Relevant bibliographies by topics / Tilted Local Linear Estimator

Academic literature on the topic 'Tilted Local Linear Estimator'

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Published: 10 December 2022
Last updated: 28 January 2023

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Journal articles on the topic "Tilted Local Linear Estimator"

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Cohen, Israel, Nicholas Coult, and Anthony A. Vassiliou. "Detection and extraction of fault surfaces in 3D seismic data." GEOPHYSICS 71, no. 4 (July 2006): P21—P27. http://dx.doi.org/10.1190/1.2215357.

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We propose an efficient method for detecting and extracting fault surfaces in 3D-seismic volumes. The seismic data are transformed into a volume of local-fault-extraction (LFE) estimates that represents the likelihood that a given point lies on a fault surface. We partition the fault surfaces into relatively small linear portions, which are identified by analyzing tilted and rotated subvolumes throughout the region of interest. Directional filtering and thresholding further enhance the seismic discontinuities that are attributable to fault surfaces. Subsequently, the volume of LFE estimates is skeletonized, and individual fault surfaces are extracted and labeled in the order of decreasing size. The ultimate result obtained by the proposed procedure provides a visual and semantic representation of a set of well-defined, cleanly separated, one-pixel-thick, labeled fault surfaces that is readily usable for seismic interpretation.
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Wang, Shuguang, and Adam H. Sobel. "A Unified Moisture Mode Theory for the Madden–Julian Oscillation and the Boreal Summer Intraseasonal Oscillation." Journal of Climate 35, no. 4 (February 15, 2022): 1267–91. http://dx.doi.org/10.1175/jcli-d-21-0361.1.

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Abstract The Madden–Julian oscillation (MJO) and the boreal summer intraseasonal oscillation (BSISO) are fundamental modes of variability in the tropical atmosphere on the intraseasonal time scale. A linear model, using a moist shallow water equation set on an equatorial beta plane, is developed to provide a unified treatment of the two modes and to understand their growth and propagation over the Indian Ocean. Moisture is assumed to increase linearly with longitude and to decrease quadratically with latitude. Solutions are obtained through linear stability analysis, considering the gravest (n = 1) meridional mode with nonzero meridional velocity. Anomalies in zonal moisture advection and surface fluxes are both proportional to those in zonal wind, but of opposite sign. With observation-based estimates for both effects, the zonal advection dominates, and drives the planetary-scale instability. With a sufficiently small meridional moisture gradient, the horizontal structure exhibits oscillations with latitude and a northwest–southeast horizontal tilt in the Northern Hemisphere, qualitatively resembling the observed BSISO. As the meridional moisture gradient increases, the horizontal tilt decreases and the spatial pattern transforms toward the “swallowtail” structure associated with the MJO, with cyclonic gyres in both hemispheres straddling the equatorial precipitation maximum. These results suggest that the magnitude of the meridional moisture gradient shapes the horizontal structures, leading to the transformation from the BSISO-like tilted horizontal structure to the MJO-like neutral wave structure as the meridional moisture gradient changes with the seasons. The existence and behavior of these intraseasonal modes can be understood as a consequence of phase speed matching between the equatorial mode with zero meridional velocity (analogous to the dry Kelvin wave) and a local off-equatorial component that is characterized by considering an otherwise similar system on an f plane.
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CAMASSA, ROBERTO, RICHARD M. McLAUGHLIN, and LONGHUA ZHAO. "Lagrangian blocking in highly viscous shear flows past a sphere." Journal of Fluid Mechanics 669 (February 16, 2011): 120–66. http://dx.doi.org/10.1017/s0022112010004933.

