Wszystkie pola: self-adaptive system - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A synthesis of adaptive, low-power real-time embedded systems for ARM big.LITTLE technology
Autorzy:: Ciopiński, L.
Deniziak, S.
Powiązania:: https://bibliotekanauki.pl/articles/114109.pdf
Data publikacji:: 2015
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: self-adaptive system
real-time embedded system
adaptive scheduler
developmental genetic programming
ARM big.LITTLE
Opis:: In this paper, we present a method of a synthesis of adaptive schedulers for real-time embedded systems. We assume that the system is implemented using a multi-core embedded processor with low-power processing capabilities. First, the developmental genetic programming is used to generate the scheduler and the initial schedule. Then during the system execution, the scheduler modifies the schedule whenever the execution time of the recently finished task has been shorter or longer than expected. The goal of rescheduling is to minimize the power consumption while all time constraints will be satisfied. We present a real-life example as well as some experimental results showing the advantages of the method.
Źródło:: Measurement Automation Monitoring; 2015, 61, 7; 340-342
2450-2855
Pojawia się w:: Measurement Automation Monitoring
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Model and implementation of a self-adaptive social navigation system for public information systems
Autorzy:: Ajanovski, Vangel V.
Powiązania:: https://bibliotekanauki.pl/articles/431856.pdf
Data publikacji:: 2013
Wydawca:: Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu
Tematy:: course management systems
curricula recommendations
social navigation
Opis:: This paper presents a model of a generic navigation system of a public information system, that can be used to improve the structure and content of the information repository via self-organization capabilities based on social navigation and interaction. This model has the primary goal of establishing a generic and adaptive social-based self-structuring navigation system. The model integrates the concepts of social navigation, interaction and self-adaptivity in a feedback control loop. The model focuses on self-adaptivity and includes elements of social navigation in all parts of the system, which enables the implementations based on this model to get social adaptability based on user actions individually, but also as a social environment, in every possible aspect of the functioning of the system. The introduced feedback control loop gives the possibility for further autonomous improvements of the organization of the information. As a proof of concept, this model is then used to build a prototype implementation solution that can be used to guide students towards better course selection during the semester enrolment process.
Źródło:: Informatyka Ekonomiczna; 2013, 3(29); 9-29
1507-3858
Pojawia się w:: Informatyka Ekonomiczna
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Bringing introspection into BlobSeer: Towards a self-adaptive distributed data management system
Autorzy:: Carpen-Amarie, A.
Costan, A.
Cai, J.
Antoniu, G.
Bougé, L.
Powiązania:: https://bibliotekanauki.pl/articles/907796.pdf
Data publikacji:: 2011
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: rozproszony system komputerowy
gospodarka magazynowa
zarządzanie danymi
distributed system
storage management
large-scale system
monitoring
introspection
Opis:: Introspection is the prerequisite of autonomic behavior, the first step towards performance improvement and resource usage optimization for large-scale distributed systems. In grid environments, the task of observing the application behavior is assigned to monitoring systems. However, most of them are designed to provide general resource information and do not consider specific information for higher-level services. More precisely, in the context of data-intensive applications, a specific introspection layer is required to collect data about the usage of storage resources, data access patterns, etc. This paper discusses the requirements for an introspection layer in a data management system for large-scale distributed infrastructures. We focus on the case of BlobSeer, a large-scale distributed system for storing massive data. The paper explains why and how to enhance BlobSeer with introspective capabilities and proposes a three-layered architecture relying on the MonALISA monitoring framework. We illustrate the autonomic behavior of BlobSeer with a self-configuration component aiming to provide storage elasticity by dynamically scaling the number of data providers. Then we propose a preliminary approach for enabling self-protection for the BlobSeer system, through a malicious client detection component. The introspective architecture has been evaluated on the Grid'5000 testbed, with experiments that prove the feasibility of generating relevant information related to the state and behavior of the system.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2011, 21, 2; 229-242
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Self-adaptation of parameters in a learning classifier system ensemble machine
Autorzy:: Troć, M.
Unold, O.
Powiązania:: https://bibliotekanauki.pl/articles/907767.pdf
Data publikacji:: 2010
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: komputerowe uczenie się
system klasyfikujący
sterowanie adaptacyjne
sterowanie parametryczne
machine learning
extended classifier system
self-adaptation
adaptive parameter control
Opis:: Self-adaptation is a key feature of evolutionary algorithms (EAs). Although EAs have been used successfully to solve a wide variety of problems, the performance of this technique depends heavily on the selection of the EA parameters. Moreover, the process of setting such parameters is considered a time-consuming task. Several research works have tried to deal with this problem; however, the construction of algorithms letting the parameters adapt themselves to the problem is a critical and open problem of EAs. This work proposes a novel ensemble machine learning method that is able to learn rules, solve problems in a parallel way and adapt parameters used by its components. A self-adaptive ensemble machine consists of simultaneously working extended classifier systems (XCSs). The proposed ensemble machine may be treated as a meta classifier system. A new self-adaptive XCS-based ensemble machine was compared with two other XCS-based ensembles in relation to one-step binary problems: Multiplexer, One Counts, Hidden Parity, and randomly generated Boolean functions, in a noisy version as well. Results of the experiments have shown the ability of the model to adapt the mutation rate and the tournament size. The results are analyzed in detail.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2010, 20, 1; 157-174
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 5.

