[HTML][HTML] A review: Data pre-processing and data augmentation techniques

K Maharana, S Mondal, B Nemade - Global Transitions Proceedings, 2022 - Elsevier
This review paper provides an overview of data pre-processing in Machine learning,
focusing on all types of problems while building the machine learning problems. It deals with …

[HTML][HTML] Methods of photovoltaic fault detection and classification: A review

YY Hong, RA Pula - Energy Reports, 2022 - Elsevier
Photovoltaic (PV) fault detection and classification are essential in maintaining the reliability
of the PV system (PVS). Various faults may occur in either DC or AC side of the PVS. The …

Remote sensing in field crop monitoring: A comprehensive review of sensor systems, data analyses and recent advances

E Omia, H Bae, E Park, MS Kim, I Baek, I Kabenge… - Remote Sensing, 2023 - mdpi.com
The key elements that underpin food security require the adaptation of agricultural systems
to support productivity increases while minimizing inputs and the adverse effects of climate …

Sustainable Development Goal for Quality Education (SDG 4): A study on SDG 4 to extract the pattern of association among the indicators of SDG 4 employing a …

M Saini, E Sengupta, M Singh, H Singh… - Education and Information …, 2023 - Springer
Abstract Sustainable Development Goals (SDG) are at the forefront of government initiatives
across the world. The SDGs are primarily concerned with promoting sustainable growth via …

Advances and opportunities in machine learning for process data analytics

SJ Qin, LH Chiang - Computers & Chemical Engineering, 2019 - Elsevier
In this paper we introduce the current thrust of development in machine learning and
artificial intelligence, fueled by advances in statistical learning theory over the last 20 years …

Big data analytics: a survey

CW Tsai, CF Lai, HC Chao, AV Vasilakos - Journal of Big data, 2015 - Springer
The age of big data is now coming. But the traditional data analytics may not be able to
handle such large quantities of data. The question that arises now is, how to develop a high …

A physics-guided neural network framework for elastic plates: Comparison of governing equations-based and energy-based approaches

W Li, MZ Bazant, J Zhu - Computer Methods in Applied Mechanics and …, 2021 - Elsevier
One of the obstacles hindering the scaling-up of the initial successes of machine learning in
practical engineering applications is the dependence of the accuracy on the size and quality …

Propagation mechanisms and diagnosis of parameter inconsistency within Li-Ion battery packs

F Feng, X Hu, L Hu, F Hu, Y Li, L Zhang - Renewable and Sustainable …, 2019 - Elsevier
Traction batteries constitute a core technology for electric vehicles. The cells used in such
batteries are usually connected in a series-parallel structure. Significant degradation in …

The effect of the normalization method used in different sample sizes on the success of artificial neural network model

G Aksu, CO Güzeller, MT Eser - International journal of assessment …, 2019 - dergipark.org.tr
In this study, it was aimed to compare different normalization methods employed in model
develo** process via artificial neural networks with different sample sizes. As part of …

The impact of agricultural chemical inputs on environment: global evidence from informetrics analysis and visualization

L Zhang, C Yan, Q Guo, J Zhang… - International Journal of …, 2018 - academic.oup.com
This paper identifies and analyzes salient research frontiers, research hotspots and high-
frequency terms using aggregated and multiple-source literature records related to the topic …