Machine learning with laser focus
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001 | MAP20200014195 | ||
003 | MAP | ||
005 | 20220911202424.0 | ||
008 | 200427e20200302gbr|||p |0|||b|eng d | ||
040 | $aMAP$bspa$dMAP | ||
084 | $a892.7 | ||
100 | $0MAPA20200009306$aHoltom, Theodore | ||
245 | 1 | 0 | $aMachine learning with laser focus$cTheodore Holtom, Anthony Brooms |
520 | $aWind energy technology is relevant to the international political objectives of the Paris Agreement, UN Sustainability Goals, the declared climate emergency, reduction of pollution, and UK green growth strategy. A number of insurance products are sensitive to wind. Wind measurements feed into the assessment of investment risk during project planning and development, while development and operational projects are subject to due diligence assessment during financial transactions, making reference to the site wind conditions and asset performance (actual or expected). Assets also need to be engineered appropriately for local wind conditions during operation, wind turbines and some other assets, such as tall buildings and bridges, undergo engineering fatigue as a result of wind. Additionally, wind turbine suppliers may provide warranty and maintenance agreements that include performance-based bonuses or penalties based on availability to generate, or guarantees of electricity sales revenue. Knowledge of wind conditions, therefore, is of financial significance. | ||
650 | 4 | $0MAPA20080568764$aEnergía eólica | |
650 | 4 | $0MAPA20080598358$aProductos de seguros | |
650 | 4 | $0MAPA20080601522$aEvaluación de riesgos | |
650 | 4 | $0MAPA20080630010$aCondiciones climáticas ambientales | |
650 | 4 | $0MAPA20080591182$aGerencia de riesgos | |
650 | 4 | $0MAPA20170005476$aMachine learning | |
650 | 4 | $0MAPA20180006456$aWarranties | |
700 | 1 | $0MAPA20200009382$aBrooms, Anthony | |
773 | 0 | $wMAP20200013259$tThe Actuary : the magazine of the Institute & Faculty of Actuaries$dLondon : Redactive Publishing, 2019-$g02/03/2020 Número 2 - marzo 2020 , p. 30-33 |