Advanced Machine Learning Techniques for Energy Consumption Analysis and Optimization at UBC Campus: Correlations with Meteorological Variables by Amir Shahcheraghian, Adrian Ilinca

“…Applying advanced machine learning techniques underscores the potential of data-driven energy optimization strategies. …”
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Data augmentation for numerical data from manufacturing processes: an overview of techniques and assessment of when which techniques work by Henry Ekwaro-Osire, Sai Lalitha Ponugupati, Abdullah Al Noman, Dennis Bode, Klaus-Dieter Thoben

“…It also provides a literature review, highlighting that generative models are the most common technique for numerical manufacturing data. Preliminary findings suggest that generative adversarial networks are effective for non-time-series numerical data, especially with datasets featuring many correlated model features, multiple machines, and sufficient instances and labels. …”
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The Concept of Data Mining and Knowledge Extraction Techniques by Renas Rajab Asaad, Revink Masoud Abdulhakim

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Nitrogen Dioxide Monitoring by Means of a Low-Cost Autonomous Platform and Sensor Calibration via Machine Learning with Global Data Correlation Enhancement by Slawomir Koziel, Anna Pietrenko-Dabrowska, Marek Wójcikowski, Bogdan Pankiewicz

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Regression for Astronomical Data with Realistic Distributions, Errors, and Nonlinearity by Tao Jing, Cheng Li

“…We have developed a new regression technique, the maximum likelihood (ML)–based method and its variant, the Kolmogorov–Smirnov (KS) test–based method, designed to obtain unbiased regression results from typical astronomical data. …”
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Use of Machine-Learning Techniques to Estimate Long-Term Wave Power at a Target Site Where Short-Term Data Are Available by María José Pérez-Molina, José A. Carta

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Mode-Stirred Chamber Sample Selection Technique Applied to Antenna Correlation Coefficient by Paul Hallbjörner, Juan D. Sánchez-Heredia, Antonio M. Martínez-González

“…Recent research has focused on making the mode-stirred chamber technique more versatile. One result of these efforts is the sample selection technique, by which a subset of data with specific properties is extracted from a measured set of raw data. …”
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Urban heat island and pollutant correlations in Bangalore, India using geospatial techniques by Aneesh Mathew, K.S. Arunab

“…Data were collected over a four-year period (2019–2022) to analyze spatial and temporal pollutant distributions and UHI effects in Bangalore and employed statistical methods, including Pearson correlation, independent t-tests, and ANOVA, to assess the relationships between UHI indicators and pollutant concentrations. …”
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A semi-automatic approach to identify first arrival time: the Cross-Correlation Technique by Mustafa Senkaya, Hakan Karslı

“…Under these considerations, identifying first arrivals in noisy data becomes more complex and unstable. In this study, the Cross-Correlation Technique (CCT), which is widely used in the process of analyzing reflection data, has been used to pick the first arrival times in noisy or noiseless seismic refraction data by a semi-automatic process. …”
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Using data mining techniques to improve inflation rate management by Fatemeh Zahra Abedi Samakoosh, Soheila Karbasi

“…Data mining techniques are a useful tool in solving various problems in the economic field by identifying correlations and discovering patterns that helps the analysts to make the best predictions of economic indicators. …”
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Synchronous application of DIC and DVC techniques for the global-local characterization of carbon fiber-reinforced composite laminates by Chaeyoung Hong, Minsu Park, Wooseok Ji

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Analysis and Prediction of Energy Consumption Data, Using Data Mining Software by KAZOLIS Dimitrios, FANTIDIS Jacob, FOTAKIS Christos Dionyshs, TRAMANTZAS Kostantinos, TSIANTOS Vassilios

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Enhancing methyldopa solubility via green supercritical fluid techniques using ethanol co-solvent by Hadil Faris Alotaibi, Suleiman Ibrahim Mohammad, Asokan Vasudevan, Suranjana V. Mayani, Suhas Ballal, Munthar Kadhim Abosaoda, Abhayveer Singh, Subhashree Ray, Atreyi Pramanik

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Business Intent and Network Slicing Correlation Dataset from Data-Driven Perspective by Jie Li, Sai Zou, Yanglong Sun, Hongfeng Gao, Wei Ni

“…We utilize natural language processing techniques based on named entity recognition and third-party data analysis tools such as DataProfiler to validate the data quality of BINS, confirming its reliability. …”
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Development and Study of Demodulation Techniques for Frequency Manipulated Signals by D. I. Kaplun, V. V. Gulvanskiy, I. I. Kanatov, D. M. Klionskiy, V. F. Lapizkiy, V. I. Bobrovskiy, K. V. Frolov, A. K. Skvortzov

“…We indicate that the best results for signal-to-noise ratio exceeding 5 dB are provided with the technique based on double correlation, and for signal-to-noise ratio less than 5 dB - with the technique based on the fast Fourier transform.…”
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A Correlation-Based Feature Selection Algorithm for Operating Data of Nuclear Power Plants by Yuxuan He, Hongxing Yu, Ren Yu, Jian Song, Haibo Lian, Jiangyang He, Jiangtao Yuan

“…In this paper, a correlation-based feature selection algorithm is developed to implement feature selection of nuclear power plant operating data. …”
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Copula-Driven Learning Techniques for Physical Layer Authentication Using Multimodal Data by Sahana Srikanth, Sanjeev Gurugopinath, Sami Muhaidat

“…In this paper, we present a study on copula-driven learning techniques for physical layer authentication (PLA) in wireless communication, using data from multiple modalities. …”
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Predicting Student Performance and Enhancing Learning Outcomes: A Data-Driven Approach Using Educational Data Mining Techniques by Athanasios Angeioplastis, John Aliprantis, Markos Konstantakis, Alkiviadis Tsimpiris

“…This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. …”
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Tree Top Detection in UAV Data: Evaluating Accuracy of Different Estimation Techniques by A. Hosingholizade, Y. Erfanifard, Y. Erfanifard, S. K. Alavipanah, V. García Millan, S. Pirasteh, S. Pirasteh, A. N. Arslan, A. N. Arslan

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Advanced air quality prediction using multimodal data and dynamic modeling techniques by Umesh Kumar Lilhore, Sarita Simaiya, Rajesh Kumar Singh, Abdullah M. Baqasah, Roobaea Alroobaea, Majed Alsafyani, Afnan Alhazmi, M. D. Monish Khan

“…This study highlights the advantages of combining multimodal data sources with advanced dynamic modeling techniques to improve air pollution prediction and inform policymaking.…”
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