2 research outputs found

    Tendencias recientes en el pronóstico de velocidad de viento para generación eólica

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    Este documento tiene como objetivo presentar un marco unificado para discutir, resumir y organizar los principales avances en pronóstico de velocidad de viento para generación eólica utilizando un método auditable, ordenado y reproducible. Los principales hallazgos fueron: La mayor parte de los trabajos provienen de China y Estados Unidos, las series de tiempo usadas poseen una longitud de menos de un año, comúnmente el pronóstico es realizado en un rango de 1 hora a 48 horas hacia adelante. Muchos estudios usan solamente modelos autoregresivos (Lineares y no lineares) o en muchos casos una sola variable explicatoria. Usualmente la variable pronosticada es la velocidad de viento u la potencia generada. La revisión muestra una tendencia en la que los autores están experimentando con modelos híbridos para obtener las ventajas de cada método utilizado, también, una tendencia a utilizar métodos clásicos como redes neuronales, máquinas de vectores de soporte y modelos autorregresivosAbstract: This document aims to provide a unified frame for discussing, summarizing and organizing the main advances in wind power forecasting using an auditable, orderly and reproducible method. Our main findings are the following: most of works forecasting time series from China and United States; time series data usually cover information with a length lower than a year of data. Commonly, the forecast is done for 1 to 48 hours ahead. Many studies using only autorregresive models (linear or no linear) or, in many cases, one explanatory variable. Usually, the variables forecasted are speed and power. The review shows a tendency in which the authors are experimenting with hybrid models to obtain the advantages of each method used, also, a trend to use classical methods such as neural networks, Support Vector Machines and autoregressive models.Maestrí

    Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

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    Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries
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