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Haneul Lee and Seokheon Yun
Accurately predicting construction costs during the initial planning stages is crucial for the successful completion of construction projects. Recent advancements have introduced various machine learning-based methods to enhance cost estimation precision...
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Sara Rajaram and Cassie S. Mitchell
The ability to translate Generative Adversarial Networks (GANs) and Variational Autoencoders (VAEs) into different modalities and data types is essential to improve Deep Learning (DL) for predictive medicine. This work presents DACMVA, a novel framework ...
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Menna Ibrahim Gabr, Yehia Mostafa Helmy and Doaa Saad Elzanfaly
Data completeness is one of the most common challenges that hinder the performance of data analytics platforms. Different studies have assessed the effect of missing values on different classification models based on a single evaluation metric, namely, a...
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Fan Zhang, Melissa Petersen, Leigh Johnson, James Hall, Raymond F. Palmer, Sid E. O?Bryant and on behalf of the Health and Aging Brain Study (HABS?HD) Study Team
The Health and Aging Brain Study?Health Disparities (HABS?HD) project seeks to understand the biological, social, and environmental factors that impact brain aging among diverse communities. A common issue for HABS?HD is missing data. It is impossible to...
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Ashokkumar Palanivinayagam and Robertas Dama?evicius
The existence of missing values reduces the amount of knowledge learned by the machine learning models in the training stage thus affecting the classification accuracy negatively. To address this challenge, we introduce the use of Support Vector Machine ...
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Mara Meggiorin, Giulia Passadore, Silvia Bertoldo, Andrea Sottani and Andrea Rinaldo
This study compares three imputation methods applied to the field observations of hydraulic head in subsurface hydrology. Hydrogeological studies that analyze the timeseries of groundwater elevations often face issues with missing data that may mislead b...
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Li Cai, Cong Sha, Jing He and Shaowen Yao
Traffic flows (e.g., the traffic of vehicles, passengers, and bikes) aim to reveal traffic flow phenomena generated by traffic participants in traffic activities. Various studies of traffic flows rely heavily on high-quality traffic data. The taxi GPS tr...
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Xing Su, Wenjie Sun, Chenting Song, Zhi Cai and Limin Guo
With the rapid development of the economy, car ownership has grown rapidly, which causes many traffic problems. In recent years, intelligent transportation systems have been used to solve various traffic problems. To achieve effective and efficient traff...
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Cong Li, Xupeng Ren and Guohui Zhao
Ground meteorological observation data (GMOD) are the core of research on earth-related disciplines and an important reference for societal production and life. Unfortunately, due to operational issues or equipment failures, missing values may occur in G...
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Saul G. Ramirez, Gustavious Paul Williams, Norman L. Jones, Daniel P. Ames and Jani Radebaugh
Obtaining and managing groundwater data is difficult as it is common for time series datasets representing groundwater levels at wells to have large gaps of missing data. To address this issue, many methods have been developed to infill or impute the mis...
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