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| Result Number | Material Type | Add to My Shelf Action | Record Details and Options |
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| 1 |
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Prediction of solar radiation for solar systems by using ANN models with different back propagation algorithmsJournal of applied research and technology, 2016-06, Vol.14 (3), p.206-214 [Peer Reviewed Journal]This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. ;ISSN: 2448-6736 ;DOI: 10.1016/j.jart.2016.05.001Digital Resources/Online E-Resources |
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Predicting breeding value of body weight at 6-month age using Artificial Neural Networks in Kermani sheep breedActa scientiarum. Animal sciences, 2019, Vol.41 (1), p.45282-e45282 [Peer Reviewed Journal]2019. This work is licensed under https://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 1806-2636 ;ISSN: 1807-8672 ;EISSN: 1807-8672 ;DOI: 10.4025/actascianimsci.v41i1.45282Full text available |
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Climate-related variables may not improve monthly scale rainfall predictions by artificial neural networks for the metropolitan region of Belo Horizonte, BrazilRevista ambiente & água, 2023, Vol.18, p.1-17 [Peer Reviewed Journal]2023. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 1980-993X ;EISSN: 1980-993X ;DOI: 10.4136/ambi-agua.2879Full text available |
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Cost Forecasting of Public Construction Projects Using Multilayer Perceptron Artificial Neural Networks: A Case StudyIngeniería e investigación, 2021-12, Vol.41 (3), p.e87737-e87737 [Peer Reviewed Journal]2021. This work is published under https://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 0120-5609 ;EISSN: 2248-8723 ;DOI: 10.15446/ing.investig.v41n3.87737Full text available |
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An Early Prediction of Tumor in Heart by Cardiac Masses Classification in Echocardiogram Images Using Robust Back Propagation Neural Network ClassifierBrazilian Archives of Biology and Technology, 2022-01, Vol.65 [Peer Reviewed Journal]This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. ;ISSN: 1516-8913 ;ISSN: 1678-4324 ;EISSN: 1678-4324 ;DOI: 10.1590/1678-4324-2022210316Full text available |
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Comprehensive performance analysis of training functions in flow prediction model using artificial neural networkWater S. A., 2024-04, Vol.50 (2), p.190-200 [Peer Reviewed Journal]COPYRIGHT 2024 Water Research Commission ;2024. This work is published under http://www.wrc.org.za/water-sa/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 0378-4738 ;ISSN: 1816-7950 ;EISSN: 1816-7950 ;DOI: 10.17159/wsa/2024.v50.i2.4099Full text available |
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Classificação da capacidade produtiva com alturas de árvores dominantes estimadas por RNACiência florestal, 2022-09, Vol.32 (3), p.1552-1574 [Peer Reviewed Journal]This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. ;ISSN: 1980-5098 ;EISSN: 1980-5098 ;DOI: 10.5902/1980509867120Digital Resources/Online E-Resources |
| 8 |
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The Use of Combined Neural Networks and Genetic Algorithms for Prediction of River Water QualityJournal of applied research and technology, 2014-06, Vol.12 (3), p.493-499 [Peer Reviewed Journal]This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. ;ISSN: 2448-6736 ;DOI: 10.1016/S1665-6423(14)71629-3Digital Resources/Online E-Resources |
| 9 |
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Research on Comparison of Different Algorithms in Diagnosing Faults of Aircraft EnginesJournal of aerospace technology and management, 2021, Vol.13 (1), p.e3821-e3821 [Peer Reviewed Journal]This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 2175-9146 ;ISSN: 1984-9648 ;EISSN: 2175-9146 ;DOI: 10.1590/jatm.v13.1229Full text available |
| 10 |
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Applications of Artificial Neural Network Simulation for Prediction of Wear Rate and Coefficient of Friction Titanium Matrix CompositesMaterials research (São Carlos, São Paulo, Brazil), 2023, Vol.26, p.1 [Peer Reviewed Journal]Copyright Universidade Federal do Sao Carlos, Departamento de Engenharia de Materiais 2023 ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 1516-1439 ;ISSN: 1980-5373 ;EISSN: 1980-5373 ;DOI: 10.1590/1980-5373-mr-2022-0306Full text available |
