[HTML][HTML] Missing value imputation affects the performance of machine learning: A review and analysis of the literature (2010–2021)

MK Hasan, MA Alam, S Roy, A Dutta, MT Jawad… - Informatics in Medicine …, 2021 - Elsevier
Recently, numerous studies have been conducted on Missing Value Imputation (MVI),
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 …

A temporal fusion transformer for short-term freeway traffic speed multistep prediction

H Zhang, Y Zou, X Yang, H Yang - Neurocomputing, 2022 - Elsevier
Accurate short-term freeway speed prediction is a key component for intelligent
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

A Dahou, MAA Al-qaness, M Abd Elaziz, A Helmi - Measurement, 2022 - Elsevier
Nowadays, people use smart devices everywhere and for different applications such as
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

R Janarthanan, P Partheeban… - Sustainable Cities and …, 2021 - Elsevier
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 …

A new method for prediction of air pollution based on intelligent computation

S Al-Janabi, M Mohammad, A Al-Sultan - Soft Computing, 2020 - Springer
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 …

An Innovative synthesis of deep learning techniques (DCapsNet & DCOM) for generation electrical renewable energy from wind energy

S Al-Janabi, AF Alkaim, Z Adel - Soft Computing, 2020 - Springer
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 …

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 …

Intelligent forecaster of concentrations (PM2. 5, PM10, NO2, CO, O3, SO2) caused air pollution (IFCsAP)

S Al-Janabi, A Alkaim, E Al-Janabi, A Aljeboree… - Neural Computing and …, 2021 - Springer
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 …

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 …