This article was developed based on a review of 20 scientific articles and documents related support to artificial neural networks (RNA), in environmental modeling, where it was determined that the RNA used in research studies, showed potential, and met the purpose for which they were trained, but n...
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| Format: | Article |
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https://revistas.sena.edu.co/index.php/rnova/article/view/185 |
| _version_ | 1862443514675068928 |
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| author | Rodriguez Acosta, Daniel |
| author_facet | Rodriguez Acosta, Daniel |
| description | This article was developed based on a review of 20 scientific articles and documents related support to artificial neural networks (RNA), in environmental modeling, where it was determined that the RNA used in research studies, showed potential, and met the purpose for which they were trained, but no was enough optima, to unlearn and face similar objectives under different scenarios, sharing a degree of similarity in the failure to biological neural network, where the problem could be to lie in the programming, because many people, when they learn something and assume them is very difficult to change what we already learned, such as physical or psychological movements proceed. After analyzing this situation proceeded to make a reflection, under a new approach, analyzing own and applied experiments to understand the phenomenon and generate a basic starting point in neuronal programming experiences. Considering that if it can reprogram the neural network of a person, so you can develop various physical and mental functions without giving everything for granted, then an RNA may also acquire this quality. In conclusion, it is determined that the biological neural network itself may be rescheduled, and thus can determine a protocol for a RNA can acquire this ability. Finally we proceed to evaluate the items with the greatest impact, the problem is identified, the so resolved, the result obtained and ends with the writing of a critical analysis of each, to highlight its importance and applicability. |
| format | Article |
| id | citeisa-185 |
| institution | OJS - REV_NOVA |
| record_format | dc |
| spellingShingle | Reprogramming of a biological neural network as a baseline for multifunctional artificial neural network programming Rodriguez Acosta, Daniel |
| title | Reprogramming of a biological neural network as a baseline for multifunctional artificial neural network programming |
| url | https://revistas.sena.edu.co/index.php/rnova/article/view/185 |