| 11 |
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A prediction method of regional water resources carrying capacity based on artificial neural networkEarth sciences research journal, 2021-06, Vol.25 (2), p.169-177 [Peer Reviewed Journal]2021. This work is published under https://creativecommons.org/licenses/by/4.0 (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 1794-6190 ;EISSN: 2339-3459 ;DOI: 10.15446/esrj.v25n2.81615Full text available |
| 12 |
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Application of artificial neural networks to frost detection in central Chile using the next day minimum air temperature forecastChilean journal of agricultural research, 2018-09, Vol.78 (3), p.327-338COPYRIGHT 2018 Instituto de Investigaciones Agropecuarias ;2018. This work is published under https://creativecommons.org/licenses/by-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. ;ISSN: 0718-5839 ;ISSN: 0718-5820 ;EISSN: 0718-5839 ;DOI: 10.4067/S0718-58392018000300327Full text available |
| 13 |
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Bead Geometry Prediction in Pulsed GMAW Welding: A Comparative Study on the Performance of Artificial Neural Network and Regression ModelsSoldagem & Inspeção, 2022, Vol.27, p.1 [Peer Reviewed Journal]Copyright Associacao Brasileira de Soldagem 2022 ;This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. ;ISSN: 0104-9224 ;ISSN: 1980-6973 ;EISSN: 1980-6973 ;DOI: 10.1590/0104-9224/si27.22Full text available |
| 14 |
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Impact of Interchannel Interference in Gridless Nyquist-wdm Systems with and without Nonlinear Impairment CompensationCiencia e ingeniería neogranadina, 2019-12, Vol.29 (2), p.9-23 [Peer Reviewed Journal]Copyright Universidad Militar Nueva Granada Jul-Dec 2019 ;This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. ;ISSN: 0124-8170 ;ISSN: 1909-7735 ;EISSN: 1909-7735 ;DOI: 10.18359/rcin.3830Full text available |
| 15 |
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A PERCEPTRON-BASED FEATURE SELECTION APPROACH FOR DECISION TREE CLASSIFICATIONBoletim de Ciências Geodésicas, 2020, Vol.26 (3) [Peer Reviewed Journal]This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 1982-2170 ;DOI: 10.1590/s1982-21702020000300015Digital Resources/Online E-Resources |
| 16 |
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Modeling the leaf area of Ormosia paraensis Ducke by statistical models and artificial neural networksChilean journal of agricultural research, 2018-12, Vol.78 (4), p.511-520COPYRIGHT 2018 Instituto de Investigaciones Agropecuarias ;2018. This work is published under https://creativecommons.org/licenses/by-sa/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License. ;ISSN: 0718-5839 ;ISSN: 0718-5820 ;EISSN: 0718-5839 ;DOI: 10.4067/S0718-58392018000400511Full text available |
| 17 |
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Evaluación de daños en pavimento flexible usando fotogrametría terrestre y redes neuronalesTecno - Lógicas (Instituto Tecnológico Metropolitano), 2021-01, Vol.24 (50), p.e1686-712021. This work is published under https://creativecommons.org/licenses/by-nc-sa/4.0/deed.es_ES (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. ;This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License. ;LICENCIA DE USO: Los documentos a texto completo incluidos en Dialnet son de acceso libre y propiedad de sus autores y/o editores. Por tanto, cualquier acto de reproducción, distribución, comunicación pública y/o transformación total o parcial requiere el consentimiento expreso y escrito de aquéllos. Cualquier enlace al texto completo de estos documentos deberá hacerse a través de la URL oficial de éstos en Dialnet. Más información: https://dialnet.unirioja.es/info/derechosOAI | INTELLECTUAL PROPERTY RIGHTS STATEMENT: Full text documents hosted by Dialnet are protected by copyright and/or related rights. This digital object is accessible without charge, but its use is subject to the licensing conditions set by its authors or editors. Unless expressly stated otherwise in the licensing conditions, you are free to linking, browsing, printing and making a copy for your own personal purposes. All other acts of reproduction and communication to the public are subject to the licensing conditions expressed by editors and authors and require consent from them. Any link to this document should be made using its official URL in Dialnet. More info: https://dialnet.unirioja.es/info/derechosOAI ;ISSN: 0123-7799 ;ISSN: 2256-5337 ;EISSN: 2256-5337 ;DOI: 10.22430/22565337.1686Full text available |
