Titlebook: Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic; Francisco Zayas-Gato,Antonio Díaz-Lo

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书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic影响因子(影响力)




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic影响因子(影响力)学科排名




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic网络公开度




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic网络公开度学科排名




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic被引频次




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic被引频次学科排名




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic年度引用




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic年度引用学科排名




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic读者反馈




书目名称Distributed Computing and Artificial Intelligence, Special Sessions III - Intelligent Systems Applic读者反馈学科排名

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crease the efficiency of the management systems responsible for the energy resources planning. The immediate benefits will be related to reduction of energy consumption, decrease in associated greenhouse gases emissions and improvement of the sustainability indexes of hotel activities. The predictio

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In this context, the labeling of these elements, coupled with optical character recognition (OCR), plays a significant role. Therefore, in this paper, it is accomplished this challenge by applying three pre-trained deep learning OCR models such as Pytesseract, EasyOCR and KerasOCR to a dataset of i

Aerophagia

Hay-Fever

regression models, pre-processing methods, and data analyses are compared in the study to forecast the input collector temperature of the heat pump. Specifically, three different techniques have been considered in this research work: Multilayer Perceptrons, Long Short Term Memory networks and Convol

方舟

ssessing battery conditions and increasing the autonomy of electric vehicles requires to improve the behavior models. Prognosticating battery performance, nevertheless, is complex due to multiple variables, such as temperature, wear, and usage guidelines. Understanding battery performance requires a

方舟

r datasets. Using six complex datasets and MatLab R2023a software, especially the . function, various clustering algorithms such as k-means, agglomerative clustering and Gaussian mixture distribution are evaluated, along with evaluation criteria such as Calinski-Harabasz index, Davies-Bouldin index,

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emissions. However, the main disadvantage of this type of system is the dependence on weather conditions. This research proposes using a virtual sensor to measure the wind speed 10 m above ground through variables measured at ground level. The modeling process followed a feature selection step befor

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Flounder