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Tytuł:
Nonlinear multiple model particle filters algorithm for tracking multiple targets
Autorzy:
Sebbagh, A.
Tebbikh, H.
Powiązania:
https://bibliotekanauki.pl/articles/229441.pdf
Data publikacji:
2011
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
estimation
particle filter
multiple targets tracking
multiple model approach
Opis:
The paper addresses multiple targets tracking problem encountered in number of situations in signal and image processing. In this paper, we present an efficient filtering algorithm to perform accurate estimation in jump Markov nonlinear systems, which we aim to contribute in solving the problem of multiple targets tracking using bearings-only measurements. The idea of this algorithm consists of the combination between the multiple model approach and particle filtering methods, which give a nonlinear multiple model particle filters algorithm. This algorithm is used to estimate the trajectories of multiple targets assumed to be nonlinear, from their noisy bearings.
Źródło:
Archives of Control Sciences; 2011, 21, 1; 37-60
1230-2384
Pojawia się w:
Archives of Control Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Measures of Diversity and the Classification Error in the Multiple-model Approach
Miary zróżnicowania modeli a błąd klasyfikacji w podejściu wielomodelowym
Autorzy:
Gatnar, Eugeniusz
Powiązania:
https://bibliotekanauki.pl/articles/905052.pdf
Data publikacji:
2009
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
Multiple-model approach
Model fusion
Classifier ensemble
Diversity measures
Opis:
Multiple-model approach (model aggregation, model fusion) is most commonly used in classification and regression. In this approach K component (single) models C1(x), C1(x), … , CK(x) are combined into one global model (ensemble) C*(x), for example using majority voting: K C* = arg max {Σ I (Ck(x)=y)} (1) y k=1 Turner i Ghosh (1996) proved that the classification error of the ensemble C*(x) depends on the diversity of the ensemble members. In other words, the higher diversity of component models, the lower classification error of the combined model. Since several diversity measures for classifier ensembles have been proposed so far in this paper we present a comparison of the ability of selected diversity measures to predict the accuracy of classifier ensembles.
Podejście wielomodelowe (agregacja modeli), stosowane najczęściej w analizie dyskryminacyjnej i regresyjnej, polega na połączeniu M modeli składowych C1(x), ..., CM(x) jeden model globalny C*(x): K C* = arg max {Σ I (Cm(x)=y)} y k=1 Turner i Ghosh (1996) udowodnili, że błąd klasyfikacji dla modelu zagregowanego C*(x) zależy od stopnia podobieństwa (zróżnicowania) modeli składowych. Inaczej mówiąc, najbardziej dokładny model C*(x) składa się z modeli najbardziej do siebie niepodobnych, tj. zupełnie inaczej klasyfikujących te same obiekty. W literaturze zaproponowano kilka miar pozwalających ocenić podobieństwo (zróżnicowanie) modeli składowych w podejściu wielomodelowym. W artykule omówiono związek znanych miar zróżnicowania z oceną wielkości błędu klasyfikacji modelu zagregowanego.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2009, 225
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Combining different types of classifiers
Łączenie różnych rodzajów modeli dyskryminacyjnych
Autorzy:
Gatnar, Eugeniusz
Powiązania:
https://bibliotekanauki.pl/articles/907037.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Łódzki. Wydawnictwo Uniwersytetu Łódzkiego
Tematy:
multiple-model approach
model fusion
classifier ensemble
diversity measures
Opis:
Model fusion has proved to be a very successful strategy for obtaining accurate models in classification and regression. The key issue, however, is the diversity of the component classifiers because classification error of an ensemble depends on the correlation between its members. The majority of existing ensemble methods combine the same type of models, e.g. trees. In order to promote the diversity of the ensemble members, we propose to aggregate classifiers of different types, because they can partition the same classification space in very different ways (e.g. trees, neural networks and SVMs).
