Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques

Efficient Program Compilation Through Machine Learning Techniques

The wealth of available compiler optimizations leads to the dual problems of finding the best set of optimizations and the best heuristic parameters to tune each optimization. We describe how machine learning techniques, such as logistic regression, can be used to address these problems. We focus on decreasing the compile time for a static commercial compiler, while preserving the execution tim...

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Electricity Load Forecasting Using Machine Learning Techniques

Electricity load forecasting has become increasingly important due to the strong impact on the operational efficiency of the power system. However, the accurate load prediction remains a challenging task due to several issues such as the nonlinear character of the time series or the seasonal patterns it exhibits. A large variety of techniques have been proposed to this aim, such as statistical ...

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Electricity Load Forecasting Using Machine Learning Techniques

Electricity load forecasting has become increasingly important due to the strong impact on the operational efficiency of the power system. However, the accurate load prediction remains a challenging task due to several issues such as the nonlinear character of the time series or the seasonal patterns it exhibits. A large variety of techniques have been proposed to this aim, such as statistical ...

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Electricity Load Forecasting Using Machine Learning Techniques

Electricity load forecasting has become increasingly important due to the strong impact on the operational efficiency of the power system. However, the accurate load prediction remains a challenging task due to several issues such as the nonlinear character of the time series or the seasonal patterns it exhibits. A large variety of techniques have been proposed to this aim, such as statistical ...

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Temperature Forecast in Buildings Using Machine Learning Techniques

Energy efficiency in buildings requires having good prediction of the variables that define the power consumption in the building. Temperature is the most relevant of these variables because it affects the operation of the cooling systems in summer and the heating systems in winter, while being also the main variable that defines comfort. This paper presents the application of classical methods...

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Predicting Heating Load in Energy-Efficient Buildings Through Machine Learning Techniques

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Efficient Program Compilation Through Machine Learning Techniques

Electricity Load Forecasting Using Machine Learning Techniques

Electricity Load Forecasting Using Machine Learning Techniques

Electricity Load Forecasting Using Machine Learning Techniques

Temperature Forecast in Buildings Using Machine Learning Techniques

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