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An analytical and computational study of Lagrangian trajectories for linear shear flow past a sphere or spheroid at low Reynolds numbers is presented. Using the exact solutions available for the fluid flow in this geometry, we discover and analyse blocking phenomena, local bifurcation structures and their influence on dynamical effects arising in the fluid particle paths. In particular, building on the work by Chwang & Wu, who established an intriguing blocking phenomenon in two-dimensional flows, whereby a cylinder placed in a linear shear prevents an unbounded region of upstream fluid from passing the body, we show that a similar blocking exists in three-dimensional flows. For the special case when the sphere is centred on the zero-velocity plane of the background shear, the separatrix streamline surfaces which bound the blocked region are computable in closed form by quadrature. This allows estimation of the cross-sectional area of the blocked flow showing how the area transitions from finite to infinite values, depending on the cross-section location relative to the body. When the sphere is off-centre, the quadrature appears to be unavailable due to the broken up-down mirror symmetry. In this case, computations provide evidence for the persistence of the blocking region. Furthermore, we document a complex bifurcation structure in the particle trajectories as the sphere centre is moved from the zero-velocity plane of the background flow. We compute analytically the emergence of different fixed points in the flow and characterize the global streamline topology associated with these fixed points, which includes the emergence of a three-dimensional bounded eddy. Similar results for the case of spheroids are considered in Appendix B. Additionally, the broken symmetry offered by a tilted spheroid geometry induces new three-dimensional effects on streamline deflection, which can be viewed as effective positive or negative suction in the horizontal direction orthogonal to the background flow, depending on the tilt orientation. We conclude this study with results on the case of a sphere embedded at a generic position in a rotating background flow, with its own prescribed rotation including fixed and freely rotating. Exact closed-form solutions for fluid particle trajectories are derived.
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Ziegelmann, Flavio A. "NONPARAMETRIC ESTIMATION OF VOLATILITY FUNCTIONS: THE LOCAL EXPONENTIAL ESTIMATOR." Econometric Theory 18, no. 4 (May 17, 2002): 985–91. http://dx.doi.org/10.1017/s026646660218409x.

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Kernel smoothing techniques free the traditional parametric estimators of volatility from the constraints related to their specific models. In this paper the nonparametric local exponential estimator is applied to estimate conditional volatility functions, ensuring its nonnegativity. Its asymptotic properties are established and compared with those for the local linear estimator. It theoretically enables us to determine when the exponential is expected to be superior to the linear estimator. A very strong and novel result is achieved: the exponential estimator is asymptotically fully adaptive to unknown conditional mean functions. Also, our simulation study shows superior performance of the exponential estimator.
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Kou, Junke, Qinmei Huang, and Huijun Guo. "Pointwise Wavelet Estimations for a Regression Model in Local Hölder Space." Axioms 11, no. 9 (September 10, 2022): 466. http://dx.doi.org/10.3390/axioms11090466.

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This paper considers an unknown functional estimation problem in a regression model with multiplicative and additive noise. A linear wavelet estimator is first constructed by a wavelet projection operator. The convergence rate under the pointwise error of linear wavelet estimators is studied in local Hölder space. A nonlinear wavelet estimator is provided by the hard thresholding method in order to obtain an adaptive estimator. The convergence rate of the nonlinear estimator is the same as the linear estimator up to a logarithmic term. Finally, it should be pointed out that the convergence rates of two wavelet estimators are consistent with the optimal convergence rate on pointwise nonparametric estimation.
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Casas, Isabel, and Irene Gijbels. "Unstable volatility: the break-preserving local linear estimator." Journal of Nonparametric Statistics 24, no. 4 (December 2012): 883–904. http://dx.doi.org/10.1080/10485252.2012.720981.

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Chan, Nigel, and Qiying Wang. "UNIFORM CONVERGENCE FOR NONPARAMETRIC ESTIMATORS WITH NONSTATIONARY DATA." Econometric Theory 30, no. 5 (April 25, 2014): 1110–33. http://dx.doi.org/10.1017/s026646661400005x.

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Sharp upper and lower uniform bounds are established for a general class of functionals of integrated and fractionally integrated time series. The main result is used to develop optimal uniform convergence for the Nadaraya-Watson estimator and the local linear nonparametric estimator in a nonlinear cointegrating regression model. Unlike the point-wise situation, it is shown that the performance of the local linear nonparametric estimator is superior to that of the Nadaraya-Watson estimator in uniform asymptotics.
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Ziegelmann, Flavio A. "A Local Linear Least-Absolute-Deviations Estimator of Volatility." Communications in Statistics - Simulation and Computation 37, no. 8 (August 27, 2008): 1543–64. http://dx.doi.org/10.1080/03610910802244398.

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Bouhadjera, Feriel, and Elias Ould Said. "Strong consistency of the local linear relative regression estimator for censored data." Opuscula Mathematica 42, no. 6 (2022): 805–32. http://dx.doi.org/10.7494/opmath.2022.42.6.805.

