Analysis of the Possibilities of the Evolutionary Algorithm to Improve the Neural Model of the TGE S.A. Day Ahead Market System Using Selected Programming Environments.
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| Title: | Analysis of the Possibilities of the Evolutionary Algorithm to Improve the Neural Model of the TGE S.A. Day Ahead Market System Using Selected Programming Environments. |
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| Authors: | Tchórzewski, Jerzy Rudolf, Zakrzewski, Maciej |
| Source: | Studia Informatica. System & information technology; 2024, Vol. 31 Issue 2, p87-102, 16p |
| Subject Terms: | ARTIFICIAL intelligence, ARTIFICIAL neural networks, PROGRAMMING languages, EVOLUTIONARY algorithms, PYTHON programming language |
| Abstract: | The article contains selected research results regarding the analysis of the possibility of using the Evolutionary Algorithm to improve neural models of intelligent systems using selected programming environments. Choosing an appropriate program ming language is one of the basic activities in the process of implementing complex algorithms, which include methods of artificial neural networks and evolutionary algorithms. Due to the fact that the object of the researchwas an intelligent Day Ahead Market system operating on the Polish Power Exchange and the modeling methods were artificial neural networks and evolutionary algorithms, it was decided to use very high-level programming languages such as Python, Matlab and C# for implementation and associated development environments. It turned out, among other things, that each of these languages and programming environments has its advantages and disadvantages, but all of them are very useful due to their useful syntax and rich included libraries. A thorough analysis of the implementation shows, among other things, that the choice of programming language affects the efficiency, speed and quality of the obtained implementations of system models. Against this background, the advantages and disadvantages of individual programming languages are shown, especially in the context of implementing evolutionary algorithms. The research results indicate directions for selecting an appropriate programming language and the associated programming environment for system modeling using artificial neural networks and evolutionary algorithms. In addition, the method of analysis, as well as the method of modeling and implementation was shown on the example of a specific system, which was the Day Ahead Market system of TGE S.A. [ABSTRACT FROM AUTHOR] |
| Copyright of Studia Informatica. System & information technology is the property of Siedlce University of Natural Sciences & Humanities and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Complementary Index |
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| Header | DbId: edb DbLabel: Complementary Index An: 184780021 RelevancyScore: 974 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 973.58447265625 |
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| Items | – Name: Title Label: Title Group: Ti Data: Analysis of the Possibilities of the Evolutionary Algorithm to Improve the Neural Model of the TGE S.A. Day Ahead Market System Using Selected Programming Environments. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Tchórzewski%2C+Jerzy+Rudolf%22">Tchórzewski, Jerzy Rudolf</searchLink><br /><searchLink fieldCode="AR" term="%22Zakrzewski%2C+Maciej%22">Zakrzewski, Maciej</searchLink> – Name: TitleSource Label: Source Group: Src Data: Studia Informatica. System & information technology; 2024, Vol. 31 Issue 2, p87-102, 16p – Name: Subject Label: Subject Terms Group: Su Data: <searchLink fieldCode="DE" term="%22ARTIFICIAL+intelligence%22">ARTIFICIAL intelligence</searchLink><br /><searchLink fieldCode="DE" term="%22ARTIFICIAL+neural+networks%22">ARTIFICIAL neural networks</searchLink><br /><searchLink fieldCode="DE" term="%22PROGRAMMING+languages%22">PROGRAMMING languages</searchLink><br /><searchLink fieldCode="DE" term="%22EVOLUTIONARY+algorithms%22">EVOLUTIONARY algorithms</searchLink><br /><searchLink fieldCode="DE" term="%22PYTHON+programming+language%22">PYTHON programming language</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The article contains selected research results regarding the analysis of the possibility of using the Evolutionary Algorithm to improve neural models of intelligent systems using selected programming environments. Choosing an appropriate program ming language is one of the basic activities in the process of implementing complex algorithms, which include methods of artificial neural networks and evolutionary algorithms. Due to the fact that the object of the researchwas an intelligent Day Ahead Market system operating on the Polish Power Exchange and the modeling methods were artificial neural networks and evolutionary algorithms, it was decided to use very high-level programming languages such as Python, Matlab and C# for implementation and associated development environments. It turned out, among other things, that each of these languages and programming environments has its advantages and disadvantages, but all of them are very useful due to their useful syntax and rich included libraries. A thorough analysis of the implementation shows, among other things, that the choice of programming language affects the efficiency, speed and quality of the obtained implementations of system models. Against this background, the advantages and disadvantages of individual programming languages are shown, especially in the context of implementing evolutionary algorithms. The research results indicate directions for selecting an appropriate programming language and the associated programming environment for system modeling using artificial neural networks and evolutionary algorithms. In addition, the method of analysis, as well as the method of modeling and implementation was shown on the example of a specific system, which was the Day Ahead Market system of TGE S.A. [ABSTRACT FROM AUTHOR] – Name: Abstract Label: Group: Ab Data: <i>Copyright of Studia Informatica. System & information technology is the property of Siedlce University of Natural Sciences & Humanities and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.) |
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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.34739/si.2024.31.07 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 87 Subjects: – SubjectFull: ARTIFICIAL intelligence Type: general – SubjectFull: ARTIFICIAL neural networks Type: general – SubjectFull: PROGRAMMING languages Type: general – SubjectFull: EVOLUTIONARY algorithms Type: general – SubjectFull: PYTHON programming language Type: general Titles: – TitleFull: Analysis of the Possibilities of the Evolutionary Algorithm to Improve the Neural Model of the TGE S.A. Day Ahead Market System Using Selected Programming Environments. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Tchórzewski, Jerzy Rudolf – PersonEntity: Name: NameFull: Zakrzewski, Maciej IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 07 Text: 2024 Type: published Y: 2024 Identifiers: – Type: issn-print Value: 17312264 Numbering: – Type: volume Value: 31 – Type: issue Value: 2 Titles: – TitleFull: Studia Informatica. System & information technology Type: main |
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