上年網上遊戲Wordle的風潮席捲全球，大家的社交媒體好一陣子都被綠色、黃色和灰色的方格佔據。你可能見過朋友誇耀自己只猜了三次就已解開當天謎題，也有時會沮喪地抱怨當天只能以「X/6」飲恨作結，未能揭開當天謎底。當我們思考應用甚麼單字開始遊戲時，我們也許會很隨性地把一個五個字母長的任意單字填進空格，但其實這其實是一個科學問題…
Tag: Mathematical Sciences
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Wordle大揭秘：资讯理论101
上年网上游戏Wordle的风潮席卷全球，大家的社交媒体好一阵子都被绿色、黄色和灰色的方格占据。你可能见过朋友夸耀自己只猜了三次就已解开当天谜题，也有时会沮丧地抱怨当天只能以「X/6」饮恨作结，未能揭开当天谜底。当我们思考应用甚么单字开始游戏时，我们也许会很随性地把一个五个字母长的任意单字填进空格，但其实这其实是一个科学问题…
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Wordle大揭秘：资讯理论101
上年网上游戏Wordle的风潮席卷全球，大家的社交媒体好一阵子都被绿色、黄色和灰色的方格占据。你可能见过朋友夸耀自己只猜了三次就已解开当天谜题，也有时会沮丧地抱怨当天只能以「X/6」饮恨作结，未能揭开当天谜底。当我们思考应用甚么单字开始游戏时，我们也许会很随性地把一个五个字母长的任意单字填进空格，但其实这其实是一个科学问题…
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Cluster-Based Aircraft Fuel Estimation Model for Effective and Efficient Fuel Budgeting on New Routes
Abstract: Fuel burn accounts for up to 25% of an aircraft’s total operating cost and has become one of the most important decision factors in the airline industry. Hence, prudent fuel estimation is essential for airlines to ensure smooth operation in the upcoming financial year. Challenges arise when airlines need to estimate the total fuel consumption of new sectors where data are not available. This necessitates the derivation of a robust parametric model that can represent the characteristics of the new route even in the absence of relevant data. To address this issue, we propose a two-step approach to derive a model that can accurately estimate the aircraft fuel needed. The developed approach involves both unsupervised learning and a regression model. For the unsupervised learning step, hierarchical density-based spatial clustering of applications with noise (HDBSCAN) is used to cluster the principal component analysis (PCA)-reduced data. This step can automatically separate flight sectors based on their underlying characteristics, as revealed by their principal components, upon filtering the noise in the data. Afterward, multivariate linear regression (MLR) is used to derive the equations for each cluster. The PCA-based clustered model is shown to be superior to using a global model for a single aircraft type. This approach yields fuel estimation with less than 5% root mean square error for existing routes within each cluster. More importantly, the proposed method can accurately estimate the total fuel of a new route with less than 2% aggregate error, thereby addressing one of the current limitations in the airline fuel estimation study…