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In this paper, we combine the local linear approach to the relative error regression estimation method to build a new estimator of the regression operator when the response variable is subject to random right censoring. We establish the uniform almost sure consistency with rate over a compact set of the proposed estimator. Numerical studies, firstly on simulated data, then on a real data set concerning the death times of kidney transplant patients, were conducted. These practical studies clearly show the superiority of the new estimator compared to competitive estimators.
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Kikechi, Conlet Biketi, and Richard Onyino Simwa. "On Comparison of Local Polynomial Regression Estimators for P=0 and P=1 in a Model Based Framework." International Journal of Statistics and Probability 7, no. 4 (June 27, 2018): 104. http://dx.doi.org/10.5539/ijsp.v7n4p104.

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This article discusses the local polynomial regression estimator for and the local polynomial regression estimator for in a finite population. The performance criterion exploited in this study focuses on the efficiency of the finite population total estimators. Further, the discussion explores analytical comparisons between the two estimators with respect to asymptotic relative efficiency. In particular, asymptotic properties of the local polynomial regression estimator of finite population total for are derived in a model based framework. The results of the local polynomial regression estimator for are compared with those of the local polynomial regression estimator for studied by Kikechi et al (2018). Variance comparisons are made using the local polynomial regression estimator for and the local polynomial regression estimator for which indicate that the estimators are asymptotically equivalently efficient. Simulation experiments carried out show that the local polynomial regression estimator outperforms the local polynomial regression estimator in the linear, quadratic and bump populations.
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Dissertations / Theses on the topic "Tilted Local Linear Estimator"

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Dharmasena, Tibbotuwa Deniye Kankanamge Lasitha Sandamali, and Sandamali dharmasena@rmit edu au. "Sequential Procedures for Nonparametric Kernel Regression." RMIT University. Mathematical and Geospatial Sciences, 2008. http://adt.lib.rmit.edu.au/adt/public/adt-VIT20090119.134815.

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In a nonparametric setting, the functional form of the relationship between the response variable and the associated predictor variables is unspecified; however it is assumed to be a smooth function. The main aim of nonparametric regression is to highlight an important structure in data without any assumptions about the shape of an underlying regression function. In regression, the random and fixed design models should be distinguished. Among the variety of nonparametric regression estimators currently in use, kernel type estimators are most popular. Kernel type estimators provide a flexible class of nonparametric procedures by estimating unknown function as a weighted average using a kernel function. The bandwidth which determines the influence of the kernel has to be adapted to any kernel type estimator. Our focus is on Nadaraya-Watson estimator and Local Linear estimator which belong to a class of kernel type regression estimators called local polynomial kerne l estimators. A closely related problem is the determination of an appropriate sample size that would be required to achieve a desired confidence level of accuracy for the nonparametric regression estimators. Since sequential procedures allow an experimenter to make decisions based on the smallest number of observations without compromising accuracy, application of sequential procedures to a nonparametric regression model at a given point or series of points is considered. The motivation for using such procedures is: in many applications the quality of estimating an underlying regression function in a controlled experiment is paramount; thus, it is reasonable to invoke a sequential procedure of estimation that chooses a sample size based on recorded observations that guarantees a preassigned accuracy. We have employed sequential techniques to develop a procedure for constructing a fixed-width confidence interval for the predicted value at a specific point of the independent variable. These fixed-width confidence intervals are developed using asymptotic properties of both Nadaraya-Watson and local linear kernel estimators of nonparametric kernel regression with data-driven bandwidths and studied for both fixed and random design contexts. The sample sizes for a preset confidence coefficient are optimized using sequential procedures, namely two-stage procedure, modified two-stage procedure and purely sequential procedure. The proposed methodology is first tested by employing a large-scale simulation study. The performance of each kernel estimation method is assessed by comparing their coverage accuracy with corresponding preset confidence coefficients, proximity of computed sample sizes match up to optimal sample sizes and contrasting the estimated values obtained from the two nonparametric methods with act ual values at given series of design points of interest. We also employed the symmetric bootstrap method which is considered as an alternative method of estimating properties of unknown distributions. Resampling is done from a suitably estimated residual distribution and utilizes the percentiles of the approximate distribution to construct confidence intervals for the curve at a set of given design points. A methodology is developed for determining whether it is advantageous to use the symmetric bootstrap method to reduce the extent of oversampling that is normally known to plague Stein's two-stage sequential procedure. The procedure developed is validated using an extensive simulation study and we also explore the asymptotic properties of the relevant estimators. Finally, application of our proposed sequential nonparametric kernel regression methods are made to some problems in software reliability and finance.
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Tristão, Tiago Santana. "Relações não lineares na curva de Phillips : uma abordagem não-paramétrica." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 2013. http://hdl.handle.net/10183/79047.

