Electricity load forecasting by an improved forecast engine for building level consumers
Y Liu, W Wang, N Ghadimi - Energy, 2017 - Elsevier
For optimal power system operation, electrical generation must follow electrical load
demand. So, short term load forecast (STLF) has been proposed by researchers to tackle the …
demand. So, short term load forecast (STLF) has been proposed by researchers to tackle the …
Feature selection for high-dimensional data
V Bolón-Canedo, N Sánchez-Maroño… - Progress in Artificial …, 2016 - Springer
This paper offers a comprehensive approach to feature selection in the scope of
classification problems, explaining the foundations, real application problems and the …
classification problems, explaining the foundations, real application problems and the …
Machine learning-based radiomics signatures for EGFR and KRAS mutations prediction in non-small-cell lung cancer
Early identification of epidermal growth factor receptor (EGFR) and Kirsten rat sarcoma viral
oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for …
oncogene homolog (KRAS) mutations is crucial for selecting a therapeutic strategy for …
Learning to rank for information retrieval
TY Liu - Foundations and Trends® in Information Retrieval, 2009 - nowpublishers.com
Learning to rank for Information Retrieval (IR) is a task to automatically construct a ranking
model using training data, such that the model can sort new objects according to their …
model using training data, such that the model can sort new objects according to their …
Classification of Alzheimer's disease and prediction of mild cognitive impairment-to-Alzheimer's conversion from structural magnetic resource imaging using feature …
We developed a novel computer-aided diagnosis (CAD) system that uses feature-ranking
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …
and a genetic algorithm to analyze structural magnetic resonance imaging data; using this …
Predicting conversion from MCI to AD using resting-state fMRI, graph theoretical approach and SVM
Background We investigated identifying patients with mild cognitive impairment (MCI) who
progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do …
progress to Alzheimer's disease (AD), MCI converter (MCI-C), from those with MCI who do …
[PDF][PDF] Truncated Power Method for Sparse Eigenvalue Problems.
This paper considers the sparse eigenvalue problem, which is to extract dominant (largest)
sparse eigenvectors with at most k non-zero components. We propose a simple yet effective …
sparse eigenvectors with at most k non-zero components. We propose a simple yet effective …
Efficient and effective tree-based and neural learning to rank
As information retrieval researchers, we not only develop algorithmic solutions to hard
problems, but we also insist on a proper, multifaceted evaluation of ideas. The literature on …
problems, but we also insist on a proper, multifaceted evaluation of ideas. The literature on …
Robustness of AI-based prognostic and systems health management
Abstract Prognostic and systems Health Management (PHM) is an integral part of a system.
It is used for solving reliability problems that often manifest due to complexities in design …
It is used for solving reliability problems that often manifest due to complexities in design …
Small-scale building load forecast based on hybrid forecast engine
M Mohammadi, F Talebpour, E Safaee… - Neural Processing …, 2018 - Springer
Electricity load forecasting plays an important role for optimal power system operation.
Accordingly, short term load forecast (STLF) is also becoming an important task by …
Accordingly, short term load forecast (STLF) is also becoming an important task by …