Constrained Clustering of Uncertain Data

2016-11-13
Dinler, Derya
Tural, Mustafa Kemal

Suggestions

Constrained discrete-time optimal control of uncertain systems with adaptive Lyapunov redesign
ALTINTAS, Oguz Han; Turgut, Ali Emre (2021-01-01)
All rights reserved.In this paper, the conventional estimation-based receding horizon control paradigm is enhanced by using functional approximation, the adaptive modifications on state estimation and convex projection notion from optimization theory. The mathematical formalism of parameter adaptation and uncertainty estimation procedure are based on the redesign of optimal state estimation in discrete-time. By using Lyapunov stability theory, it is shown that the online approximation of uncertainties acti...
Robust parameter design of products and processes with an ordinal categorical response using random forests
Gülbudak Dil, Seçil; Köksal, Gülser; Department of Industrial Engineering (2018)
In industrial organizations, manufacturers aim to achieve target product performance with minimum variation. For that reason, finding optimal settings of product and process design parameters that make it possible to consistently achieve target product performance is an important design problem. In this study, we propose an alternative method to solve this problem for the case of an ordinal categorical product/process response. The method utilizes Random Forest (RF) for modelling mean and variance of the re...
Constrained nonlinear least squares estimation: a milk production study
Orman, Mehmet N.; Yıldırım, Fetih; Department of Statistics (1991)
Robust optimization in spline regression models for multi-model regulatory networks under polyhedral uncertainty
Ozmen, Ayse; Kropat, Erik; Weber, Gerhard Wilhelm (2017-01-01)
In our study, we integrate the data uncertainty of real-world models into our regulatory systems and robustify them. We newly introduce and analyse robust time-discrete target-environment regulatory systems under polyhedral uncertainty through robust optimization. Robust optimization has reached a great importance as a modelling framework for immunizing against parametric uncertainties and the integration of uncertain data is of considerable importance for the model's reliability of a highly interconnected ...
Robust Tracking in Cellular Networks Using HMM Filters and Cell-ID Measurements
Bshara, Mussa; Orguner, Umut; Gustafsson, Fredrik; Van Biesen, Leo (Institute of Electrical and Electronics Engineers (IEEE), 2011-03-01)
A localization algorithm based on cell identification (Cell-ID) information is proposed. Instead of building the localization decisions only on the serving base station, all the detected Cell-IDs (serving or nonserving) by the mobile station are utilized. The statistical modeling of user motion and the measurements are done via a hidden Markov model (HMM), and the localization decisions are made with maximum a posteriori estimation criterion using the posterior probabilities from an HMM filter. The results ...
Citation Formats
D. Dinler and M. K. Tural, “Constrained Clustering of Uncertain Data,” 2016, Accessed: 00, 2021. [Online]. Available: https://hdl.handle.net/11511/86199.