18 resultados para estimation of parameters

em Bulgarian Digital Mathematics Library at IMI-BAS


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The present research offers the technique of the experimental estimation of the ergonomic parameters of the computer training programs, created on the basis of the method of theoretical images are submitted.

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2000 Mathematics Subject Classification: 97C40.

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2000 Mathematics Subject Classification: Primary 62F35; Secondary 62P99

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Multitype branching processes (MTBP) model branching structures, where the nodes of the resulting tree are particles of different types. Usually such a process is not observable in the sense of the whole tree, but only as the “generation” at a given moment in time, which consists of the number of particles of every type. This requires an EM-type algorithm to obtain a maximum likelihood (ML) estimate of the parameters of the branching process. Using a version of the inside-outside algorithm for stochastic context-free grammars (SCFG), such an estimate could be obtained for the offspring distribution of the process.

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2010 Mathematics Subject Classification: 60J80.

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2010 Mathematics Subject Classification: 62J99.

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When designing specification on-board algorithm (the algorithm, realized on on-board digital computing machine, and algorithm to activity of the crew necessary to conduct the estimation their realizing. Presented computer system allows in interactive mode with user to value the temporary expenseses of the operator on processes decision making and their realizing, participations it in process of the spying.

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Existing approaches to quality estimation of e-learning systems are analyzed. The “layered” approach for quality estimation of e-learning systems enhanced with learning process modeling and simulation is presented. The method of quality estimation using learning process modeling and quality criteria are suggested. The learning process model based on extended colored stochastic Petri net is described. The method has been implemented in the automated system of quality estimation of e-learning systems named “QuAdS”. Results of approbation of the developed method and quality criteria are shown. We argue that using learning process modeling for quality estimation simplifies identifying lacks of an e-learning system for an expert.

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In the world, scientific studies increase day by day and computer programs facilitate the human’s life. Scientists examine the human’s brain’s neural structure and they try to be model in the computer and they give the name of artificial neural network. For this reason, they think to develop more complex problem’s solution. The purpose of this study is to estimate fuel economy of an automobile engine by using artificial neural network (ANN) algorithm. Engine characteristics were simulated by using “Neuro Solution” software. The same data is used in MATLAB to compare the performance of MATLAB is such a problem and show its validity. The cylinder, displacement, power, weight, acceleration and vehicle production year are used as input data and miles per gallon (MPG) are used as target data. An Artificial Neural Network model was developed and 70% of data were used as training data, 15% of data were used as testing data and 15% of data is used as validation data. In creating our model, proper neuron number is carefully selected to increase the speed of the network. Since the problem has a nonlinear structure, multi layer are used in our model.

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2000 Mathematics Subject Classification: 60J80.

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AMS subject classification: 49N35,49N55,65Lxx.

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A computer code system for simulation and estimation of branching processes is proposed. Using the system, samples for some models with or without migration are generated. Over these samples we compare some properties of various estimators.

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2000 Mathematics Subject Classification: 60J80, 60J85, 62P10, 92D25.

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2000 Mathematics Subject Classification: 60J80, 62M05.

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2000 Mathematics Subject Classi cation: 62D05.