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Vybudování sítě PPBP v katastrálním území Vysoká u Valašského Meziříčí / Construction of the net of the points of detailed planimetric survey in the cadastre unit Vysoká by Valašské MeziříčíRybecký, Pavel January 2013 (has links)
The main fokus of this D thesis consists in the creating of horizontal points in Lešná village that is closed to Valašské Meziříčí, part Vysoká. Sixty five points of horizontal control (PPBP) were located and set in Vysoká. The network adjustment was done with the help of the method of lest squares and coordinates were counted with the G-NET/Mini programme.
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Využití rekurzivní metody nejmenších čtverců pro analýzu dynamiky vozidel / The Use of Recursive Least Squares Method for Vehicle Dynamics AnalysisSladká, Pavla January 2010 (has links)
Tato diplomová práce nastiňuje teoretické základy potřebné pro návrh algoritmu rekurzivní metody nejmenších čtverců a následně jeho aplikaci na experimentální data naměřená při testovacím manévru uskutečněném v roce 2001. Analyzována byla příčná dynamika jednostopého rovinného modelu vozidla. Práce také obsahuje srovnání výsledků získaných jednak rekurzivním algoritmem a dále i algoritmem Kalmanova filtru.
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Modelování tržní ceny nemovitosti mnohonásobnou lineární regresí / Market price modelling by real estates with multiple linear regressionStudený, Marek January 2013 (has links)
The main subject of the diploma thesis is a market price modeling by real estates. As a tool for modeling, is used a multiple linear regression. As starting points, are used an econometrical theory and knowledge about real estate valuation. The main goal is to find optimal model for best capture in the time and place.
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Rozšířená kvadraticky optimální identifikace a filtrace / Quadratically Optimal Augmented Identification and FiltrationDokoupil, Jakub January 2012 (has links)
Simultaneous evaluation of the whole set of the model parameters of different orders together with an ability to track unmodeled dynamics are desired features in the tasks of parameter estimation. A technique handling with the factors produced by an augmented covariance (ACM) or information (AIM) matrices is considered to be an appropriate tool for designing multiple model estimation. This is where the name augmented identification (AI) by using the least-squares method was taken. The method AI attains numerical stability of the calculation of the conventional least squares method while in the same time, fully extracts information contained in the observation. In order to track time varying parameters can be found that all the information pertinent to recursive identification and thus to data driven forgetting is concentrated in ACM as well as in AIM. In this thesis will be introduced how to selective forgetting to ACM should be applied in an effective way. It means forget only a portion of accumulated information which will be further modified by the newest data included in the regressor. In the estimation problems the knowledge of the inner states of the identified system is often required. Because the augmented identification belongs within the class so called prediction error method (PEM), some rational requirements can be deduced. As a result, state filter should constitute optimization procedure minimizing the predicted error of given state space model representation with respect to the vector of states. The proposed scheme will considerably extend the family of algorithms based on processing of ACM (AIM) about augmented filtering (AF). This all will establish a comprehensive concept of parametric estimation that compared with conventional approaches is characterized by versatility, low demands on a priori process information and by excellent numerical properties (robust against overparametrization, capable solving the multiple model problem).
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Detekce zubů na 3D počítačovém polygonálním modelu čelisti / Tooth Detection of jaw 3D Computer Polygonal ModelKantor, Roman January 2012 (has links)
This document discusses a problem of tooth detection on jaw 3D polygonal model. It describes known methods that can be used to reach expected results, such as their advantages and disadvantages. Considering this, I choose one solution that is closely described with all theory needed for its implementation.
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Řízení nelineárních systémů s využitím lokálních aproximačních metod / Control of Nonlinear Systems using Local Approximation MethodsBrablc, Martin January 2016 (has links)
Tato práce se zabývá návrhem adaptivního řídícího algortitmu pro konkrétní třídu elektromechanických aktuátorů, založeného na principu dopředného řízení pomocí inverzního dynamického modelu. Adaptibilita řízení spočívá v mechanismu získání inverzního dynamického modelu. Tato práce se zaměřuje na jeho online aproximaci pomocí lokálních aproximačních metod. Výstupem práce je shrnutí analýzy, simulačního testování a reálných experimentů, které testovaly možnosti praktického využití lokálných aproximačních metod pro účely adaptivního řízení v reálném prostředí.
