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Humies Award for Paper at GECCO Conference in Kyoto Japan

27.08.2018 17:21

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Third prize in the Humies Awards presented annually by the Association for Computing Machinery (ACM), was won by a paper entitled “A Hybrid Method for Feature Construction and Selection to Improve Wind-Damage Prediction in the Forestry Sector” co-authored by Prof. Ema Hart and Dr. Kevin Sim at Edinburgh Napier University, Dr. Kana Kamimura of Shinshu University, Japan and Dr. Barry Gardiner of EFIPLANT, Bordeaux.

The paper was presented at the Genetic and Evolutionary Computation Conference (GECCO) in Berlin (Germany) in July 2017, and discussed new machine learning algorithms for identifying the level of risk of wind damage to individual trees.

These algorithms are significantly more accurate than existing mechanistic or statistical models and potentially can provide forest managers and planners with new fast and accurate assessment methods for determining the impact of different management options and forest structures over whole regions.

 

Publisher:
Stephanie Hayes



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