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Carlos Alfonso Zafra-Mejía, Hugo Alexander Rondón-Quintana and Carlos Felipe Urazán-Bonells
The objective of this paper is to use autoregressive, integrated, and moving average (ARIMA) and transfer function ARIMA (TFARIMA) models to analyze the behavior of the main water quality parameters in the initial components of a drinking water supply sy...
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Luca Scrucca
Gaussian mixture modeling is a generative probabilistic model that assumes that the observed data are generated from a mixture of multiple Gaussian distributions. This mixture model provides a flexible approach to model complex distributions that may not...
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Chunhyun Paik, Yongjoo Chung and Young Jin Kim
The estimation of power curve is the central task for efficient operation and prediction of wind power generation. It is often the case, however, that the actual data exhibit a great deal of variations in power output with respect to wind speed, and thus...
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Francisco Melo Pereira and Rute C. Sofia
This paper provides an analysis of two machine learning algorithms, density-based spatial clustering of applications with noise (DBSCAN) and the local outlier factor (LOF), applied in the detection of outliers in the context of a continuous framework for...
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Annwesha Banerjee Majumder, Somsubhra Gupta, Dharmpal Singh, Biswaranjan Acharya, Vassilis C. Gerogiannis, Andreas Kanavos and Panagiotis Pintelas
Heart disease is a leading global cause of mortality, demanding early detection for effective and timely medical intervention. In this study, we propose a machine learning-based model for early heart disease prediction. This model is trained on a dataset...
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James Simon Flynn, Cinzia Giannetti and Hessel Van Dijk
In many manufacturing systems, anomaly detection is critical to identifying process errors and ensuring product quality. This paper proposes three semi-supervised solutions to detect anomalies in Direct Current (DC) Nut Runner engine assembly processes. ...
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Gaurav Narkhede, Anil Hiwale, Bharat Tidke and Chetan Khadse
Day by day pollution in cities is increasing due to urbanization. One of the biggest challenges posed by the rapid migration of inhabitants into cities is increased air pollution. Sustainable Development Goal 11 indicates that 99 percent of the world?s u...
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Imran, Megat Farez Azril Zuhairi, Syed Mubashir Ali, Zeeshan Shahid, Muhammad Mansoor Alam and Mazliham Mohd Su?ud
Anomaly detection (AD) has captured a significant amount of focus from the research field in recent years, with the rise of the Internet of Things (IoT) application. Anomalies, often known as outliers, are defined as the discovery of anomalous occurrence...
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Cindy Trinh, Silvia Lasala, Olivier Herbinet and Dimitrios Meimaroglou
This article investigates the applicability domain (AD) of machine learning (ML) models trained on high-dimensional data, for the prediction of the ideal gas enthalpy of formation and entropy of molecules via descriptors. The AD is crucial as it describe...
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Jiamu Li, Ji Zhang, Mohamed Jaward Bah, Jian Wang, Youwen Zhu, Gaoming Yang, Lingling Li and Kexin Zhang
When dealing with high-dimensional data, such as in biometric, e-commerce, or industrial applications, it is extremely hard to capture the abnormalities in full space due to the curse of dimensionality. Furthermore, it is becoming increasingly complicate...
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