Temat: deterministic annealing - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Neuro-fuzzy modelling based on a deterministic annealing approach
Autorzy:: Czabański, R.
Powiązania:: https://bibliotekanauki.pl/articles/908442.pdf
Data publikacji:: 2005
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: system rozmyty
sieć neuronowa
ekstrakcja reguł
fuzzy systems
neural networks
neuro-fuzzy systems
rules extraction
deterministic annealing
prediction
Opis:: This paper introduces a new learning algorithm for artificial neural networks, based on a fuzzy inference system ANBLIR. It is a computationally effective neuro-fuzzy system with parametrized fuzzy sets in the consequent parts of fuzzy if-then rules, which uses a conjunctive as well as a logical interpretation of those rules. In the original approach, the estimation of unknown system parameters was made by means of a combination of both gradient and least-squares methods. The novelty of the learning algorithm consists in the application of a deterministic annealing optimization method. It leads to an improvement in the neuro-fuzzy modelling performance. To show the validity of the introduced method, two examples of application concerning chaotic time series prediction and system identification problems are provided.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2005, 15, 4; 561-576
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: 2.

Tytuł:: Extraction of fuzzy rules using deterministic annealing integrated with ε-insensitive learning
Autorzy:: Czabański, R.
Powiązania:: https://bibliotekanauki.pl/articles/908395.pdf
Data publikacji:: 2006
Wydawca:: Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:: system rozmyty
sieć neuronowa
sieć neuronowa rozmyta
ekstrakcja reguł
fuzzy systems
neural networks
neuro-fuzzy systems
rules extraction
deterministic annealing
Opis:: A new method of parameter estimation for an artificial neural network inference system based on a logical interpretation of fuzzy if-then rules (ANBLIR) is presented. The novelty of the learning algorithm consists in the application of a deterministic annealing method integrated with ε-insensitive learning. In order to decrease the computational burden of the learning procedure, a deterministic annealing method with a “freezing” phase and ε-insensitive learning by solving a system of linear inequalities are applied. This method yields an improved neuro-fuzzy modeling quality in the sense of an increase in the generalization ability and robustness to outliers. To show the advantages of the proposed algorithm, two examples of its application concerning benchmark problems of identification and prediction are considered.
Źródło:: International Journal of Applied Mathematics and Computer Science; 2006, 16, 3; 357-372
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: 3.

Tytuł:: An adaptive stochastic optimization method for medical registration problem
Autorzy:: Król, Z.
Powiązania:: https://bibliotekanauki.pl/articles/333559.pdf
Data publikacji:: 2004
Wydawca:: Uniwersytet Śląski. Wydział Informatyki i Nauki o Materiałach. Instytut Informatyki. Zakład Systemów Komputerowych
Tematy:: registration
matching
optimization
simulated annealing
similarity measure
non-deterministic methods
cooling schedule
tomographic data
rejestracja
optymalizacja
wyżarzanie
miara podobieństwa
metody niedeterministyczne
chłodzenie
dane tomograficzne
Opis:: This paper presents a methodology that addresses important issues concerned with the optimization of the misregistration measures in the volumetric medical data registration problem. Our registration framework uses robust simulated annealing method to handle multiple local minima of the cost function. Our efforts have been centred on obtaining a reliable, efficient and generally applicable method to solve such optimization problems. This has been accomplished through developing an adaptive cooling schedule for the simulated annealing method. The proposed method is very reliable for the estimation of the global minimum in the optimization of objective functions with highly differentiated search space landscapes. We present the detailed description of the method as well as discussion of its advantages and disadvantages.
Źródło:: Journal of Medical Informatics & Technologies; 2004, 7; MIP79-88
1642-6037
Pojawia się w:: Journal of Medical Informatics & Technologies
Dostawca treści:: Biblioteka Nauki

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