Los pronósticos facilitan la toma de decisiones en granjas productoras de leche y contribuyen a mejorar la cadena productiva de este alimento. En la literatura se identificó que las redes neuronales artificiales poseen un ajuste aceptable al pronóstico de las producciones de leche. Sin embargo, en las fuentes bibliográficas consultadas no se evidenció un consenso sobre el tipo de red neuronal artificial con mejores rendimientos en esta actividad. Esta investigación tiene como objetivo identificar la red neuronal artificial con mayores índices de desempeño en el pronóstico de la producción de leche bovina. Se realizó una revisión de la literatura relacionada con los pronósticos de las producciones de leche mediante el uso de redes neuronales artificiales. Los resultados obtenidos en la literatura analizada evidenciaron que las redes no lineales autorregresivas con variables exógenas y las redes convolucionales poseen los mejores rendimientos en el pronóstico de la producción de leche bovina.
Image segmentation and computer vision are becoming more important in computer-aided design. A computer algorithm extracts image borders, colours, and textures. It also depletes resources. Technical knowledge is required to extract information about distinctive features. There is currently no medical picture segmentation or recognition software available. The proposed model has 13 layers and uses dilated convolution and max-pooling to extract small features. Ghost model deletes the duplicated features, makes the process easier, and reduces the complexity. The Convolution Neural Network (CNN) generates a feature vector map and improves the accuracy of area or bounding box proposals. Restructuring is required for healing. As a result, convolutional neural networks segment medical images. It is possible to acquire the beginning region of a segmented medical image. The proposed model gives better results as compared to the traditional models, it gives an accuracy of 96.05, Precision 98.2, and recall 95.78. The first findings are improved by thickening and categorising the image’s pixels. Morphological techniques may be used to segment medical images. Experiments demonstrate that the recommended segmentation strategy is effective. This study rethinks medical image segmentation methods.
The process of teaching-apprenticeship in the processes of training and professional surmounting and specially the integration between the industrial processes for the professionals that is formed require, more and more, of a sustenance in the technologies of the information and the communications. Your endless occurrence and without limitations space out-temporal, constitute anticipated for the appropriate attainment of the process of teaching in the XXI century. In the viable solutions constitutes it the integration of the Massive Open Online Course (MOOC, Massive Open Online Course), with the use of the information that is to store in digital repositories, digital arcades, and other resources as it is the semantic web. The present work has as objective, lay the foundations of the integration between the MOOC and the semantic web for a process of teaching-apprenticeship of quality, as demand it the educational contexts of the XXI century, for the sake of facilitating the massive apprenticeship and on line of the professionals that form to him. The sample was composite for 10500 participants. It used to him the Delphi method to evaluate the effectiveness of the integration of the MOOC and the semantic web. By means of the Delphi method, a group of 45 expert made evident that the time factor is the key to lay the foundations of the integration between the MOOC and the semantic web. It concludes to him that without measurement of the results it cannot value the success of the integration of the MOOC and the semantic web, for a process of teaching-apprenticeship of quality.
Las herramientas de innovación constituyen un elemento trascendental en el apoyo a la toma de decisiones frente a los modelos de negocios actuales. La irrupción de la Inteligencia Artificial ha hecho énfasis significativo en las herramientas de innovación, destacándose el Razonamiento Basado en Casos, como una técnica perteneciente a la Inteligencia Artificial, útil para el apoyo a la toma de decisiones. Al respecto, la herramienta Innovación Think, se basa específicamente en el Razonamiento Basado en Casos, para hacer del modelo de negocios EM3, un modelo capaz de rectificar las deficiencias de un negocio y conducir a un logro eficiente de la rentabilidad de los negocios. El modelo de negocio EM3, contribuye a innovar hacia un mercado objetivo, donde se involucra las áreas que conocen el mercado en aras de alinear pensamientos para lograr mejores innovaciones y cubrir las necesidades del mercado, todo ello gracias a las recomendaciones que aporta la herramienta Innovación Think, al utilizar como técnica de Inteligencia Artificial el Razonamiento Basado en Casos. En el presente trabajo se propone como objetivo describir la herramienta Innovación Think, para apoyar la toma de decisiones y determinar la viabilidad y rentabilidad de los negocios, obteniéndose a través de ella un mapeo de clientes donde se identifican sus necesidades, con el fin de lograr rediseñar estrategias de negocios que favorezcan la rentabilidad.
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