Łączenie modeli okazało się być bardzo efektywną strategią poprawy jakości predykcji modeli dyskryminacyjnych. Kluczowym zagadnieniem, jak wynika z twierdzenia Turnera i Ghosha (1996), jest jednak stopień różnorodności agregowanych modeli, tzn. im większa korelacja między wynikami klasyfikacji tych modeli, tym większy błąd. Większość znanych metod łączenia modeli, np. RandomForest zaproponowany przez Breimana (2001), agreguje modele tego samego typu w różnych przestrzeniach cech. Aby zwiększyć różnice między pojedynczymi modelami, w referacie zaproponowano łączenie modeli różnych typów, które zostały zbudowane w tej samej przestrzeni zmiennych (np. drzewa klasyfikacyjne i modele SVM). W eksperymentach wykorzystano 5 klas modeli: liniowe i kwadratowe modele dyskryminacyjne, drzewa klasyfikacyjne, sieci neuronowe, oraz modele zbudowane za pomocą metody £-najbliższych sąsiadów (k-NN) i metody wektorów nośnych (SVM). Uzyskane rezultaty pokazują, że modele zagregowane powstałe w wyniku łączenia różnych modeli są bardziej dokładne niż gdy modele składowe są tego samego typu.
Źródło:
Acta Universitatis Lodziensis. Folia Oeconomica; 2008, 216
0208-6018
2353-7663
Pojawia się w:
Acta Universitatis Lodziensis. Folia Oeconomica
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Software implementation of multiple model neural filter for radar target tracking
Autorzy:
Kazimierski, W.
Wawrzyniak, N.
Powiązania:
https://bibliotekanauki.pl/articles/359024.pdf
Data publikacji:
2012
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
radar target tracking
multiple model filters
neural networks
Opis:
The paper presents a software implementation of multiple model neural filter for radar target tracking. Such a filter may be proposed as an interesting alternative for numerical filters. The main purpose of software implementation is to provide a tool for complex research of the filter possibilities and adjusting options. A concept of a filter is briefly mentioned, however the main body of paper is focused on user-approach detailed description of application with UML use-case diagrams. Examples of detailed presentation of usecases are given and the general use-case diagram for application is included. The application itself is to be an advanced tool for researchers interested in analyzing target tracking process, providing different tracking methods and the possibility of adjusting their parameters. The possibility of simulating any scenario, as well as working with real data (also on-line) was ensured. The research was financed by Polish National Centre of Science under the research project “Development of radar target tracking methods of floating targets with the use of multiple model neural filtering”.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2012, 32 (104) z. 2; 88-93
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
The analysis of methods of interaction between elementary filters in multiple model tracking filter in marine radars
Autorzy:
Kazimierski, W.
Powiązania:
https://bibliotekanauki.pl/articles/359032.pdf
Data publikacji:
2012
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
radar target tracking
multiple model filters
manoeuvre detection
Opis:
Radar target tracking on a sea-going ship is a basic source of information about movement of other vessels, influencing directly safety of navigation. The research on improving of tracking methods has led to a new concept of multiple model neural filtration, which is a combination of multiple model approach with the use of artificial neural networks for the needs of estimation of movement vector. One of the key issue during designing of filter id to establish rules of interaction between elementary filters. The paper presents the most popular methods of manoeuvre detection and interaction of elementary filters in the numerical filtration. The modifications of them for the needs of neural tracking are proposed. Additionally, a concept of use of probabilistic neural network for this purpose is described. The idea was checked in the experimental research with the use of simulation. The result of the research confirmed usefulness of using PNN in multiple model filtration, showing however simultaneously the directions of future research in this. The research was financed by Polish National Centre of Science under the research project “Development of radar target tracking methods of floating targets with the use of multiple model neural filtering”.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2012, 32 (104) z. 2; 81-87
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Fuzzy switching for multiple model adaptive control in manipulator robot
Autorzy:
Kharabian, B.
Bolandi, H.
Smailzadeh, S. M.
Mousavi Mashhadi, S. K.
