Recently, numerous studies have been conducted on Missing Value Imputation (MVI),
intending the primary solution scheme for the datasets containing one or more missing …

Clean water is an indispensable essential resource on which humans and other living
beings depend. Therefore, the establishment of a water quality prediction model to predict …

Understanding the population's dietary patterns and their impacts on health requires many
different sources of information. The development of reliable food composition databases is …

As a direct reference tool to reflect the operational status and development level of national
industry, industrial statistics hold significant value for numerous systematic studies …

Fly ash-based alkali-activated concrete (AAC) is renowned for its superior mechanical
performance and sustainability, presenting an attractive alternative to traditional Portland …

Complete data on wastewater quality are essential for managing and monitoring wastewater
treatment processes. Most management and monitoring methods involve the use of …

Missing values in air quality datasets bring trouble to exploration and decision making about
the environment. Few imputation methods aim at time series air quality data so that they fail …

Background Food reformulation is promoted as a tool to improve the nutritional quality of
population diets. However, the potential impact of industry-wide reformulation on dietary …

Missing data is a common problem in a wide range of fields that can arise as a result of
different reasons: lack of analysis, mishandling samples, measurement error, etc. The area …

In the development of predictive models, the problem of missing data is a critical issue that
traditionally requires a two-step analysis. Data scientists analyze the patterns of missing …