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[HTML][HTML] Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)
Recently, numerous studies have been conducted on Missing Value Imputation (MVI),
intending the primary solution scheme for the datasets containing one or more missing …
intending the primary solution scheme for the datasets containing one or more missing …
A systematic review of machine learning-based missing value imputation techniques
T Thomas, E Rajabi - Data Technologies and Applications, 2021 - emerald.com
Purpose The primary aim of this study is to review the studies from different dimensions
including type of methods, experimentation setup and evaluation metrics used in the novel …
including type of methods, experimentation setup and evaluation metrics used in the novel …
A temporal fusion transformer for short-term freeway traffic speed multistep prediction
Accurate short-term freeway speed prediction is a key component for intelligent
transportation management and can help travelers plan travel routes. However, very few …
transportation management and can help travelers plan travel routes. However, very few …
Human activity recognition in IoHT applications using arithmetic optimization algorithm and deep learning
Nowadays, people use smart devices everywhere and for different applications such as
healthcare. The Internet of Healthcare Things (IoHT) generates enormous amounts of data …
healthcare. The Internet of Healthcare Things (IoHT) generates enormous amounts of data …
A deep learning approach for prediction of air quality index in a metropolitan city
Abstract In India, the Central and State Pollution Control Boards have commissioned the
National Air Monitoring Program (NAMP) which covers 240 cities with 342 monitoring …
National Air Monitoring Program (NAMP) which covers 240 cities with 342 monitoring …
A new method for prediction of air pollution based on intelligent computation
The detection and treatment of increasing air pollution due to technological developments
represent some of the most important challenges facing the world today. Indeed, there has …
represent some of the most important challenges facing the world today. Indeed, there has …
An Innovative synthesis of deep learning techniques (DCapsNet & DCOM) for generation electrical renewable energy from wind energy
Renewable energy becomes one of the main resources that help the world to safety the
environment from pollution and provide the people of new type of energy; therefore, this …
environment from pollution and provide the people of new type of energy; therefore, this …
Development of deep learning method for predicting DC power based on renewable solar energy and multi-parameters function
S Al-Janabi, Z Al-Janabi - Neural Computing and Applications, 2023 - Springer
In recent decades, the world has witnessed a great expansion in the world of technology
and electronics, in addition to the tremendous development in various industries, which has …
and electronics, in addition to the tremendous development in various industries, which has …
Intelligent forecaster of concentrations (PM2. 5, PM10, NO2, CO, O3, SO2) caused air pollution (IFCsAP)
Upgrading health reality is the responsibility of all, it is necessary to think about the design of
a smart system based on modern technologies to reduce the time and effort exerted on the …
a smart system based on modern technologies to reduce the time and effort exerted on the …
Multi-objective workflow scheduling in cloud computing: trade-off between makespan and cost
A Belgacem, K Beghdad-Bey - Cluster Computing, 2022 - Springer
Recently, modern businesses have started to transform into cloud computing platforms to
deploy their workflow applications. However, scheduling workflow under resource allocation …
deploy their workflow applications. However, scheduling workflow under resource allocation …