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Tytuł:
Semi-Markov decision process as a safety and reliability model of a sea transport operations
Autorzy:
Grabski, F.
Powiązania:
https://bibliotekanauki.pl/articles/2069650.pdf
Data publikacji:
2010
Wydawca:
Uniwersytet Morski w Gdyni. Polskie Towarzystwo Bezpieczeństwa i Niezawodności
Tematy:
safety reliability
semi-Markov decision process
transport operation
Opis:
A problem of optimization of a sea transport operation in safety and reliability aspect is discussed in the paper. To describe and solve this problem, a semi-Markov decision processes theory is applied. The semi-Markov decision process as a model of the sea transport operation is constructed. An algorithm which Allowi to compute the optimal strategy of the operation in safety and reliability aspect is presented.
Źródło:
Journal of Polish Safety and Reliability Association; 2010, 1, 1; 99--104
2084-5316
Pojawia się w:
Journal of Polish Safety and Reliability Association
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Intelligent control system for HSM
Autorzy:
Vallejo, A.
Morales-Menendez, R.
Elizalde-Siller, H.
Powiązania:
https://bibliotekanauki.pl/articles/384709.pdf
Data publikacji:
2009
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
Markov decision process
optimization
high-speed machining
milling process
neural network
Opis:
Next-generation of High-Speed Machining (HSM) systems demand advanced features such as intelligent control under uncertainty. This requires, in turn, an efficient administration and optimization of all system's resources towards a previously identified objective. This work presents an optimization system based on Markov Decision Process (MDP), where an intelligent control guides the actions of the operator in peripheral milling processes. Early results suggest that MDP framework can cope with this application, yielding several benefits, which are discussed in detail. Future work will address the full integration of the developed optimization scheme within a commercial machining center.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2009, 3, 3; 54-63
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Example of applying markov decision process o model vehicle maintenance process
Autorzy:
Landowski, B.
Powiązania:
https://bibliotekanauki.pl/articles/243975.pdf
Data publikacji:
2013
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
transport system
operation process
Markov decision process
urban transportation
state of object
Opis:
The subject of this paper are selected issues connected with modelling, prognosis and control of the process of operation and maintenance of a certain category of technical objects. The research object is a system of transport means operation. Assumptions for building a model of the operation process state changes of objects used in a complex system of operation and maintenance have been presented. The operation process model was built on the basis of an analysis of the space of states and events concerning technical objects, which are used in the analysed real transportation system. Source data necessary to make assumptions for the model development and its initial verification, has been obtained by means of the passive experiment method from a real system of transport means operation. An example of Markov decision process use for modelling and analysis of a public city transportation system operation process has been presented. Determination of values of indices characterizing the analysed process has been carried out basing on computer simulation of Markov decision process, being a mathematical model of technical objects operation process. A computing model has illustrated the entire study. Values of the model parameters have been estimated basing on the results of preliminary tests conducted in a real system of transport means operation. The model presented in this work has been built in such a way that it can be used for a wide category of problems connected with technical objects operation.
Źródło:
Journal of KONES; 2013, 20, 4; 209-218
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Applying the Markov decision processes to model changes to the maintenance states of an object
Autorzy:
Landowski, B.
Powiązania:
https://bibliotekanauki.pl/articles/244035.pdf
Data publikacji:
2010
Wydawca:
Instytut Techniczny Wojsk Lotniczych
Tematy:
Markov decision process
modelling
operation and maintenance process
transport system
urban public transport
Opis:
Operation and maintenance of technical objects is related to occurrence of various events, the effects of which affect the operation and maintenance process course, and particularly the courses of their use and service processes. Occurrence of those events may be of both determined and random nature. Assessing, analysing and forecasting the operation and maintenance process course, in complex technical systems, are connected with the problems of modelling the operation and maintenance processes of technical objects. Those processes are random ones which depend on one another. The paper presents an example of the Markov decision process to model changes of the analysed operation and maintenance states of technical objects. The investigation object is a real operation and maintenance system of urban transport buses in a middle-sized agglomeration (about 400 k residents). Supporting a decision maker, in the process of making decisions concerning performance of the operation and maintenance process of the means of transport, may be carried out by analysing the results of the investigations of the operation and maintenance process model. The investigations of that type are to determine values of the selected measures of technical and economic efficiency of the process being carried out for the estimated values of the model parameters. The values of the model parameters were estimated on the basis of the analysis of the results of the investigations performed in the analysed system of urban bus transport. A change to the values of the model parameters may reflect a change of influence of internal and external factors on behaviour of the system and the operation and maintenance process of the means of transport being carried out in it. Mathematical models of the operation and maintenance processes are intrinsically simplified, therefore practical conclusions resulting from investigating those models should be formulated carefully.
