DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS
A successful experiment has been done to train the neural network to determine the drum mills’engine capacity by using the program „QwikNet 2.23”. As a result we get a trained neural network with amaximum error of 1.00619.10-5 which can be used for assessing the capacity of the electric motors of dr...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Academica Brancusi
2013-05-01
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| Series: | Fiabilitate şi Durabilitate |
| Subjects: | |
| Online Access: | http://www.utgjiu.ro/rev_mec/mecanica/pdf/2013-01.Supliment/61_Teodora%20Hristova,%20Ivan%20Minin.pdf |
| _version_ | 1828385028294311936 |
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| author | Teodora HRISTOVA Ivan MININ |
| author_facet | Teodora HRISTOVA Ivan MININ |
| author_sort | Teodora HRISTOVA |
| collection | DOAJ |
| description | A successful experiment has been done to train the neural network to determine the drum mills’engine capacity by using the program „QwikNet 2.23”. As a result we get a trained neural network with amaximum error of 1.00619.10-5 which can be used for assessing the capacity of the electric motors of drum millsand can be considered an accurate mathematical model |
| first_indexed | 2024-12-10T05:12:24Z |
| format | Article |
| id | doaj.art-54f767c8faa44298a47a4a4e7c20eafb |
| institution | Directory Open Access Journal |
| issn | 1844-640X |
| language | English |
| last_indexed | 2024-12-10T05:12:24Z |
| publishDate | 2013-05-01 |
| publisher | Academica Brancusi |
| record_format | Article |
| series | Fiabilitate şi Durabilitate |
| spelling | doaj.art-54f767c8faa44298a47a4a4e7c20eafb2022-12-22T02:01:03ZengAcademica BrancusiFiabilitate şi Durabilitate1844-640X2013-05-011-supl387391DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERSTeodora HRISTOVAIvan MININA successful experiment has been done to train the neural network to determine the drum mills’engine capacity by using the program „QwikNet 2.23”. As a result we get a trained neural network with amaximum error of 1.00619.10-5 which can be used for assessing the capacity of the electric motors of drum millsand can be considered an accurate mathematical modelhttp://www.utgjiu.ro/rev_mec/mecanica/pdf/2013-01.Supliment/61_Teodora%20Hristova,%20Ivan%20Minin.pdfneural networkdrum mill’s enginesubordinate input parameters |
| spellingShingle | Teodora HRISTOVA Ivan MININ DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS Fiabilitate şi Durabilitate neural network drum mill’s engine subordinate input parameters |
| title | DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS |
| title_full | DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS |
| title_fullStr | DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS |
| title_full_unstemmed | DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS |
| title_short | DЕTERMINATION OF THE DRUM MILLS’ ENGINE CAPACITY BYUSING NEURAL NETWORK WITH SUBORDINATE INPUT PARAMETERS |
| title_sort | dеtermination of the drum mills engine capacity byusing neural network with subordinate input parameters |
| topic | neural network drum mill’s engine subordinate input parameters |
| url | http://www.utgjiu.ro/rev_mec/mecanica/pdf/2013-01.Supliment/61_Teodora%20Hristova,%20Ivan%20Minin.pdf |
| work_keys_str_mv | AT teodorahristova determinationofthedrummillsenginecapacitybyusingneuralnetworkwithsubordinateinputparameters AT ivanminin determinationofthedrummillsenginecapacitybyusingneuralnetworkwithsubordinateinputparameters |