{"id":3299,"date":"2024-10-10T10:58:15","date_gmt":"2024-10-10T08:58:15","guid":{"rendered":"https:\/\/www.mosaicfactor.com\/project\/raise\/"},"modified":"2024-12-20T10:10:07","modified_gmt":"2024-12-20T09:10:07","slug":"raise","status":"publish","type":"proyecto","link":"https:\/\/www.mosaicfactor.com\/es\/projects\/raise\/","title":{"rendered":"RAISE"},"content":{"rendered":"

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Modelo predictivo para el flujo de carga ferroviaria.<\/p>\n

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Cliente<\/h2>\n

[\/et_pb_text][\/et_pb_column][\/et_pb_row][et_pb_row module_id=\u00bbfila-clientes\u00bb _builder_version=\u00bb4.27.2″ _module_preset=\u00bbdefault\u00bb width=\u00bb150%\u00bb custom_padding=\u00bb0em||2em||false|false\u00bb custom_css_free_form=\u00bbselector .et_pb_module{|| padding:0 1em;|| min-width:12%;||}\u00bb locked=\u00bboff\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_column type=\u00bb4_4″ _builder_version=\u00bb4.27.2″ _module_preset=\u00bbdefault\u00bb custom_css_main_element=\u00bbdisplay:flex;||align-items:center;||flex-flow:wrap;;\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_image src=\u00bbhttps:\/\/www.mosaicfactor.com\/wp-content\/uploads\/2024\/10\/logo-circle-group.webp\u00bb title_text=\u00bblogo-circle-group\u00bb url=\u00bbhttps:\/\/www.circlegroup.eu\/it\/\u00bb url_new_window=\u00bbon\u00bb _builder_version=\u00bb4.27.2″ _module_preset=\u00bbdefault\u00bb width=\u00bb120px\u00bb max_width=\u00bb120px\u00bb custom_css_main_element=\u00bbmax-width:fit-content;\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][\/et_pb_image][\/et_pb_column][\/et_pb_row][et_pb_row admin_label=\u00bbrow\u00bb _builder_version=\u00bb4.27.2″ background_size=\u00bbinitial\u00bb background_position=\u00bbtop_left\u00bb background_repeat=\u00bbrepeat\u00bb width=\u00bb100%\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_column type=\u00bb4_4″ _builder_version=\u00bb4.16″ custom_padding=\u00bb|||\u00bb global_colors_info=\u00bb{}\u00bb custom_padding__hover=\u00bb|||\u00bb theme_builder_area=\u00bbpost_content\u00bb][et_pb_text _builder_version=\u00bb4.27.2″ _module_preset=\u00bbdefault\u00bb text_font_size=\u00bb18px\u00bb text_line_height=\u00bb1.6em\u00bb custom_margin=\u00bb||1em||false|false\u00bb global_colors_info=\u00bb{}\u00bb theme_builder_area=\u00bbpost_content\u00bb]<\/p>\n

Problema<\/h2>\n

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El objetivo de este proyecto es emplear y aprovechar t\u00e9cnicas de modelado predictivo<\/strong> para discernir informaci\u00f3n valiosa que pueda guiar los procesos de toma de decisiones<\/strong> y tener una comprensi\u00f3n clara de la situaci\u00f3n portuaria en t\u00e9rminos de flujos de carga ferroviaria<\/strong>. La atenci\u00f3n se centra en transformar los datos brutos disponibles en inteligencia procesable, facilitando la anticipaci\u00f3n de resultados significativos para la toma de decisiones informadas dentro del contexto dado.<\/p>\n

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Soluci\u00f3n<\/h2>\n

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Nuestra soluci\u00f3n integral de big data est\u00e1 estructurada en cuatro niveles para cumplir con los requisitos y necesidades del proyecto.<\/p>\n

    \n
  1. \n
      \n
    1. An\u00e1lisis de datos y detecci\u00f3n de patrones<\/li>\n
    2. Modelo de predicci\u00f3n de retrasos<\/li>\n
    3. Panel de predicci\u00f3n<\/li>\n
    4. Suite de an\u00e1lisis ferroviario<\/li>\n<\/ol>\n<\/li>\n<\/ol>\n

      Los cuatro niveles de nuestra soluci\u00f3n incluyen no solo el an\u00e1lisis exploratorio de datos brutos con la detecci\u00f3n de patrones hist\u00f3ricos y el desarrollo del modelo de predicci\u00f3n de retrasos, sino tambi\u00e9n la representaci\u00f3n visual de esas actividades como un panel de control de predicci\u00f3n y una suite de an\u00e1lisis ferroviario como un sistema completo.<\/p>\n

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