Powiązania:
https://bibliotekanauki.pl/articles/384940.pdf
Data publikacji:
2017
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
manipulator robot
fuzzy logic
multiple model
adaptive control
switching
Opis:
In this paper, fuzzy logic is used to perform switching controllers for Multiple Model Adaptive Control (MMAC) in manipulator robot. In the cases which uncertainty bounds of system’s parameters are large, the performance and stability issue of system are considerable concerns. Multiple Model Adaptive Control approach can be useful method to stabilize these kinds of systems. In this control method, the uncertainty bound is divided into several smaller bounds. As a result, the process of stabilization would be streamlined. In this regard, one estimation is obtained for uncertain parameter in every minor bound, and based on estimation errors designed controller can alter. In order to avoid switching controllers and pertinent challenges a summation of controllers with coefficient tuned by fuzzy logic is considered. Simulation results substantiate the efficacy of this method.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2017, 11, 1; 53-56
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Nonlinear system identification using heterogeneous multiple models
Autorzy:
Orjuela, R.
Marx, B.
Ragot, J.
Maquin, D.
Powiązania:
https://bibliotekanauki.pl/articles/330794.pdf
Data publikacji:
2013
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
nonlinear system identification
multiple model
heterogeneous submodel
układ nieliniowy
model wielokrotny
podmodel heterogeniczny
Opis:
Multiple models are recognised by their abilities to accurately describe nonlinear dynamic behaviours of a wide variety of nonlinear systems with a tractable model in control engineering problems. Multiple models are built by the interpolation of a set of submodels according to a particular aggregation mechanism, with the heterogeneous multiple model being of particular interest. This multiple model is characterized by the use of heterogeneous submodels in the sense that their state spaces are not the same and consequently they can be of various dimensions. Thanks to this feature, the complexity of the submodels can be well adapted to that of the nonlinear system introducing flexibility and generality in the modelling stage. This paper deals with off-line identification of nonlinear systems based on heterogeneous multiple models. Three optimisation criteria (global, local and combined) are investigated to obtain the submodel parameters according to the expected modelling performances. Particular attention is paid to the potential problems encountered in the identification procedure with a special focus on an undesirable phenomenon called the no output tracking effect. The origin of this difficulty is explained and an effective solution is suggested to overcome this problem in the identification task. The abilities of the model are finally illustrated via relevant identification examples showing the effectiveness of the proposed methods.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2013, 23, 1; 103-115
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Forecasting production volume in a plastics enterprise
Autorzy:
Grzelak, Małgorzata
Powiązania:
https://bibliotekanauki.pl/articles/970665.pdf
Data publikacji:
2019-03-31
Wydawca:
Uniwersytet Gdański. Wydział Ekonomiczny
Tematy:
multiple regression model
production scheduling
readiness
forecasting
Opis:
The functioning of production enterprises is based on satisfying the needs of customers through the timely manufacture of products in accordance with the demand existing on the market. The availability of the offered range of products is guaranteed by a correct preparation of forecasts of potential orders. This article presents a multiple-regression-method-based tool supporting the planning of production volumes in an enterprise depending on the calendar month. Reliability analysis of the developed model through the analysis of residuals and their autocorrelations and partial autocorrelations is also presented. Key words: multiple regression model, production scheduling, readiness, forecasting JEL classification: C2, C22.
Źródło:
Współczesna Gospodarka; 2019, 10, 1 (32); 69-78
2082-677X
Pojawia się w:
Współczesna Gospodarka
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Variable- and Fixed-Structure Augmented Interacting Multiple-Model Algorithms for Manoeuvring Ship Tracting Based on New Ship Models
Autorzy:
Semerdjiev, E.
Mihaylova, L.