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Uma das principais preocupações da macroeconomia é a compreensão da dinâmica da inflação no curto prazo. Entender como a inflação se relaciona com a atividade econômica é decisivo para traçar estratégias de desinflação, assim como, de determinação da trajetória de política monetária. Uma questão que surge é qual a forma exata da relação inflação-produto. Ou seja, podemos caracterizar essa relação como não linear? Se sim, qual a forma dessa não linearidade? Para responder a essas perguntas, estimou-se a relação inflação-produto de forma não-paramétrica através de um local linear kernel estimator. O resultado da estimação gerou uma forma funcional a qual foi aproximada pela estimação, via GMM, de uma curva de Phillips Novo-Keynesiana Híbrida. Essa abordagem foi aplicada para o Brasil a partir de 2000. As estimações sugeriram que a dinâmica da inflação brasileira é melhor descrita quando adiciona-se um termo cúbico relativo ao hiato do produto, ou seja, a inflação brasileira mostrou-se state-dependent.
One of the most important macroeconomics’ concerns is the comprehension about sort-run inflation dynamic. To understand how inflation relates to economic activity is crucial to decision-making in disinflation strategies, as well as in monetary policy paths. A question that arises is what does real form of relation inflation-output trade-off? Could one characterize it as a non-linear relation? If does, what is the shape of this non-linear relation? To answer those questions, we estimate the inflation-output relation non-parametrically using a local linear kernel estimator. The functional form achieved was approximated by a New-Keynesian Hybrid Phillips Curve, which one was estimated by GMM. This approach was applied to Brazil since 2000. We have found evidence that Brazilian inflation dynamic is better described adding a cubic term related to output gap, in other words, the Brazilian inflation is state-dependent.
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Pingel, Ronnie. "Some Aspects of Propensity Score-based Estimators for Causal Inference." Doctoral thesis, Uppsala universitet, Statistiska institutionen, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-229341.

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This thesis consists of four papers that are related to commonly used propensity score-based estimators for average causal effects. The first paper starts with the observation that researchers often have access to data containing lots of covariates that are correlated. We therefore study the effect of correlation on the asymptotic variance of an inverse probability weighting and a matching estimator. Under the assumptions of normally distributed covariates, constant causal effect, and potential outcomes and a logit that are linear in the parameters we show that the correlation influences the asymptotic efficiency of the estimators differently, both with regard to direction and magnitude. Further, the strength of the confounding towards the outcome and the treatment plays an important role. The second paper extends the first paper in that the estimators are studied under the more realistic setting of using the estimated propensity score. We also relax several assumptions made in the first paper, and include the doubly robust estimator. Again, the results show that the correlation may increase or decrease the variances of the estimators, but we also observe that several aspects influence how correlation affects the variance of the estimators, such as the choice of estimator, the strength of the confounding towards the outcome and the treatment, and whether constant or non-constant causal effect is present. The third paper concerns estimation of the asymptotic variance of a propensity score matching estimator. Simulations show that large gains can be made for the mean squared error by properly selecting smoothing parameters of the variance estimator and that a residual-based local linear estimator may be a more efficient estimator for the asymptotic variance. The specification of the variance estimator is shown to be crucial when evaluating the effect of right heart catheterisation, i.e. we show either a negative effect on survival or no significant effect depending on the choice of smoothing parameters.   In the fourth paper, we provide an analytic expression for the covariance matrix of logistic regression with normally distributed regressors. This paper is related to the other papers in that logistic regression is commonly used to estimate the propensity score.
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Měsíček, Martin. "Neparametrické regresní odhady." Master's thesis, 2017. http://www.nusl.cz/ntk/nusl-367571.

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This thesis is focused on local polynomial smoothers of the conditional vari- ance function in a heteroscedastic nonparametric regression model. Both mean and variance functions are assumed to be smooth, but neither is assumed to be in a parametric family. The basic idea is to apply a local linear regression to squa- red residuals. This method, as we have shown, has high minimax efficiency and it is fully adaptive to the unknown conditional mean function. However, the local linear estimator may give negative values in finite samples which makes variance estimation impossible. Hence Xu and Phillips proposed a new variance estimator that is asymptotically equivalent to the local linear estimator for interior points but is guaranteed to be non-negative. We also established asymptotic results of both estimators for boundary points and proved better asymptotic behavior of the local linear estimator. That motivated us to propose a modification of the local li- near estimator that guarantees non-negativity. Finally, simulations are conducted to evaluate the finite sample performances of the mentioned estimators.
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Maas, Bea. "Birds, bats and arthropods in tropical agroforestry landscapes: Functional diversity, multitrophic interactions and crop yield." Doctoral thesis, 2013. http://hdl.handle.net/11858/00-1735-0000-0022-5E77-5.