Źródło:
Journal of KONES; 2010, 17, 3; 263-270
1231-4005
2354-0133
Pojawia się w:
Journal of KONES
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optimal stopping model with unknown transition probabilities
Autorzy:
Horiguchi, M.
Piunovskiy, A. B.
Powiązania:
https://bibliotekanauki.pl/articles/205727.pdf
Data publikacji:
2013
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
Markov Decision Process (MDP) unknown transition matrices
dynamic programming
Bayesian method
optimal stopping
Opis:
This article concerns the optimal stopping problem for a discrete-time Markov chain with observable states, but with unknown transition probabilities. A stopping policy is graded via the expected total-cost criterion resulting from the non-negative running and terminal costs. The Dynamic Programming method, combined with the Bayesian approach, is developed. A series of explicitly solved meaningful examples illustrates all the theoretical issues.
Źródło:
Control and Cybernetics; 2013, 42, 3; 593-612
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Control design for untimed Petri nets using Markov Decision Processes
Autorzy:
Daoui, C.
Lefebvre, D.
Powiązania:
https://bibliotekanauki.pl/articles/406340.pdf
Data publikacji:
2017
Wydawca:
Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:
discrete event systems
Petri nets
control design
Markov decision process
value iteration algorithm
Opis:
Design of control sequences for discrete event systems (DESs) has been presented modelled by untimed Petri nets (PNs). PNs are well-known mathematical and graphical models that are widely used to describe distributed DESs, including choices, synchronizations and parallelisms. The domains of application include, but are not restricted to, manufacturing systems, computer science and transportation networks. We are motivated by the observation that such systems need to plan their production or services. The paper is more particularly concerned with control issues in uncertain environments when unexpected events occur or when control errors disturb the behaviour of the system. To deal with such uncertainties, a new approach based on discrete time Markov decision processes (MDPs) has been proposed that associates the modelling power of PNs with the planning power of MDPs. Finally, the simulation results illustrate the benefit of our method from the computational point of view.
Źródło:
Operations Research and Decisions; 2017, 27, 4; 27-43
2081-8858
2391-6060
Pojawia się w:
Operations Research and Decisions
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of Markov decision process as a mathematical model of operation and maintenance process
Zastosowanie decyzyjnego procesu Markowa jako matematycznego modelu procesu eksploatacji
Autorzy:
Landowski, B.
Powiązania:
https://bibliotekanauki.pl/articles/359385.pdf
Data publikacji:
2010
Wydawca:
Akademia Morska w Szczecinie. Wydawnictwo AMSz
Tematy:
komunikacja miejska
proces eksploatacji
decyzyjny proces Markowa
urban transport system
operation and maintenance process
Markov decision process
Opis:
This paper presents an example of applying Markov decision process to model and analyse the bus operation and maintenance process within an urban transport system and to forecast the influence of the operation and maintenance strategies realised for the technical objects on the transport system behaviour. Setting the values of the indices describing the process under the analysis is performed on the basis of a computerised simulation of the Markov decision process, being a mathematical model of the technical objects operation and maintenance process. In order to simulate the operation and maintenance process (Markov decision process) and to evaluate the influence of the decisions being made on the course and effectiveness of the process being realised within the study object a simulation algorithm has been elaborated and a computer calculation program has been written. The model presented herein has been created in such a way to assure that it shall be possible to use it in as extensive as possible class of the problems regarding the operation and maintenance of the technical objects.
W artykule przedstawiono przykład zastosowania decyzyjnego procesu Markowa do modelowania i analizy procesu eksploatacji autobusów komunikacji miejskiej oraz prognozowania wpływu realizowanych strategii eksploatacji obiektów technicznych na zachowanie się systemu transportowego. Wyznaczanie wartości wskaźników charakteryzujących analizowany proces realizowane jest na podstawie komputerowej symulacji decyzyjnego procesu Markowa, będącego matematycznym modelem procesu eksploatacji obiektów technicznych. W celu symulacji procesu eksploatacji (decyzyjnego procesu Markowa) i oceny wpływu podejmowanych decyzji na przebieg i efektywność procesu realizowanego w obiekcie badań opracowano algorytm symulacji i napisano komputerowy program obliczeniowy. Przedstawiony w pracy model został skonstruowany w taki sposób, by zapewnić możliwość jego wykorzystania w jak najszerszej klasie problemów związanych z eksploatacją obiektów technicznych.
