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Machine learning with laser focus

Recurso electrónico / Electronic resource
Registro MARC
Tag12Valor
LDR  00000cab a2200000 4500
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
24510‎$a‎Machine learning with laser focus‎$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
7001 ‎$0‎MAPA20200009382‎$a‎Brooms, Anthony
7730 ‎$w‎MAP20200013259‎$t‎The Actuary : the magazine of the Institute & Faculty of Actuaries‎$d‎London : Redactive Publishing, 2019-‎$g‎02/03/2020 Número 2 - marzo 2020 , p. 30-33