Powiązania:
https://bibliotekanauki.pl/articles/911219.pdf
Data publikacji:
2000
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
model niepewności
estymacja parametryczna
Interacting Multiple Model (IMM) algorithm
model uncertainty
state and parameter estimation
Opis:
Real-world tracking applications are related to a number of difficulties caused by the presence of different kinds of uncertainty, e.g. unknown or incompletely known system models and statistics of random processes or abrupt changes in the system modes of functioning. These problems are especially complicated in the marine navigation practice, where the commonly-used simple models of rectilinear or curvilinear target motions are not adequate for highly non-linear dynamics of the manoeuvring ship motion. A solution to these problems is to derive more suitable descriptions of real ship dynamics and to design adaptive estimation algorithms. After an analysis of basic hydrodynamic models, new ship models are derived in the paper. They are implemented in two versions of the Interacting Multiple Model (IMM) algorithm which has become very popular recently. The first one is a standard IMM version based on fixed model structures (FS's). They represent various modes of ship motion, distinguished by their rates of turns. The same rate of turn is additionally adjusted in the proposed new augmented versions of the IMM (AIMM) algorithm by using FS's and variable structures (VS's) of adaptive models estimating the current change in the system control parameters. Monte Carlo simulation experiments indicate that the VS AIMM algorithm outperforms the FS AIMM and FS IMM ones with respect to both accuracy and adaptability.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2000, 10, 3; 591-604
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Decentralized and distributed active fault diagnosis: Multiple model estimation algorithms
Autorzy:
Straka, Ondřej
Punčochář, Ivo
Powiązania:
https://bibliotekanauki.pl/articles/330423.pdf
Data publikacji:
2020
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fault diagnosis
large scale system
multiple model
diagnostyka błędu
system dużej skali
model wieloskładnikowy
Opis:
The paper focuses on active fault diagnosis (AFD) of large scale systems. The multiple model framework is considered and two architectures are treated: the decentralized and the distributed one. An essential part of the AFD algorithm is state estimation, which must be supplemented with a mechanism to achieve feasible implementation in the multiple model framework. In the paper, the generalized pseudo Bayes and interacting multiple model estimation algorithms are considered. They are reformulated for a given model of a large scale system. Performance of both AFD architectures is analyzed for different combinations of multiple model estimation algorithms using a numerical example.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2020, 30, 2; 239-249
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Actuator failure compensation for two linked 2WD mobile robots based on multiple-model control
Autorzy:
Ma, Y.
Cocquempot, V.
El Badaoui El Najjar, M.
Jiang, B.
Powiązania:
https://bibliotekanauki.pl/articles/331196.pdf
Data publikacji:
2017
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
actuator failure
multiple model control
physically linked robot
two wheel drive
awaria siłownika
sterowanie wielomodelowe
robot połączony
Opis:
This paper develops a new actuator failure compensation scheme for two linked two-wheel drive (2WD) mobile robots based on multiple-model control. First, a configuration of two linked 2WD robots is described, and their kinematics and dynamics are modeled. Then, a multiple-model based failure compensation scheme is developed to compensate for actuator failures, consisting of a kinematic controller, multiple dynamic controllers and a control switching mechanism, which ensures system stability and asymptotic tracking properties. Finally, simulation results verify the effectiveness of the proposed failure compensation control system.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2017, 27, 4; 763-776
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dynamic modelling of an anaerobic reactor treating coffee wet wastewater via multiple regression model
Autorzy:
Guardia-Puebla, Yans
Llanes-Cedeño, Edilberto
Domínguez-León, Ana Velia
Arias-Cedeño, Quirino
Sánchez-Girón, Victor
Morscheck, Gert
Eichler-Löbermann, Bettina
Powiązania:
https://bibliotekanauki.pl/articles/1841946.pdf
Data publikacji:
2021
Wydawca:
Instytut Technologiczno-Przyrodniczy
Tematy:
coffee wet wastewater
modelling
multiple regression model
upflow anaerobic sludge blanket
UASB
Opis:
A multiple regression model approach was developed to estimate buffering indices, as well as biogas and methane productions in an upflow anaerobic sludge blanket (UASB) reactor treating coffee wet wastewater. Five input variables measured (pH, alkalinity, outlet VFA concentration, and total and soluble COD removal) were selected to develop the best models to identify their importance on methanation. Optimal regression models were selected based on four statistical performance criteria, viz. Mallow’s Cp statistic (Cp), Akaike information criterion (AIC), Hannan–Quinn criterion (HQC), and Schwarz–Bayesian information criterion (SBIC). The performance of the models selected were assessed through several descriptive statistics such as measure of goodness-of-fit test (coefficient of multiple determination, R2; adjusted coefficient of multiple determination, Adj-R2; standard error of estimation, SEE; and Durbin–Watson statistic, DWS), and statistics on the prediction errors (mean squared error, MSE; mean absolute error, MAE; mean absolute percentage error, MAPE; mean error, ME and mean percentage error, MPE). The estimated model reveals that buffering indices are strongly influenced by three variables (volatile fatty acids (VFA) concentration, soluble COD removal, and alkalinity); while, pH, VFA concentration and total COD removal were the most significant independent variables in biogas and methane production. The developed equation models obtained in this study, could be a powerful tool to predict the functionability and stability for the UASB system.
