Autor: Kotlarz, Piotr - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: An Expert System for Automatic Classiﬁcation of Sound Signals
Autorzy:: Tyburek, Krzysztof
Kotlarz, Piotr
Powiązania:: https://bibliotekanauki.pl/articles/307799.pdf
Data publikacji:: 2020
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: audio descriptors
bird species
fuzzy classification of audio signals
MPEG-7
spectral features of sound
Opis:: In this paper, we present the results of research focusing on methods for recognition/classiﬁcation of audio signals. We consider the results of the research project to serve as a basis for the main module of a hybrid expert system currently under development. In our earlier studies, we conducted research on the eﬀectiveness of three classiﬁers: fuzzy classiﬁer, neural classiﬁer and WEKA system for reference data. In this project, a particular emphasis was placed on ﬁne-tuning the fuzzy classiﬁer model and on identifying neural classiﬁer applications, taking into account new neural networks that we have not studied so far in connection with sounds classiﬁcation methods.
Źródło:: Journal of Telecommunications and Information Technology; 2020, 2; 86-90
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 2.

Tytuł:: Fuzzy-based Description of Computational Complexity of Central Nervous Systems
Autorzy:: Prokopowicz, Piotr
Mikołajewski, Dariusz
Tyburek, Krzysztof
Kotlarz, Piotr
Powiązania:: https://bibliotekanauki.pl/articles/309535.pdf
Data publikacji:: 2020
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: cognitive deficit
cognitive functions
computational simulation
fuzzy descriptors
Opis:: Computational intelligence algorithms are currently capable of dealing with simple cognitive processes, but still remain inefficient compared with the human brain’s ability to learn from few exemplars or to analyze problems that have not been deﬁned in an explicit manner. Generalization and decision-making processes typically require an uncertainty model that is applied to the decision options while relying on the probability approach. Thus, models of such cognitive functions usually interact with reinforcement-based learning to simplify complex problems. Decision-makers are needed to choose from the decision options that are available, in order to ensure that the decision-makers’ choices are rational. They maximize the subjective overall utility expected, given by the outcomes in diﬀerent states and weighted with subjective beliefs about the occurrence of those states. Beliefs are captured by probabilities and new information is incorporated using the Bayes’ law. Fuzzy-based models described in this paper propose a diﬀerent – they may serve as a point of departure for a family of novel methods enabling more effective and neurobiologically reliable brain simulation that is based on fuzzy logic techniques and that turns out to be useful in both basic and applied sciences. The approach presented provides a valuable insight into understanding the aforementioned processes, doing that in a descriptive, fuzzy-based manner, without presenting a complex analysis.
Źródło:: Journal of Telecommunications and Information Technology; 2020, 3; 57-66
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 3.

Tytuł:: Intelligent system supporting technological process planning for machining and 3D printing
Autorzy:: Rojek, Izabela
Mikołajewski, Dariusz
Kotlarz, Piotr
Macko, Marek
Kopowski, Jakub
Powiązania:: https://bibliotekanauki.pl/articles/2090703.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: artificial intelligence
AI
intelligent system
technological process
machining
3D printing
sztuczna inteligencja
system inteligentny
proces technologiczny
obróbka skrawaniem
druk 3D
Opis:: The study aimed to develop a system supporting technological process planning for machining and 3D printing. Such a system should function similarly to the way human experts act in their fields of expertise and should be capable of gathering the necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods and their significant effectiveness in supporting technological process planning. The purpose of this article is to show an intelligent system that includes knowledge, models, and procedures supporting the company’s employees as part of machining and 3D printing. Few works are combining these two types of processing. Nowadays, however, these two types of processing overlap each other into a common concept of hybrid processing. Therefore, in the opinion of the authors, such a comprehensive system is necessary. The system-embedded knowledge takes the form of neural networks, decision trees, and facts. The system is presented using the example of a real enterprise. The intelligent expert system is intended for process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise and are not very familiar with its machinery and other means of production.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; e136722, 1--8
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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Skocz do pozycji: 4.

Tytuł:: Intelligent system supporting technological process planning for machining and 3D printing
Autorzy:: Rojek, Izabela
Mikołajewski, Dariusz
Kotlarz, Piotr
Macko, Marek
Kopowski, Jakub
Powiązania:: https://bibliotekanauki.pl/articles/2173593.pdf
Data publikacji:: 2021
Wydawca:: Polska Akademia Nauk. Czytelnia Czasopism PAN
Tematy:: artificial intelligence
AI
intelligent system
technological process
machining
3D printing
sztuczna inteligencja
system inteligentny
proces technologiczny
obróbka skrawaniem
druk 3D
Opis:: The study aimed to develop a system supporting technological process planning for machining and 3D printing. Such a system should function similarly to the way human experts act in their fields of expertise and should be capable of gathering the necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods and their significant effectiveness in supporting technological process planning. The purpose of this article is to show an intelligent system that includes knowledge, models, and procedures supporting the company’s employees as part of machining and 3D printing. Few works are combining these two types of processing. Nowadays, however, these two types of processing overlap each other into a common concept of hybrid processing. Therefore, in the opinion of the authors, such a comprehensive system is necessary. The system-embedded knowledge takes the form of neural networks, decision trees, and facts. The system is presented using the example of a real enterprise. The intelligent expert system is intended for process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise and are not very familiar with its machinery and other means of production.
Źródło:: Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 2; art. no. e136722
0239-7528
Pojawia się w:: Bulletin of the Polish Academy of Sciences. Technical Sciences
Dostawca treści:: Biblioteka Nauki

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