Źródło:
Zeszyty Naukowe Akademii Morskiej w Szczecinie; 2010, 24 (96); 12-16
1733-8670
2392-0378
Pojawia się w:
Zeszyty Naukowe Akademii Morskiej w Szczecinie
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Optymalizacja zależnego od stanu technicznego utrzymania urządzeń dla dwuskładnikowego systemu szeregowego nie wymagająca z góry ustalonej struktury strategii
Condition-based Maintenance Optimisation without a Predetermined Strategy Structure for a Two-component Series System
Autorzy:
Zhang, Z.
Zhou, Y.
Sun, Y.
Ma, L.
Powiązania:
https://bibliotekanauki.pl/articles/301595.pdf
Data publikacji:
2012
Wydawca:
Polska Akademia Nauk. Polskie Naukowo-Techniczne Towarzystwo Eksploatacyjne PAN
Tematy:
semimarkowski proces decyzyjny
condition-based maintenance
system wieloskładnikowy
semi-Markov decision process
multi-component system
Opis:
Większość badań nad optymalizacją utrzymania systemów wieloskładnikowych bierze pod uwagę jedynie rozkład czasu życia elementów składowych. Kiedy przyjmie się dla systemów wieloskładnikowych strategię utrzymania urządzeń zależną od ich bieżącego stanu technicznego (condition-based maintenance, CBM), struktura strategii staje się złożona w związku z dużą liczbą stanów składowych oraz ich kombinacji. W konsekwencji, często przyjmuje się pewne z góry ustalone struktury strategii utrzymania przed optymalizacją utrzymania systemu wieloskładnikowego w kontekście CBM. Opracowanie takich z góry ustalonych struktur strategii wymaga jednak specjalistycznego doświadczenia, a i tak brak dowodów na optymalność tych strategii. W artykule zaproponowano metodę optymalizacji utrzymania szeregowego systemu dwuskładnikowego, która nie wymaga wcześniej ustalonej struktury strategii. Proponowaną metodę opracowano na podstawie semimarkowskiego procesu decyzyjnego (SMDP). Badanie symulacyjne pokazało, że za pomocą proponowanej metody można ustalać optymalną strategię utrzymania w sposób adaptacyjny dla różnych kosztów utrzymania oraz parametrów procesów degradacyjnych. Za pomocą symulacji badano także optymalną strukturę strategii utrzymania, jako punkt odniesienia dla przyszłych studiów nad optymalizacją systemów wieloskładnikowych.
Most existing research on maintenance optimisation for multi-component systems only considers the lifetime distribution of the components. When the condition-based maintenance (CBM) strategy is adopted for multi-component systems, the strategy structure becomes complex due to the large number of component states and their combinations. Consequently, some predetermined maintenance strategy structures are often assumed before the maintenance optimisation of a multicomponent system in a CBM context. Developing these predetermined strategy structure needs expert experience and the optimality of these strategies is often not proofed. This paper proposed a maintenance optimisation method that does not require any predetermined strategy structure for a two-component series system. The proposed method is developed based on the semi-Markov decision process (SMDP). A simulation study shows that the proposed method can identify the optimal maintenance strategy adaptively for different maintenance costs and parameters of degradation processes. The optimal maintenance strategy structure is also investigated in the simulation study, which provides reference for further research in maintenance optimisation of multi-component systems.