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Book chapters on the topic "Tilted Local Linear Estimator"

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Naceri, Amina, Ali Laksaci, and Mustapha Rachdi. "Exact Quadratic Error of the Local Linear Regression Operator Estimator for Functional Covariates." In Functional Statistics and Applications, 79–90. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-22476-3_5.

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González-López, A., J. Morales-Sánchez, R. Verdú-Monedero, J. Larrey-Ruiz, J. L. Sancho-Gómez, and B. Tobarra-González. "SURE-LET and BLS-GSM wavelet-based denoising algorithms versus linear Local Wiener Estimator in Radiotherapy portal image denoising." In IFMBE Proceedings, 938–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-03474-9_263.

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Tu, Yundong. "Entropy-Based Model Averaging Estimation of Nonparametric Models." In Advances in Info-Metrics, 493–506. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780190636685.003.0018.

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In this chapter, I propose a model averaging estimation of nonparametric models based on Shannon’s entropy measure. The choice of weights in the averaging estimator is implemented bya maximizing the Shannon’s entropy measure which aggregates both model uncertainty and data uncertainty. Finite sample simulation studies show that the proposed averaging estimator outperforms the local linear least square estimator in terms of mean-squared errors and outperforms the Mallows averaging estimator of Hansen (2007) when the signal-to-noise ratio is low. An empirical example to apply the proposed estimator is provided to study the wage equation and illustrates its superiority in out-of-sample forecasts.
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Conference papers on the topic "Tilted Local Linear Estimator"

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Sriliana, Idhia, I. Nyoman Budiantara, and Vita Ratnasari. "The mixed estimator of truncated spline and local linear in multivariable nonparametric regression." In THE 8TH INTERNATIONAL CONFERENCE AND WORKSHOP ON BASIC AND APPLIED SCIENCE (ICOWOBAS) 2021. AIP Publishing, 2023. http://dx.doi.org/10.1063/5.0104167.

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Chamidah, N., M. F. F. Mardianto, E. E. Limanta, and D. R. Hastuti. "Modelling of Poverty Percentage Based on Mean Years of Schooling in Indonesia Using Local Linear Estimator." In The 2nd International Seminar on Science and Technology (ISSTEC 2019). Paris, France: Atlantis Press, 2020. http://dx.doi.org/10.2991/assehr.k.201010.014.

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Chamidah, Nur, and Marisa Rifada. "Estimation of median growth curves for children up two years old based on biresponse local linear estimator." In 5TH INTERNATIONAL CONFERENCE AND WORKSHOP ON BASIC AND APPLIED SCIENCES (ICOWOBAS 2015). AIP Publishing LLC, 2016. http://dx.doi.org/10.1063/1.4943348.

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Anam, W. A., A. Massaid, N. A. Amesya, and N. Chamidah. "Modeling of diabetes mellitus risk based on consumption of salt, sugar, and fat factors using local linear estimator." In SYMPOSIUM ON BIOMATHEMATICS 2019 (SYMOMATH 2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0023498.

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Dow, Eric, Abishek Kashinath, Savithru Jayasinghe, Usuf Middya, and Ali Dogru. "Novel Methods for Simulating Reservoirs with Tilted Fluid Contacts." In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22028-ms.

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Abstract This paper introduces two new approaches for modeling reservoirs with tilted fluid contacts. We first introduce a method based on local capillary pressure adjustments, which uses adjustments of the capillary pressure near the oil-water contact to ensure that the contact surface does not move during production. The second approach uses hydrodynamic aquifer flow to support the oil-water tilt. A non-linear inverse problem is solved to determine the parameters that control the aquifer flow. Both approaches are implemented in a parallel reservoir simulator and applied to a synthetic reservoir case.
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Sorokin, Michael, and Aleksandar Egelja. "Wear Problem in a Linear Hydraulic Actuation System and Solution Using Forced Lubrication." In ASME 2003 International Mechanical Engineering Congress and Exposition. ASMEDC, 2003. http://dx.doi.org/10.1115/imece2003-41296.

