Quantum-inspired method of neural modeling of the day-ahead market of the Polish electricity exchange
The paper presents selected elements of a modelling methodology involving quantization, quantum calculations and dequantization on the example of the neural model of the Day-Ahead Market of the Polish Electricity Exchange. Based on the fundamental assumptions of quantum computing, a new method has b...
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Veröffentlicht in: | Control and Cybernetics 2021-07, Vol.50 (3), p.383-399 |
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description | The paper presents selected elements of a modelling methodology involving quantization, quantum calculations and dequantization on the example of the neural model of the Day-Ahead Market of the Polish Electricity Exchange. Based on the fundamental assumptions of quantum computing, a new method has been proposed here of converting the real numbers in decimal notation into quantum mixed numbers using the probability modules of quantum mixed number and the principle of superposition, along with a new method of quantum calculations using linear algebra and vectormatrix calculus, and the Artificial Neural Network was taught accordingly. Dequantization of quantum mixed numbers to real numbers in decimal notation using the new method of dequantization has been proposed as well. The operation of the methods introduced was shown on numerical examples. |
doi_str_mv | 10.2478/candc-2021-0023 |
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The operation of the methods introduced was shown on numerical examples.</description><subject>Algebra</subject><subject>artificial neural networks</subject><subject>day-ahead market</subject><subject>dequantization with ANN</subject><subject>Methods</subject><subject>neural modeling</subject><subject>Neural networks</subject><subject>Polish Electricity Exchange</subject><subject>quantum computing</subject><subject>quantum-inspired method</subject><subject>system quantization</subject><issn>2720-4278</issn><issn>0324-8569</issn><issn>2720-4278</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><recordid>eNp1kUFP3DAQRiPUSkWUc6-ReuIQsD1JnD1wQIgWJKQWCmdrYo8Tt4mDbEdl_z1Jl0pdicqHGX16z4f5suwTZ6eilM2ZRm90IZjgBWMCDrJDIQUrSiGbd__sH7LjGF3LSglQS2gOM7qb0ad5LJyPTy6QyUdK_WTyyeae5oBDPk6GBue7NUo95Qa3BfaEC4rhF6W_-fdpcLHPaSCdgtMubXN61j36jj5m7y0OkY5f51H2-OXq4fK6uP329eby4rbQAmooqGqk1LWRYCzoinPJTcORY6WRV7w1dauh5XbDpS1bJuWmtmUlW0TLRUslHGWfd_92OJBy3k4poB5d1OpCQr2RwGGlTt-glmdodHryZN2S7wkne8LCJHpOHc4xqpsf9_vs2Y7VYYoxkFVPwS2H2irO1NqV-tOVWrtSa1eLcb4zfuOQKBjqwrxdFvVzmoNfzvU_s2IADcAL-nWbIg</recordid><startdate>20210701</startdate><enddate>20210701</enddate><creator>Tchorzewsk, Jerzy</creator><creator>Rucinski, Dariusz</creator><general>Sciendo</general><general>Instytut Badan Systemowych Polskiej Akademii Nauk</general><scope>AAYXX</scope><scope>CITATION</scope><scope>ISR</scope></search><sort><creationdate>20210701</creationdate><title>Quantum-inspired method of neural modeling of the day-ahead market of the Polish electricity exchange</title><author>Tchorzewsk, Jerzy ; Rucinski, Dariusz</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2363-e5877c6d73df3c51171d81a1a5ca151bd6bc3b1f917f4b07796f457baaf12be43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Algebra</topic><topic>artificial neural networks</topic><topic>day-ahead market</topic><topic>dequantization with ANN</topic><topic>Methods</topic><topic>neural modeling</topic><topic>Neural networks</topic><topic>Polish Electricity Exchange</topic><topic>quantum computing</topic><topic>quantum-inspired method</topic><topic>system quantization</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tchorzewsk, Jerzy</creatorcontrib><creatorcontrib>Rucinski, Dariusz</creatorcontrib><collection>CrossRef</collection><collection>Gale In Context: Science</collection><jtitle>Control and Cybernetics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tchorzewsk, Jerzy</au><au>Rucinski, Dariusz</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantum-inspired method of neural modeling of the day-ahead market of the Polish electricity exchange</atitle><jtitle>Control and Cybernetics</jtitle><date>2021-07-01</date><risdate>2021</risdate><volume>50</volume><issue>3</issue><spage>383</spage><epage>399</epage><pages>383-399</pages><issn>2720-4278</issn><issn>0324-8569</issn><eissn>2720-4278</eissn><abstract>The paper presents selected elements of a modelling methodology involving quantization, quantum calculations and dequantization on the example of the neural model of the Day-Ahead Market of the Polish Electricity Exchange. 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subjects | Algebra artificial neural networks day-ahead market dequantization with ANN Methods neural modeling Neural networks Polish Electricity Exchange quantum computing quantum-inspired method system quantization |
title | Quantum-inspired method of neural modeling of the day-ahead market of the Polish electricity exchange |
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