A systematic literature review on machine learning applications for sustainable agriculture supply chain performance

R Sharma, SS Kamble, A Gunasekaran… - Computers & Operations …, 2020 - Elsevier
Agriculture plays an important role in sustaining all human activities. Major challenges such
as overpopulation, competition for resources poses a threat to the food security of the planet …

A systematic literature review on machine learning applications for consumer sentiment analysis using online reviews

PK Jain, R Pamula, G Srivastava - Computer science review, 2021 - Elsevier
Consumer sentiment analysis is a recent fad for social media-related applications such as
healthcare, crime, finance, travel, and in academia. Disentangling consumer perception to …

Application of an artificial neural network to optimise energy inputs: An energy-and cost-saving strategy for commercial poultry farms

E Elahi, Z Zhang, Z Khalid, H Xu - Energy, 2022 - Elsevier
The current study estimates target values of energy inputs along with an assessment of
energy-and cost-saving strategies for poultry farms. In 2019, cross-sectional data were …

Multi-classification of brain tumor images using deep neural network

HH Sultan, NM Salem, W Al-Atabany - IEEE access, 2019 - ieeexplore.ieee.org
Brain tumor classification is a crucial task to evaluate the tumors and make a treatment
decision according to their classes. There are many imaging techniques used to detect brain …

Automatically designing CNN architectures using the genetic algorithm for image classification

Y Sun, B Xue, M Zhang, GG Yen… - IEEE transactions on …, 2020 - ieeexplore.ieee.org
Convolutional neural networks (CNNs) have gained remarkable success on many image
classification tasks in recent years. However, the performance of CNNs highly relies upon …

[HTML][HTML] Prescriptive analytics: Literature review and research challenges

K Lepenioti, A Bousdekis, D Apostolou… - International Journal of …, 2020 - Elsevier
Business analytics aims to enable organizations to make quicker, better, and more
intelligent decisions with the aim to create business value. To date, the major focus in the …

A review on weed detection using ground-based machine vision and image processing techniques

A Wang, W Zhang, X Wei - Computers and electronics in agriculture, 2019 - Elsevier
Weeds are among the major factors that could harm crop yield. With the advances in
electronic and information technologies, machine vision combined with image processing …

[HTML][HTML] Machine learning in chemoinformatics and drug discovery

YC Lo, SE Rensi, W Torng, RB Altman - Drug discovery today, 2018 - Elsevier
Highlights•Chemical graph theory and descriptors in drug discovery.•Chemical fingerprint
and similarity analysis.•Machine learning models for virtual screening.•Future challenges …

Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning

S Lu, Q Zhou, Y Ouyang, Y Guo, Q Li, J Wang - Nature communications, 2018 - nature.com
Rapidly discovering functional materials remains an open challenge because the traditional
trial-and-error methods are usually inefficient especially when thousands of candidates are …

Deep learning framework to forecast electricity demand

J Bedi, D Toshniwal - Applied energy, 2019 - Elsevier
The increasing world population and availability of energy hungry smart devices are major
reasons for alarmingly high electricity consumption in the current times. So far, various …