Źródło:
Eksploatacja i Niezawodność; 2012, 14, 2; 120-129
1507-2711
Pojawia się w:
Eksploatacja i Niezawodność
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Predictive Modelling of a Honeypot System Based on a Markov Decision Process and a Partially Observable Markov Decision Process
Autorzy:
Wang, Lidong
Mosher, Reed
Duett, Patti
Falls, Terril
Powiązania:
https://bibliotekanauki.pl/articles/27304921.pdf
Data publikacji:
2023
Wydawca:
NASK - National Research Institute
Tematy:
cybersecurity
honeypot
machine learning
Markov decision process
Q-learning
cyberbezpieczeństwo
uczenie maszynowe
proces decyzyjny Markowa
Opis:
A honeypot is used to attract and monitor attacker activities and capture valuable information that can be used to help practice good cybersecurity. Predictive modelling of a honeypot system based on a Markov decision process (MDP) and a partially observable Markov decision process (POMDP) is performed in this paper. Analyses over a finite planning horizon and an infinite planning horizon for a discounted MDP are respectively conducted. Four methods, including value iteration (VI), policy iteration (PI), linear programming (LP), and Q-learning, are used in the analyses over an infinite planning horizon for the discounted MDP. The results of the various methods are compared to evaluate the validity of the created MDP model and the parameters in the model. The optimal policy to maximise the total expected reward of the states of the honeypot system is achieved, based on the MDP model employed. In the modelling over an infinite planning horizon for the discounted POMDP of the honeypot system, the effects of the observation probability of receiving commands, the probability of attacking the honeypot, the probability of the honeypot being disclosed, and transition rewards on the total expected reward of the honeypot system are studied.
Źródło:
Applied Cybersecurity & Internet Governance; 2023, 2, 1; 1-14
2956-3119
2956-4395
Pojawia się w:
Applied Cybersecurity & Internet Governance
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Markov Decision Process based Model for Performance Analysis an Intrusion Detection System in IoT Networks
Autorzy:
Kalnoor, Gauri
Gowrishankar, -
Powiązania:
https://bibliotekanauki.pl/articles/1839336.pdf
Data publikacji:
2021
Wydawca:
Instytut Łączności - Państwowy Instytut Badawczy
Tematy:
DDoS
intrusion detection
IoT
machine learning
Markov decision process
MDP
Q-learning
NSL-KDD
reinforcement learning
Opis:
In this paper, a new reinforcement learning intrusion detection system is developed for IoT networks incorporated with WSNs. A research is carried out and the proposed model RL-IDS plot is shown, where the detection rate is improved. The outcome shows a decrease in false alarm rates and is compared with the current methodologies. Computational analysis is performed, and then the results are compared with the current methodologies, i.e. distributed denial of service (DDoS) attack. The performance of the network is estimated based on security and other metrics.
Źródło:
Journal of Telecommunications and Information Technology; 2021, 3; 42-49
1509-4553
1899-8852
Pojawia się w:
Journal of Telecommunications and Information Technology
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A Deep Q-Learning Network for ship stowage planning problem
Autorzy:
Shen, Y.
Zhao, N.
Xia, M.
Du, X.
Powiązania:
https://bibliotekanauki.pl/articles/260614.pdf
Data publikacji:
2017
Wydawca:
Politechnika Gdańska. Wydział Inżynierii Mechanicznej i Okrętownictwa
Tematy:
Deep Q-Leaning Network (DQN)
container terminal
ship stowage plan
markov decision process
value function approximation
generalization
Opis:
Ship stowage plan is the management connection of quae crane scheduling and yard crane scheduling. The quality of ship stowage plan affects the productivity greatly. Previous studies mainly focuses on solving stowage planning problem with online searching algorithm, efficiency of which is significantly affected by case size. In this study, a Deep Q-Learning Network (DQN) is proposed to solve ship stowage planning problem. With DQN, massive calculation and training is done in pre-training stage, while in application stage stowage plan can be made in seconds. To formulate network input, decision factors are analyzed to compose feature vector of stowage plan. States subject to constraints, available action and reward function of Q-value are designed. With these information and design, an 8-layer DQN is formulated with an evaluation function of mean square error is composed to learn stowage planning. At the end of this study, several production cases are solved with proposed DQN to validate the effectiveness and generalization ability. Result shows a good availability of DQN to solve ship stowage planning problem.
Źródło:
Polish Maritime Research; 2017, S 3; 102-109
1233-2585
Pojawia się w:
Polish Maritime Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Dynamic programming in constrained Markov decision
Autorzy:
Piunovskiy, A. B.
Powiązania:
https://bibliotekanauki.pl/articles/970861.pdf
Data publikacji:
2006
Wydawca:
Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:
optymalizacja
programowanie dynamiczne
system kolejek
Markov decision process (MDP)
constraints
optimization
dynamic programming
myopic control strategy
queuing system
Opis:
We consider a discounted Markov Decision Process (MDP) supplemented with the requirement that another discounted loss must not exceed a specified value, almost surely. We show that he problem can be reformulated as a standard MDP and solved using the Dynamic Programming approach. An example on a controlled queue is presented. In the last section, we briefly reinforce the connection of the Dynamic Programming approach to another close problem statement and present the corresponding example. Several other types of constraints are discussed, as well.
