Partial Autocorrelation Features
Partial Autocorrelation Features is a time series feature engineering method that quantifies the direct linear dependence between an observation and its lagged values at a specific lag, after removing the effect of intermediate lags, thereby isolating the unique correlation at each lag order.
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529
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18
Institutions
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2017–2026
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Building Energy Consumption Prediction: An Extreme Deep Learning Approach
Chengdong Li, Zixiang Ding, Dongbin Zhao et al. · Energies · 2017 · 293 citations · Full text
Unobtrusive and Multimodal Wearable Sensing to Quantify Anxiety
Yali Zheng, Tracy C. H. Wong, Billy H. K. Leung et al. · IEEE Sensors Journal · 2016 · 71 citations
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Universidad de Jaén
Jaén, Spain
1 h-index
3 publications
84 citations
University of Tabriz
Tabriz, Iran
1 h-index
2 publications
28 citations
Hainan University
Haikou, China
1 h-index
1 publications
27 citations
Shanghai Polytechnic University
Shanghai, China
1 h-index
1 publications
27 citations

Chinese Academy of Sciences
Beijing, China
1 h-index
2 publications
586 citations
Qazvin Islamic Azad University
Qazvin, Iran
1 h-index
1 publications
14 citations
Shanghai Medical Information Center
Shanghai, China
1 h-index
1 publications
27 citations
University of Talca
Talca, Chile
1 h-index
1 publications
28 citations
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1 publications · 14 citations
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1 publications · 71 citations
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1 publications · 27 citations
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1 publications · 293 citations
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SHM · 1 publications · 17 citations
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