|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Xinxi Lu, Lijuan Yuan, Ruifeng Li, Zhihuan Xing, Ning Yao and Yichun Yu
In recent years, the development of computer technology has promoted the informatization and intelligentization of hospital management systems and thus produced a large amount of medical data. These medical data are valuable resources for research. We ca...
ver más
|
|
|
|
|
|
|
|
|
|
|
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 ...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|
|
|
|
|
|
Edgar Acuna, Roxana Aparicio and Velcy Palomino
In this paper we investigate the effect of two preprocessing techniques, data imputation and smoothing, in the prediction of blood glucose level in type 1 diabetes patients, using a novel deep learning model called Transformer. We train three models: XGB...
ver más
|
|
|
|
|
|
|
|
|
|
|
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...
ver más
|
|
|
|
|
|