176 resultados para Optimum-Path Forest classifier


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A formula has been derived for the mean-square error in the phases of crystal reflections determined through the multiwavelength anomalous scattering method.The error is written in terms of a simple function of the positions in the complex plane of the 'centres' corresponding to the different wavelengths. For the case of three centres, the mean-square error is inversely proportional to the area of the triangle formed by them.

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Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

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An exact expression for the calculation of gaussian path integrals involving non-local potentials is given. Its utility is demonstrated by using it to evaluate a path integral arising in the study of an electron gas in a random potential.

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Forested areas play a dominant role in the global hydrological cycle. Evapotranspiration is a dominant component most of the time catching up with the rainfall. Though there are sophisticated methods which are available for its estimation, a simple reliable tool is needed so that a good budgeting could be made. Studies have established that evapotranspiration in forested areas is much higher than in agricultural areas. Latitude, type of forests, climate and geological characteristics also add to the complexity of its estimation. Few studies have compared different methods of evapotranspiration on forested watersheds in semi arid tropical forests. In this paper a comparative study of different methods of estimation of evapotranspiration is made with reference to the actual measurements made using all parameter climatological station data of a small deciduous forested watershed of Mulehole (area of 4.5 km2 ), South India. Potential evapotranspiration (ETo) was calculated using ten physically based and empirical methods. Actual evapotranspiration (AET) has been calculated through computation of water balance through SWAT model. The Penman-Montieth method has been used as a benchmark to compare the estimates arrived at using various methods. The AET calculated shows good agreement with the curve for evapotranspiration for forests worldwide. Error estimates have been made with respect to Penman-Montieth method. This study could give an idea of the errors involved whenever methods with limited data are used and also show the use indirect methods in estimation of Evapotranspiration which is more suitable for regional scale studies.

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Systems of learning automata have been studied by various researchers to evolve useful strategies for decision making under uncertainity. Considered in this paper are a class of hierarchical systems of learning automata where the system gets responses from its environment at each level of the hierarchy. A classification of such sequential learning tasks based on the complexity of the learning problem is presented. It is shown that none of the existing algorithms can perform in the most general type of hierarchical problem. An algorithm for learning the globally optimal path in this general setting is presented, and its convergence is established. This algorithm needs information transfer from the lower levels to the higher levels. Using the methodology of estimator algorithms, this model can be generalized to accommodate other kinds of hierarchical learning tasks.

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Gaussian processes (GPs) are promising Bayesian methods for classification and regression problems. Design of a GP classifier and making predictions using it is, however, computationally demanding, especially when the training set size is large. Sparse GP classifiers are known to overcome this limitation. In this letter, we propose and study a validation-based method for sparse GP classifier design. The proposed method uses a negative log predictive (NLP) loss measure, which is easy to compute for GP models. We use this measure for both basis vector selection and hyperparameter adaptation. The experimental results on several real-world benchmark data sets show better orcomparable generalization performance over existing methods.

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Using the promeasure technique, we give an alternative evaluation of a path integral corresponding to a quadratic action with a generalized memory.

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Theoretical optimization studies of the performance of a combustion driven premixed two-phase flow gasdynamic laser are presented. The steady inviscid nonreacting quasi-one-dimensional two-phase flow model including appropriate finite rate vibrational kinetic rates has been used in the analysis. The analysis shows that the effect of the particles on the optimum performance of the two-phase laser is very small. The results are presented in graphical form. Applied Physics Letters is copyrighted by The American Institute of Physics.

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Numerically discretized dynamic optimization problems having active inequality and equality path constraints that along with the dynamics induce locally high index differential algebraic equations often cause the optimizer to fail in convergence or to produce degraded control solutions. In many applications, regularization of the numerically discretized problem in direct transcription schemes by perturbing the high index path constraints helps the optimizer to converge to usefulm control solutions. For complex engineering problems with many constraints it is often difficult to find effective nondegenerat perturbations that produce useful solutions in some neighborhood of the correct solution. In this paper we describe a numerical discretization that regularizes the numerically consistent discretized dynamics and does not perturb the path constraints. For all values of the regularization parameter the discretization remains numerically consistent with the dynamics and the path constraints specified in the, original problem. The regularization is quanti. able in terms of time step size in the mesh and the regularization parameter. For full regularized systems the scheme converges linearly in time step size.The method is illustrated with examples.

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Data-flow analysis is an integral part of any aggressive optimizing compiler. We propose a framework for improving the precision of data-flow analysis in the presence of complex control-flow. W initially perform data-flow analysis to determine those control-flow merges which cause the loss in data-flow analysis precision. The control-flow graph of the program is then restructured such that performing data-flow analysis on the resulting restructured graph gives more precise results. The proposed framework is both simple, involving the familiar notion of product automata, and also general, since it is applicable to any forward data-flow analysis. Apart from proving that our restructuring process is correct, we also show that restructuring is effective in that it necessarily leads to more optimization opportunities. Furthermore, the framework handles the trade-off between the increase in data-flow precision and the code size increase inherent in the restructuring. We show that determining an optimal restructuring is NP-hard, and propose and evaluate a greedy strategy. The framework has been implemented in the Scale research compiler, and instantiated for the specific problem of Constant Propagation. On the SPECINT 2000 benchmark suite we observe an average speedup of 4% in the running times over Wegman-Zadeck conditional constant propagation algorithm and 2% over a purely path profile guided approach.

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Instead of waiting for the acknowledgments from all the copies of a single data block sent, as in the optimum generalised stop-and-wait ARQ scheme, the transmitter in the proposed scheme starts sending an optimum number of copies of the next block in the queue, soon after receiving the positive acknowledgment from the receiver, thereby further improving the throughput efficiency.

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For systems which can be decomposed into slow and fast subsystems, a near optimum linear state regulator consisting of two subsystem regulators can be developed. Depending upon the desired criteria, either a short term (fast controller) or a long term controller (slow controller) can be easily designed with minimum computational costs. Using this approach an example of a power system supplying a cyclic load is studied and the performance of the different controllers are compared.

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The operation of thyristor-controlled static VAR compensators (SVCs) at various conduction angles can be used advantageously to meet the unablanced reactive power demands in a system. However, such operation introduces harmonic currents into the AC system. This paper presents an algorithm to evaluate an optimum combination of the phase-wise reactive power generations from SVC and balanced reactive power supply from the AC system, based on the defined performance indices, namely, the telephone influence factor (TIF), the total harmonic current factor (IT) and the distortion factor (D). Results of the studies conducted on a typical distribution system are presented and discussed.

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The problem of designing an optimum Lanchester damper for a viscously damped single degree of freedom system subjected to inertial harmonic excitation is investigated. Two criteria are used for optimizing the performance of the damper: (i) minimum motion transmissibility; (ii) minimum force transmissibility. Explicit expressions are developed for determining the absorber parameters.

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An experimental investigation dealing with the influence of stress path on the shear behaviour of a layered soil prepared in the laboratory is described. Specimens trimmed in vertical and horizontal directions have been sheared under three different stress paths in compression and extension tests. Either in compression or extension, the stress–strain behaviour of the specimens with both orientations was apparently the same, although the volume change behaviour was different. The effective stress parameters C′ and ′ were found to be unique and independent of the stress path and two principal orientations. However, the values of ′ in extension tests were 6–7° higher than those in compression tests.