a b s t r a c tFootball is the team sport that mostly attracts great mass audience. Because of the detailed information about all football matches of championships over almost a century, matches build a huge and valuable database to test prediction of matches results. The problem of modeling football data has become increasingly popular in the last years and learning machine have been used to predict football matches results in many studies. Our present work brings a new approach to predict matches results of championships. This approach investigates data of matches in order to predict the results, which are win, draw and defeat. The investigated groups were different type of combinations of two by two pairs, win-draw, windefeat and draw-defeat, of the possible matches results of each championship. In this study we employed the features obtained by scouts during a football match. The proposed system applies a polynomial algorithm to analyse and define matches results. Some machine-learning algorithms were compared with our approach, which includes experiments with information obtained from the football championships. The association between polynomial algorithm and machine learning techniques allowed a significant increase of the accuracy values. Our polynomial algorithm provided an accuracy superior to 96%, selecting the relevant features from the training and testing set.
Activated carbons were produced by chemical activation with H 3 PO 4 (CAQ1) and ZnCl 2 (CAQ2), and used for the methane storage under compression and adsorption. Storage evaluations were performed in a semi-pilot unit where temperature and pressure evolutions were measured (charge pressure: 3.0 MPa). Textural characteristics, absolute densities and specific heats of the activated carbons were measured and related to the performance of the storage system. Mathematical models were developed to predict temperature and pressure evolutions during the gas loading. Our results showed that activated carbon CAQ1 had higher absolute density and lower specific heat than CAQ2. Models that consider the pore-size distribution were the most representative of experimental data for both activated carbons.
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