[HTML][HTML] Survey on recent advances in IoT application layer protocols and machine learning scope for research directions
Abstract The Internet of Things (IoT) has been growing over the past few years due to its
flexibility and ease of use in real-time applications. The IoT's foremost task is ensuring that …
flexibility and ease of use in real-time applications. The IoT's foremost task is ensuring that …
A comprehensive and systematic literature review on the big data management techniques in the internet of things
Abstract The Internet of Things (IoT) is a communication paradigm and a collection of
heterogeneous interconnected devices. It produces large-scale distributed, and diverse data …
heterogeneous interconnected devices. It produces large-scale distributed, and diverse data …
Comparative study on total nitrogen prediction in wastewater treatment plant and effect of various feature selection methods on machine learning algorithms …
F Bagherzadeh, MJ Mehrani, M Basirifard… - Journal of Water Process …, 2021 - Elsevier
Wastewater characteristics prediction in wastewater treatment plants (WWTPs) is valuable
and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods …
and can reduce the number of sampling, energy, and cost. Feature Selection (FS) methods …
Internet of things with artificial intelligence for health care security
TM Ghazal - Arabian Journal for Science and …, 2021 - research.skylineuniversity.ac.ae
In recent years, health care facilities are moving towards technological advancements for
precise patient monitoring and record management. Though it is technically advanced, the …
precise patient monitoring and record management. Though it is technically advanced, the …
[HTML][HTML] A novel improved random forest for text classification using feature ranking and optimal number of trees
Abstract Machine learning-based models like random forest (RF) have been widely
deployed in diverse domains such as image processing, health care, and text processing …
deployed in diverse domains such as image processing, health care, and text processing …
Prediction of energy consumption and evaluation of affecting factors in a full-scale WWTP using a machine learning approach
F Bagherzadeh, AS Nouri, MJ Mehrani… - Process Safety and …, 2021 - Elsevier
Abstract Treatment of municipal wastewater to meet the stringent effluent quality standards is
an energy-intensive process and the main contributor to the costs of wastewater treatment …
an energy-intensive process and the main contributor to the costs of wastewater treatment …
[HTML][HTML] Predicting quality parameters of wastewater treatment plants using artificial intelligence techniques
Estimating wastewater treatment plants'(WWTPs) influent parameters such as 5-day
biological oxygen demand (BOD 5) and chemical oxygen demand (COD) is vital for …
biological oxygen demand (BOD 5) and chemical oxygen demand (COD) is vital for …
Reduced kernel random forest technique for fault detection and classification in grid-tied PV systems
K Dhibi, R Fezai, M Mansouri, M Trabelsi… - IEEE Journal of …, 2020 - ieeexplore.ieee.org
The random forest (RF) classifier, which is a combination of tree predictors, is one of the
most powerful classification algorithms that has been recently applied for fault detection and …
most powerful classification algorithms that has been recently applied for fault detection and …
Multivariate feature extraction based supervised machine learning for fault detection and diagnosis in photovoltaic systems
Fault detection and diagnosis (FDD) in the photovoltaic (PV) array has become a challenge
due to the magnitudes of the faults, the presence of maximum power point trackers, non …
due to the magnitudes of the faults, the presence of maximum power point trackers, non …
An enhanced ensemble learning-based fault detection and diagnosis for grid-connected PV systems
The main objective of this article is to develop an enhanced ensemble learning (EL) based
intelligent fault detection and diagnosis (FDD) paradigms that aim to ensure the high …
intelligent fault detection and diagnosis (FDD) paradigms that aim to ensure the high …