Tytuł:: Predictive neural network in multipurpose self-tuning controller
Autorzy:: Bondar, Oleksiy
Powiązania:: https://bibliotekanauki.pl/articles/386771.pdf
Data publikacji:: 2020
Wydawca:: Politechnika Białostocka. Oficyna Wydawnicza Politechniki Białostockiej
Tematy:: artificial neural network
adaptive regulator
backpropagation algorithm
system modelling
Opis:: A very important problem in designing of controlling systems is to choose the right type of architecture of controller. And it is always a compromise between accuracy, difficulty in setting up, technical complexity and cost, expandability, flexibility and so on. In this paper, multipurpose adaptive controller with implementation of artificial neural network is offered as an answer to a wide range of tasks related to regulation. The effectiveness of the approach is demonstrated by the example of an adaptive thermostat. It also compares its capabilities with those of classic PID controller. The core of this approach is the use of an artificial neural network capable of predicting the behaviour of controlled object within its known range of parameters. Since such a network, being trained, is a model of a regulated system with arbitrary precision, it can be analysed to make optimal management decisions at the moment or in a number of steps. Network learning algorithm is backpropagation and its modified version is used to analyse an already trained network in order to find the optimal solution for the regulator. Software implementation, such as graphical user interface, routines related to neural network and many other, is done using Java programming language and Processing open-source integrated development environment.
Źródło:: Acta Mechanica et Automatica; 2020, 14, 2; 114-120
1898-4088
2300-5319
Pojawia się w:: Acta Mechanica et Automatica
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 6.

Tytuł:: Self-configuring hybrid evolutionary algorithm for fuzzy imbalanced classification with adaptive instance selection
Autorzy:: Stanovov, V.
Semenkin, E.
Semenkina, O.
Powiązania:: https://bibliotekanauki.pl/articles/91578.pdf
Data publikacji:: 2016
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: fuzzy classification
instance selection
genetic fuzzy system
self-configuration
Opis:: A novel approach for instance selection in classification problems is presented. This adaptive instance selection is designed to simultaneously decrease the amount of computation resources required and increase the classification quality achieved. The approach generates new training samples during the evolutionary process and changes the training set for the algorithm. The instance selection is guided by means of changing probabilities, so that the algorithm concentrates on problematic examples which are difficult to classify. The hybrid fuzzy classification algorithm with a self-configuration procedure is used as a problem solver. The classification quality is tested upon 9 problem data sets from the KEEL repository. A special balancing strategy is used in the instance selection approach to improve the classification quality on imbalanced datasets. The results prove the usefulness of the proposed approach as compared with other classification methods.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2016, 6, 3; 173-188
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 7.

Tytuł:: Novel Fuzzy-Based Self-Adaptive Single Neuron PID Load Frequency Controller for Power System
Autorzy:: Eissa, M. Abdullah
Powiązania:: https://bibliotekanauki.pl/articles/1193688.pdf
Data publikacji:: 2019
Wydawca:: Politechnika Wrocławska. Oficyna Wydawnicza Politechniki Wrocławskiej
Tematy:: power system
load frequency
Intelligent Control
PID
Single Neuron
Opis:: This paper proposes a newly adaptive single-neuron proportional integral derivative (SNPID) controller that uses fuzzy logic as an adaptive system. The main problem of the classical controller is lacking the required robustness against disturbers, measurement noise in industrial applications. The new formula of the proposed controller helps in fixing this problem based on the fuzzy logic technique. In addition, the genetic algorithm (GA) is used to optimize parameters of the SNPID controller. Because of the high demands on the availability and efficiency of electrical power production, the design of robust load-frequency controller is becoming increasingly important due to its potential in increasing the reliability, maintainability and safety of power systems. So, the proposed controller has been applied for load-frequency control (LFC) of a single-area power system. The effectiveness of the proposed SNPID controller has been compared with the conventional controllers. The simulation results show that the proposed controller approach provides better damping of oscillations with a smaller settling time. This confirms its superiority against its counterparts. In addition, the results show the robustness of the proposed controller against the parametric variation of the system.
Źródło:: Power Electronics and Drives; 2019, 4, 39; 141-150
2451-0262
2543-4292
Pojawia się w:: Power Electronics and Drives
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 8.

