations with direct (forward-time) parabolicity as diffusive (or as a combination of diffusion, convection and reaction), the possibility of a similar interpretation for equations with inverse parabolicity is not clear. According to Einstein's point of view, a diffusion process is associated with the random walk of some physical or imaginary particles, which can be modelled by a Markov diffusion process. In the present paper it is shown that the Markov diffusion process directly associated with the PDF equation represents a reasonable model for dealing with the PDFs of scalars but it significantly underestimates the diffusion rate required to simulate turbulent dispersion when the velocity components are considered.

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We consider the direct adaptive inverse control of nonlinear multivariable systems with different delays between every input-output pair. In direct adaptive inverse control, the inverse mapping is learned from examples of input-output pairs. This makes the obtained controller sub optimal, since the network may have to learn the response of the plant over a larger operational range than necessary. Moreover, in certain applications, the control problem can be redundant, implying that the inverse problem is ill posed. In this paper we propose a new algorithm which allows estimating and exploiting uncertainty in nonlinear multivariable control systems. This approach allows us to model strongly non-Gaussian distribution of control signals as well as processes with hysteresis. The proposed algorithm circumvents the dynamic programming problem by using the predicted neural network uncertainty to localise the possible control solutions to consider.

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To avoid counter-intuitive result of classical Dempster's combination rule when dealing with highly conflict information, many improved combination methods have been developed through modifying the basic probability assignments (BPAs) of bodies of evidence (BOEs) by using a certain measure of the degree of conflict or uncertain information, such as Jousselme's distance, the pignistic probability distance and the ambiguity measure. However, if BOEs contain some non-singleton elements and the differences among their BPAs are larger than 0.5, the current conflict measure methods have limitations in describing the interrelationship among the conflict BOEs and may even lead to wrong combination results. In order to solve this problem, a new distance function, which is called supporting probability distance, is proposed to characterize the differences among BOEs. With the new distance, the information of how much a focal element is supported by the other focal elements in BOEs can be given. Also, a new combination rule based on the supporting probability distance is proposed for the combination of the conflicting evidences. The credibility and the discounting factor of each BOE are generated by the supporting probability distance and the weighted BOEs are combined directly using Dempster's rules. Analytical results of numerical examples show that the new distance has a better capability of describing the interrelationships among BOEs, especially for the highly conflicting BOEs containing non-singleton elements and the proposed new combination method has better applicability and effectiveness compared with the existing methods.

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We consider an uncertain version of the scheduling problem to sequence set of jobs J on a single machine with minimizing the weighted total flow time, provided that processing time of a job can take on any real value from the given closed interval. It is assumed that job processing time is unknown random variable before the actual occurrence of this time, where probability distribution of such a variable between the given lower and upper bounds is unknown before scheduling. We develop the dominance relations on a set of jobs J. The necessary and sufficient conditions for a job domination may be tested in polynomial time of the number n = |J| of jobs. If there is no a domination within some subset of set J, heuristic procedure to minimize the weighted total flow time is used for sequencing the jobs from such a subset. The computational experiments for randomly generated single-machine scheduling problems with n ≤ 700 show that the developed dominance relations are quite helpful in minimizing the weighted total flow time of n jobs with uncertain processing times.

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Павел Т. Стойнов - В тази работа се разглежда отрицателно биномното разпределение, известно още като разпределение на Пойа. Предполагаме, че смесващото разпределение е претеглено гама разпределение. Изведени са вероятностите в някои частни случаи. Дадени са рекурентните формули на Панжер.

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Probability density function (pdf) for sum of n correlated lognormal variables is deducted as a special convolution integral. Pdf for weighted sums (where weights can be any real numbers) is also presented. The result for four dimensions was checked by Monte Carlo simulation.

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The existence of an inverse limit of an inverse system of (probability) measure spaces has been investigated since the very beginning of the birth of the modern probability theory. Results from Kolmogorov [10], Bochner [2], Choksi [5], Metivier [14], Bourbaki [3] among others have paved the way of the deep understanding of the problem under consideration. All the above results, however, call for some topological concepts, or at least ones which are closely related topological ones. In this paper we investigate purely measurable inverse systems of (probability) measure spaces, and give a sucient condition for the existence of a unique inverse limit. An example for the considered purely measurable inverse systems of (probability) measure spaces is also given.