نتایج جستجو برای: backward probability model
تعداد نتایج: 2271375 فیلتر نتایج به سال:
We propose a closed form Gaussian sum smoother and, more importantly, closed form smoothing solutions for increasingly complex problems arising from practice, including tracking in clutter, joint detection and tracking (in clutter), and multiple target tracking (in clutter) via the Probability Hypothesis Density. The solutions are based on the corresponding forward-backward smoothing recursions...
this thesis is a study on insurance fraud in iran automobile insurance industry and explores the usage of expert linkage between un-supervised clustering and analytical hierarchy process(ahp), and renders the findings from applying these algorithms for automobile insurance claim fraud detection. the expert linkage determination objective function plan provides us with a way to determine whi...
Memex is an algorithmic composition, created by a computer program that operates on a database of works by Bach, Mozart and Beethoven. The program steps forward with probability Q and jumps backward with probability P=1-Q along note links in this database – where the P/Q odds are set by a human artist. Coincidentally, the backward/forward odds used in composing Memex are the same as the win/los...
We consider the dynamics of a stochastic cobweb model with linear demand and a backwardbending supply curve. In our model, forward-looking expectations and backward-looking ones are assumed, in fact we assume that the representative agent chooses the backward predictor with probability q , 0 q 1, and the forward predictor with probability 1 − q , so that the expected price at time t is a random...
The present study aims to model systematic risk using financial and accounting variables. Accordingly, the data for 174 companies in Tehran Stock Exchange are extracted for the period of 2006 to 2016. First, the systematic risk index is estimated using the ARFIMA-FIGARCH model. Then, based on the research background, 35 affective financial and accounting variables are simultaneously used with t...
In this paper, we develop a kernel learning backward SDE filter method to estimate the state of stochastic dynamical system based on its partial noisy observations. A forward differential equations is used propagate target model, and Bayesian inference applied incorporate observational information. To characterize model in entire space, introduce learn continuous global approximation for condit...
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