Tytuł:: Indirect adaptive controller based on a self-structuring fuzzy system for nonlinear modeling and control
Autorzy:: Qi, R.
Brdyś, M. A.
Powiązania:: https://bibliotekanauki.pl/articles/929998.pdf
Data publikacji:: 2009
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: sterowanie rozmyte
model rozmyty
stabilność
fuzzy control
self-structuring fuzzy model
on-line modeling
stability
Opis:: In this paper, a unified nonlinear modeling and control scheme is presented. A self-structuring Takagi-Sugeno (T-S) fuzzy model is used to approximate the unknown nonlinear plant based on I/O data collected on-line. Both the structure and the parameters of the T-S fuzzy model are updated by an on-line clustering method and a recursive least squares estimation (RLSE) algorithm. The rules of the fuzzy model can be added, replaced or deleted on-line to allow a more flexible and compact model structure. The overall controller consists of an indirect adaptive controller and a supervisory controller. The former is the dominant controller, which maintains the closed-loop stability when the fuzzy system is a good approximation of the nonlinear plant. The latter is an auxiliary controller, which is activated when the tracking error reaches the boundary of a predefined constraint set. It is proven that global stability of the closed-loop system is guaranteed in the sense that all the closed-loop signals are bounded and simulation examples demonstrate the effectiveness of the proposed control scheme.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2009, 19, 4; 619-630
1641-876X
2083-8492
Pojawia się w:: International Journal of Applied Mathematics and Computer Science
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 9.

Tytuł:: A Novel System Architecture for an Improved Self-care Solution – Conceptual Design and Key Components
Autorzy:: Santos, Patrick
Ramos, Jorge
Seabra, Eduardo
Castro, José
Powiązania:: https://bibliotekanauki.pl/articles/1839314.pdf
Data publikacji:: 2020
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: adaptive interfaces
big data analytics
data mining
user profiling
Opis:: The high penetration rate that mobile devices enjoy in to day’s society has facilitated the creation of new digital services, with those offered by operators and content providers standing out. However, even this has failed to encourage consumers to express positive opinions on telecommunication services, especially when compared with other sectors. One of the main reasons of the mistrust shown is the low level of quality of customer service provided an area that generates high costs for the operators themselves, due to the high number of people employed at call centers in order to handle the volume of calls received. To face these challenges, operators launched self-care applications in order to provide customers with a tool that would allow them to autonomously manage the services they have subscribed. In this paper, we present an architecture that provides customized information to customers – a solution that is separate from mobile operating systems and communication technologies.
Źródło:: Journal of Telecommunications and Information Technology; 2020, 4; 88-97
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 10.

Tytuł:: Using intelligent programming paradigm in CAD systems
Wykorzystanie paradygmatu programowania inteligentnego w systemach projektowania wspomaganego komputerowo
Autorzy:: Rogoza, V.
Powiązania:: https://bibliotekanauki.pl/articles/972190.pdf
Data publikacji:: 2009
Wydawca:: Stowarzyszenie Inżynierów i Techników Mechaników Polskich
Tematy:: symulacja adaptacyjna
samoorganizacja
systemy projektowania wspomaganego komputerowo
projektowanie układów scalonych o dużym stopniu scalenia
adaptive simulation
self-organization
CAD system
VLSI design
Opis:: The intelligent programming paradigm is considered as a concept that combines two basic properties of a sophisticated software, namely: adaptive tuning and evolutionary self-organization. Such properties can be realized at the algorithmic level using object-oriented programming languages.
Paradygmat programowania inteligentnego jest rozpatrywany jako koncepcja, która łączy w sobie dwie zasadnicze własności skomplikowanego oprogramowania, mianowicie: adaptacyjne dostrajanie modeli i ich samoorganizacja ewolucyjna. W artykule pokazano, że omówione właściwości mogą być realizowane z wykorzystaniem specjalnych algorytmów syntezy modeli składników obiektów ulegających symulacji oraz paradygmatu programowania obiektowego.
Źródło:: Pomiary Automatyka Kontrola; 2009, R. 55, nr 10, 10; 847-850
0032-4140
Pojawia się w:: Pomiary Automatyka Kontrola
Dostawca treści:: Biblioteka Nauki

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