Temat: optimal parameters - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: A parametric testing of the firefly algorithm in the determination of the optimal osmotic drying parameters of mushrooms
Autorzy:: Yeomans, J.S.
Powiązania:: https://bibliotekanauki.pl/articles/91745.pdf
Data publikacji:: 2014
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: Firefly Algorithm
FA
osmotic dehydration
mushroom
dehydration model
surface technique
mathematical programming
optimal process parameters
Opis:: The Firefly Algorithm (FA) is employed to determine the optimal parameter settings in a case study of the osmotic dehydration process of mushrooms. In the case, the functional form of the dehydration model is established through a response surface technique and the resulting mathematical programming is formulated as a non-linear goal programming model. For optimization purposes, a computationally efficient, FA-driven method is used and the resulting optimal process parameters are shown to be superior to those from previous approaches. The final section of this study provides a computational experimentation performed on the FA to analyze its relative sensitivity over a range of the two key parameters that most influence its running time.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2014, 4, 4; 257-256
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Optimal training strategies for locally recurrent neural networks
Autorzy:: Patan, K.
Patan, M.
Powiązania:: https://bibliotekanauki.pl/articles/1396735.pdf
Data publikacji:: 2011
Wydawca:: Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:: training schedule
neural network
Fisher information matrix
network parameters
optimal experimental design
convex optimization theory
Opis:: The problem of determining an optimal training schedule for locally recurrent neural network is discussed. Specifically, the proper choice of the most informative measurement data guaranteeing the reliable prediction of neural network response is considered. Based on a scalar measure of performance defined on the Fisher information matrix related to the network parameters, the problem was formulated in terms of optimal experimental design. Then, its solution can be readily achieved via adaptation of effective numerical algorithms based on the convex optimization theory. Finally, some illustrative experiments are provided to verify the presented approach.
Źródło:: Journal of Artificial Intelligence and Soft Computing Research; 2011, 1, 2; 103-114
2083-2567
2449-6499
Pojawia się w:: Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:: Biblioteka Nauki

Artykuł

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