Results 71 to 80 of about 27,804 (170)
Enhancing the Symbolic Aggregate Approximation Method Using Updated Lookup Tables
, 2010 Similarity search in time series data mining is a problem that has at- tracted increasing attention recently. The high dimensionality and large volume of time series databases make sequential scanning inefficient to tackle this problem. There are many representation techniques that aim at reducing the dimensionality of time series so that the search ...
Muhammad Fuad, Muhammad Marwan +1 more
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Engineering Science and Technology, an International JournalIn deepwater and ultra-deepwater drilling, formation pressures are complex and the drilling fluid density window is narrow, which makes it prone to well control incidents such as kicks and lost circulation.
Kai Feng +7 more
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A comparative study of symbolic aggregate approximation and topological data analysis
Quantitative Finance and Economics<p>The movement of stocks is often perceived as random due to the complex interactions between different stocks and the inherently chaotic nature of the market. This study investigated the similarity in stock movements across multiple industry sectors in Europe. Specifically, we applied topological data analysis (TDA) to analyze stock time series
Hobbelhagen, Fredrik, Diamantis, Ioannis
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, 2017 A novel reduced-scaling, general-order coupled-cluster approach is formulated by exploiting hierarchical representations of many-body tensors, combined with the recently suggested formalism of scale-adaptive tensor algebra.
Lyakh, Dmitry I.
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Financial time series representation using multiresolution important point retrieval method [PDF]
, 2008 Financial time series analysis usually conducts by determining the series important points. These important points which are the peaks and the dips indicate the affecting of some important factors or events which are available both internal factors and ...
Md. Sap, Mohd. Noor +2 more
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2018 IEEE 14th International Conference on Automation Science and Engineering (CASE), 2018 Building system faults in commercial and office buildings can result in a reduced occupant comfort and increased utility bills. Energy performance-based anomaly detection helps operators efficiently identify faults. In this work, a data-driven method for anomaly detection is presented.
Ashouri, Araz +3 more
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Representation learning in intraoperative vital signs for heart failure risk prediction
BMC Medical Informatics and Decision Making, 2019 Background The probability of heart failure during the perioperative period is 2% on average and it is as high as 17% when accompanied by cardiovascular diseases in China. It has been the most significant cause of postoperative death of patients. However,
Yuwen Chen, Baolian Qi
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Ultra-short-term power forecasting for regional DPV systems based on SAX-MHA-GCN
Zhejiang dianliImproving the accuracy of ultra-short-term power forecasting for distributed photovoltaic （DPV） systems is of great significance for optimizing real-time grid dispatch， ensuring power supply reliability， and formulating electricity market competition ...
TANG Yajie +4 more
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Particle Swarm Optimization of Information-Content Weighting of Symbolic Aggregate Approximation [PDF]
, 2012 The 8th International Conference on Advanced Data Mining and Applications (ADMA 2012)
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A Semantic Hybrid Temporal Approach for Detecting Driver Mental Fatigue
SafetyDriver mental fatigue is considered a major factor affecting driver behavior that may result in fatal accidents. Several approaches are addressed in the literature to detect fatigue behavior in a timely manner through either physiological or in-vehicle ...
Shahzeb Ansari +4 more
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