| 18 |
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Wavelet denoising of partial discharge signals and their pattern classification using artificial neural networks and support vector machinesDyna (Medellín, Colombia), 2017-12, Vol.84 (203), p.240-248 [Peer Reviewed Journal]Copyright Universidad Nacional de Colombia 2017 ;This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. ;LICENCIA DE USO: Los documentos a texto completo incluidos en Dialnet son de acceso libre y propiedad de sus autores y/o editores. Por tanto, cualquier acto de reproducción, distribución, comunicación pública y/o transformación total o parcial requiere el consentimiento expreso y escrito de aquéllos. Cualquier enlace al texto completo de estos documentos deberá hacerse a través de la URL oficial de éstos en Dialnet. Más información: https://dialnet.unirioja.es/info/derechosOAI | INTELLECTUAL PROPERTY RIGHTS STATEMENT: Full text documents hosted by Dialnet are protected by copyright and/or related rights. This digital object is accessible without charge, but its use is subject to the licensing conditions set by its authors or editors. Unless expressly stated otherwise in the licensing conditions, you are free to linking, browsing, printing and making a copy for your own personal purposes. All other acts of reproduction and communication to the public are subject to the licensing conditions expressed by editors and authors and require consent from them. Any link to this document should be made using its official URL in Dialnet. More info: https://dialnet.unirioja.es/info/derechosOAI ;ISSN: 0012-7353 ;EISSN: 2346-2183 ;DOI: 10.15446/dyna.v84n203.63745Full text available |
| 19 |
Material Type: Article
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Application of artificial neural networks in modeling deforestation associated with new road infrastructure projectsDyna (Medellín, Colombia), 2017, Vol.84 (201), p.68-73 [Peer Reviewed Journal]Copyright Universidad Nacional de Colombia 2017 ;This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License. ;LICENCIA DE USO: Los documentos a texto completo incluidos en Dialnet son de acceso libre y propiedad de sus autores y/o editores. Por tanto, cualquier acto de reproducción, distribución, comunicación pública y/o transformación total o parcial requiere el consentimiento expreso y escrito de aquéllos. Cualquier enlace al texto completo de estos documentos deberá hacerse a través de la URL oficial de éstos en Dialnet. Más información: https://dialnet.unirioja.es/info/derechosOAI | INTELLECTUAL PROPERTY RIGHTS STATEMENT: Full text documents hosted by Dialnet are protected by copyright and/or related rights. This digital object is accessible without charge, but its use is subject to the licensing conditions set by its authors or editors. Unless expressly stated otherwise in the licensing conditions, you are free to linking, browsing, printing and making a copy for your own personal purposes. All other acts of reproduction and communication to the public are subject to the licensing conditions expressed by editors and authors and require consent from them. Any link to this document should be made using its official URL in Dialnet. More info: https://dialnet.unirioja.es/info/derechosOAI ;ISSN: 0012-7353 ;EISSN: 2346-2183 ;DOI: 10.15446/dyna.v84n201.54310Full text available |
| 20 |
Material Type: Article
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USING PARTICLE SWARM OPTIMIZATION TO ESTABLISH A LOCAL GEOMETRIC GEOID MODELBoletim de Ciências Geodésicas, 2017-06, Vol.23 (2), p.327-337 [Peer Reviewed Journal]Copyright Universidade Federal do Paraná, Centro Politécnico Apr/Jun 2017 ;This work is licensed under a Creative Commons Attribution 4.0 International License. ;ISSN: 1982-2170 ;ISSN: 1413-4853 ;EISSN: 1982-2170 ;DOI: 10.1590/s1982-21702017000200021Full text available |
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