Źródło:
Control and Cybernetics; 2006, 35, 3; 645-660
0324-8569
Pojawia się w:
Control and Cybernetics
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Bottom-up learning of hierarchical models in a class of deterministic POMDP environments
Autorzy:
Itoh, H.
Fukumoto, H.
Wakuya, H.
Furukawa, T.
Powiązania:
https://bibliotekanauki.pl/articles/330566.pdf
Data publikacji:
2015
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
partially observable system
Markov decision process
hierarchical model
bottom up learning
układ częściowo obserwowalny
decyzyjny proces Markowa
model hierarchiczny
Opis:
The theory of partially observable Markov decision processes (POMDPs) is a useful tool for developing various intelligent agents, and learning hierarchical POMDP models is one of the key approaches for building such agents when the environments of the agents are unknown and large. To learn hierarchical models, bottom-up learning methods in which learning takes place in a layer-by-layer manner from the lowest to the highest layer are already extensively used in some research fields such as hidden Markov models and neural networks. However, little attention has been paid to bottom-up approaches for learning POMDP models. In this paper, we present a novel bottom-up learning algorithm for hierarchical POMDP models and prove that, by using this algorithm, a perfect model (i.e., a model that can perfectly predict future observations) can be learned at least in a class of deterministic POMDP environments.
Źródło:
International Journal of Applied Mathematics and Computer Science; 2015, 25, 3; 597-615
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Reinforcement Learning in Ship Handling
Autorzy:
Łącki, M.
Powiązania:
https://bibliotekanauki.pl/articles/117361.pdf
Data publikacji:
2008
Wydawca:
Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:
Ship Handling
Reinforcement Learning
Machine Learning Techniques
Manoeuvring
Restricted Waters
Markov Decision Process (MDP)
Artificial Neural Network (ANN)
multi-agent environment
Opis:
This paper presents the idea of using machine learning techniques to simulate and demonstrate learning behaviour in ship manoeuvring. Simulated model of ship is treated as an agent, which through environmental sensing learns itself to navigate through restricted waters selecting an optimum trajectory. Learning phase of the task is to observe current state and choose one of the available actions. The agent gets positive reward for reaching destination and negative reward for hitting an obstacle. Few reinforcement learning algorithms are considered. Experimental results based on simulation program are presented for different layouts of possible routes within restricted area.
Źródło:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2008, 2, 2; 157-160
2083-6473
2083-6481
Pojawia się w:
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
An efficient microgrid model based on Markov fuzzy demand-side management
Autorzy:
Jabash Samuel, G. K.
Sivagama Sundari, M. S.
Bhavani, R.
Jasmine Gnanamalar, A.
Powiązania:
https://bibliotekanauki.pl/articles/27311444.pdf
Data publikacji:
2023
Wydawca:
Polska Akademia Nauk. Czasopisma i Monografie PAN
Tematy:
smart grid
fuzzy Markov decision process
power scheduling
operating cost
nonlinear model predictive control
inteligentna sieć
planowanie mocy
koszt operacyjny
proces decyzyjny Markowa rozmyty
regulator predykcyjny nieliniowego modelu
Opis:
Today’s electricity management mainly focuses on smart grid implementation for better power utilization. Supply-demand balancing, and high operating costs are still considered the most challenging factors in the smart grid. To overcome this drawback, a Markov fuzzy real-time demand-side manager (MARKOV FRDSM) is proposed to reduce the operating cost of the smart grid system and maintain a supply-demand balance in an uncertain environment. In addition, a non-linear model predictive controller (NMPC) is designed to give a global solution to the non-linear optimization problem with real-time requirements based on the uncertainties over the forecasted load demands and current load status. The proposed MARKOV FRDSM provides a faster scale power allocation concerning fuzzy optimization and deals with uncertainties and imprecision. The implemented results show the proposed MARKOV FRDSM model reduces the cost of operation of the microgrid by 1.95%, 1.16%, and 1.09% than the existing method such as differential evolution and real coded genetic algorithm and maintains the supply-demand balance in the microgrid.
Źródło:
Bulletin of the Polish Academy of Sciences. Technical Sciences; 2023, 71, 3; art. no. e145569
0239-7528
Pojawia się w:
Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:
Biblioteka Nauki
Artykuł
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