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The subject of this paper is early hours wear problem of a hydraulic actuator. Material transfer from the actuator housing to the actuator surface was observed after short time of component testing. A general case, where the actuator is tilted in the bore due to side load, is examined. The mechanism of local scuffing (micro-welding) is discussed. The paper describes the theoretical analysis combined with practical experience in solving common wear problems related to poor material pair and lack of lubrication between sliding surfaces. A validated solution is also discussed.
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Tohari, Amin, Nur Chamidah, and Fatmawati. "Estimating model of the number of HIV and AIDS cases in East Java using bi-response negative binomial regression based on local linear estimator." In SYMPOSIUM ON BIOMATHEMATICS 2019 (SYMOMATH 2019). AIP Publishing, 2020. http://dx.doi.org/10.1063/5.0023451.

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Tohari, Amin, Nur Chamidah, and Fatmawati. "Modeling the number of confirmed and suspected cases of Covid-19 in East Java using bi-response negative binomial regression based on local linear estimator." In INTERNATIONAL CONFERENCE ON MATHEMATICS, COMPUTATIONAL SCIENCES AND STATISTICS 2020. AIP Publishing, 2021. http://dx.doi.org/10.1063/5.0042288.

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Faseyiku, I. O. "Challenges of Autonomy on Effective Local Government in Nigeria." In 28th iSTEAMS Multidisciplinary Research Conference AIUWA The Gambia. Society for Multidisciplinary and Advanced Research Techniques - Creative Research Publishers, 2021. http://dx.doi.org/10.22624/aims/isteams-2021/v28p19.

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The study examined the impact (COVID-19) pandemic on family owned business (FOBs) in Southwest Nigeria. This study targeted a total population of 23,228 SMEs (SMEDAN, 2017) adopted for FOBs because most SMEs are FOBs in Nigeria. A sample size of three hundred and seventy eight 378 respondents from the total population constitutes the sample size for questionnaire that was administered. The determination of sample size for the study was achieved using the Raosoft sample size estimator. Out of the 378 questionnaire being distributed, only 250 were filled and returned appropriately. The study adopted multistage sampling technique. The focus of the study was based on fast moving consumable goods (FMCGs) producers of essential goods. The collected data was scored, tabulated, coded, and analyzed using multiple linear regression analysis with the aid of SPSS 23.0., the result reveals that there is a moderate significant relationship between COVID-19 pandemic and FOBs performance, where product patronage (r = 0.534, P< 0.01); growth (r= 0.623, P< 0.01), and profitability (r = 0.228, P< 0.01). Therefore, the study accepted the alternative hypothesis that there is a significant relationship exist between COVID-19 pandemic and FOBs performance. The study recommended that government should strengthen the business related incentive packages and circulate the information noticeably, this is indispensable in volatile potential of the Covid-19 pandemic predicament; FOBs should identify critical business issues and develop recovery strategy such as business recovery plan (BRP) to enable them mitigates the impact of covid-19 on their businesses; and opportunities should always tap from every situation by businesses. Keywords: COVID-19 Pandemic, FOBs Performance, Product Patronage, Growth, Profitability
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Liu, Yi, and Dragan Djurdjanovic. "Topology Optimization for Piecewise Dynamic Models Using a Genetic Algorithm." In ASME 2010 Dynamic Systems and Control Conference. ASMEDC, 2010. http://dx.doi.org/10.1115/dscc2010-4180.

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It has been demonstrated in the previous research that the node connectivity in the graph encoding the topological neighborhood relationships between local models in a piecewise dynamic model may significantly affect the cooperative learning process. It was shown that a graph with a larger connectivity leads to a quicker learning adaption due to more rapidly decaying transients of the estimation of local model parameters. In the same time, it was shown that the accuracy could be degraded by a larger bias in the asymptotic portion of the estimations of local model parameters. The efforts in topology optimization should therefore strive towards a high accuracy of the asymptotic portion of the estimator of local model parameters while simultaneously accelerating the decay of the estimation transients. In this paper, we pursue minimization of the residual sum of squares of a piecewise dynamic model after a predetermined number of training steps. The optimization of inter-model topology is implemented via a genetic algorithm that manipulates adjacency matrices of the graph underlying the piecewise dynamic model. An example of applying the topology optimization procedure on a peicewise linear model of a highly nonlinear dynamic system is provided to show the efficacy of the new method.
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