Multivariate Time Series Analysis of Temperatures in the Archaeological Museum of L’Almoina (Valencia, Spain) [PDF]
Sensors, 2021 An earlier study carried out in 2010 at the archaeological site of L’Almoina (Valencia, Spain) found marked daily fluctuations of temperature, especially in summer. Such pronounced gradient is due to the design of the museum, which includes a skylight as
Sandra Ramírez +2 more
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Topological Data Analysis for Multivariate Time Series Data
Entropy, 2023 Over the last two decades, topological data analysis (TDA) has emerged as a very powerful data analytic approach that can deal with various data modalities of varying complexities.
Anass B. El-Yaagoubi +2 more
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Improving cardiovascular risk stratification through multivariate time-series analysis of cardiopulmonary exercise test data [PDF]
iScienceSummary: Nowadays cardiorespiratory fitness (CRF) is assessed using summary indexes of cardiopulmonary exercise tests (CPETs). Yet, raw time-series CPET recordings may hold additional information with clinical relevance.
Evangelos Ntalianis +11 more
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Connectivity Analysis for Multivariate Time Series: Correlation vs. Causality
Entropy, 2021 The study of the interdependence relationships of the variables of an examined system is of great importance and remains a challenging task. There are two distinct cases of interdependence.
Angeliki Papana
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PSO based Hyperparameter tuning of CNN Multivariate Time- Series Analysis
JOIN: Jurnal Online Informatika, 2022 Convolutional Neural Network (CNN) is an effective Deep Learning (DL) algorithm that solves various image identification problems. The use of CNN for time-series data analysis is emerging.
Agung Bella Putra Utama +3 more
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Pseudo Bidirectional Linear Discriminant Analysis for Multivariate Time Series Classification
IEEE Access, 2021 Multivariate time series (MTS) is a kind of matrix data, typically consisting of multiple variables measured at multiple time points. Due to the high dimensionality of MTS data, many methods for MTS classification have been proposed within the literature
Jianhua Zhao +5 more
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Normalized Multivariate Time Series Causality Analysis and Causal Graph Reconstruction
Entropy, 2021 Causality analysis is an important problem lying at the heart of science, and is of particular importance in data science and machine learning. An endeavor during the past 16 years viewing causality as a real physical notion so as to formulate it from ...
X. San Liang
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Gated Res2Net for Multivariate Time Series Analysis [PDF]
2020 International Joint Conference on Neural Networks (IJCNN), 2020 Multivariate time series analysis is an important problem in data mining because of its widespread applications. With the increase of time series data available for training, implementing deep neural networks in the field of time series analysis is becoming common. Res2Net, a recently proposed backbone, can further improve the state-of-the-art networks
Chao Yang 0024 +3 more
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Automata Based Multivariate Time Series Analysis for Anomaly Detection over Sliding Time Windows
Engineering Proceedings, 2023 We describe an optimal linear time complexity method for extracting patterns from sliding windows of multivariate time series that depends only on the length of the time series.
Arnold Hien +3 more
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Entropy, 2021 In practice, time series forecasting involves the creation of models that generalize data from past values and produce future predictions. Moreover, regarding financial time series forecasting, it can be assumed that the procedure involves phenomena ...
Charalampos M. Liapis +2 more
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