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Optimisation of adaptive localisation techniques for cognitive radioThomas, Robin Rajan 06 August 2012 (has links)
Spectrum, environment and location awareness are key characteristics of cognitive radio (CR). Knowledge of a user’s location as well as the surrounding environment type may enhance various CR tasks, such as spectrum sensing, dynamic channel allocation and interference management. This dissertation deals with the optimisation of adaptive localisation techniques for CR. The first part entails the development and evaluation of an efficient bandwidth determination (BD) model, which is a key component of the cognitive positioning system. This bandwidth efficiency is achieved using the Cramer-Rao lower bound derivations for a single-input-multiple-output (SIMO) antenna scheme. The performances of the single-input-single-output (SISO) and SIMO BD models are compared using three different generalised environmental models, viz. rural, urban and suburban areas. In the case of all three scenarios, the results reveal a marked improvement in the bandwidth efficiency for a SIMO antenna positioning scheme, especially for the 1×3 urban case, where a 62% root mean square error (RMSE) improvement over the SISO system is observed. The second part of the dissertation involves the presentation of a multiband time-of arrival (TOA) positioning technique for CR. The RMSE positional accuracy is evaluated using a fixed and dynamic bandwidth availability model. In the case of the fixed bandwidth availability model, the multiband TOA positioning model is initially evaluated using the two-step maximum-likelihood (TSML) location estimation algorithm for a scenario where line-of-sight represents the dominant signal path. Thereafter, a more realistic dynamic bandwidth availability model has been proposed, which is based on data obtained from an ultra-high frequency spectrum occupancy measurement campaign. The RMSE performance is then verified using the non-linear least squares, linear least squares and TSML location estimation techniques, using five different bandwidths. The proposed multiband positioning model performs well in poor signal-to-noise ratio conditions (-10 dB to 0 dB) when compared to a single band TOA system. These results indicate the advantage of opportunistic TOA location estimation in a CR environment. / Dissertation (MEng)--University of Pretoria, 2012. / Electrical, Electronic and Computer Engineering / unrestricted
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Forecasting Foreign Direct Investment in South Africa using Non-Parametric Quantile Regression ModelsNetshivhazwaulu, Nyawedzeni 16 May 2019 (has links)
MSc (Statistics) / Department of Statistics / Foreign direct investment plays an important role in the economic growth
process in the host country, since foreign direct investment is considered as
a vehicle transferring new ideas, capital, superior technology and skills from
developed country to developing country. Non-parametric quantile regression
is used in this study to estimate the relationship between foreign direct
investment and the factors in
uencing it in South Africa, using the data for
the period 1996 to 2015. The variables are selected using the least absolute
shrinkage and selection operator technique, and all the variables were selected
to be in the models. The developed non-parametric quantile regression models
were used for forecasting the future in
ow of foreign direct investment
in South Africa. The forecast evaluation was done for all models and the
laplace radial basis kernel, ANOVA radial basis kernel and linear quantile
regression averaging were selected as the three best models based on the accuracy
measures (mean absolute percentage error, root mean square error
and mean absolute error). The best set of forecast was selected based on the
prediction interval coverage probability, Prediction interval normalized average
deviation and prediction interval normalized average width. The results
showed that linear quantile regression averaging is the best model to predict
foreign direct investment since it had 100% coverage of the predictions. Linear
quantile regression averaging was also con rmed to be the best model
under the forecast error distribution. One of the contributions of this study
was to bring the accurate foreign direct investment forecast results that can
help policy makers to come up with good policies and suitable strategic plans
to promote foreign direct investment in
ows into South Africa. / NRF
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Stability Rates for Linear Ill-Posed Problems with Convolution and Multiplication OperatorsHofmann, B., Fleischer, G. 30 October 1998 (has links)
In this paper we deal with the `strength' of ill-posedness for ill-posed linear operator equations Ax = y in Hilbert spaces, where we distinguish according_to_M. Z. Nashed [15] the ill-posedness of type I if A is not compact, but we have R(A) 6= R(A) for the range R(A) of A; and the ill-posedness of type II for compact operators A: From our considerations it seems to follow that the problems with noncompact operators A are not in general `less' ill-posed than the problems with compact operators. We motivate this statement by comparing the approximation and stability behaviour of discrete least-squares solutions and the growth rate of Galerkin matrices in both cases. Ill-posedness measures for compact operators A as discussed in [10] are derived from the decay rate of the nonincreasing sequence of singular values of A. Since singular values do not exist for noncompact operators A; we introduce stability rates in order to have a common measure for the compact and noncompact cases. Properties of these rates are illustrated by means of convolution equations in the compact case and by means of equations with multiplication operators in the noncompact case. Moreover using increasing rearrangements of the multiplier functions specific measures of ill-posedness called ill-posedness rates are considered for the multiplication operators. In this context, the character of sufficient conditions providing convergence rates of Tikhonov regularization are compared for compact operators and multiplication operators.
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Optimisation of food overloading at long distance flightsEger, Karl-Heinz, Uranchimeg, Tudevdagva 22 August 2009 (has links)
This paper deals with optimisation of food overloading
at long distance flights. It is described how in case of two
offered meals and two several passenger groups reserve meals
are to distribute to both meals such that the probability that
each passenger will get the meal of its choice is maximised.
A statistical procedure is presented for estimation of needed
demand probabilities.
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