Źródło:
Journal of Water and Land Development; 2021, 50; 229-239
1429-7426
2083-4535
Pojawia się w:
Journal of Water and Land Development
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A fault tree-based approach for aviation risk analysis considering mental workload overload
Autorzy:
Che, Haiyang
Zeng, Shengkui
You, Qidong
Song, Yueheng
Guo, Jianbin
Powiązania:
https://bibliotekanauki.pl/articles/2038044.pdf
Data publikacji:
2021
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
risk analysis
human error
mental workload overload
multiple resources model
fault tree analysis
Opis:
Many lives and aircrafts have been lost due to human errors associated with mental workload overload (MWLOL). Human errors are successfully considered in existing Fault Tree Analysis (FTA) methods. However, MWLOL is considered through Performance Shaping Factors indirectly and its information is hidden in FT construction, which is not conducive to analyze the root causes of human errors and risks. To overcome this difficulty, we develop a risk analysis method where Multiple Resources Model (MRM) is incorporated into FTA methods. MRM analyzes mental workload by estimating the resources used during performing concurrent tasks, probably including abnormal situation handling tasks introduced by basic events in FT. Such basic events may cause MWLOL and then trigger corresponding human error events. A MWLOL gate is proposed to describe MWLOL explicitly and add these new relationships to traditional FT. This new method extends previous FTA methods and provides a more in-depth risk analysis. An accident, a helicopter crash in Maryland, is analyzed by the proposed method.
Źródło:
Eksploatacja i Niezawodność; 2021, 23, 4; 646-658
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Multiple State Model for Premium Calculation when Several Premium-Paid States are Involved
Autorzy:
Dębicka, Joanna
Zmyślona, Beata
Powiązania:
https://bibliotekanauki.pl/articles/2076271.pdf
Data publikacji:
2018
Wydawca:
Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:
modified multiple state model
net premium
life annuity
criticalillness insurance
accelerated death benefits
Opis:
The aim of this contribution is to derive a general matrix formula for the net period premium paid in more than one state. In order to avoid “overpayment” which implies higher premiums we give a formula for replacement of lump sum benefit into annuity benefits paid in more than one state. The obtained result is useful for example to more advanced models of dread disease insurances allowing period premiums paid by both healthy and ill person (e.g. not terminally yet). As an application, we supply analysis of dread disease insurances against the risk of lung cancer based on the actual data for the Lower Silesian Voivodship in Poland.
Źródło:
Central European Journal of Economic Modelling and Econometrics; 2018, 1; 27-52
2080-0886
2080-119X
Pojawia się w:
Central European Journal of Economic Modelling and Econometrics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A multi-model based adaptive reconfiguration control scheme for an electro-hydraulic position servo system
Autorzy:
Zhang, Zhao
Yang, Zhong
Liu, Shuchang
Chen, Shuang
Zhang, Xiaokai
Powiązania:
https://bibliotekanauki.pl/articles/2124780.pdf
Data publikacji:
2022
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
fault tolerant control
electro hydraulic position
servo system
multiple model
adaptive control
reconfiguration control
sterowanie tolerujące uszkodzenia
serwomechanizm
sterowanie adaptacyjne
Opis:
Reliability and safety of an electro-hydraulic position servo system (EHPSS) can be greatly reduced for potential sensor and actuator faults. This paper proposes a novel reconfiguration control (RC) scheme that combines multi-model and adaptive control to compensate for the adverse effects. Such a design includes several fixed models, one adaptive model, and one reinitialized adaptive model. Each of the models has its own independent controller that is based on a complete parametrization of the corresponding fault. A proper switching mechanism is set up to select the most appropriate controller to control the current plant. The system output can track the reference model asymptotically using the proposed method. Simulation results validate robustness and effectiveness of the proposed scheme. The main contribution is a reconfiguration control method that can handle component faults and maintain the acceptable performance of the EHPSS.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2022, 32, 2; 185--196
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
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