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 …
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
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 …
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 …
energy-and cost-saving strategies for poultry farms. In 2019, cross-sectional data were …
Multi-classification of brain tumor images using deep neural network
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 …
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
Convolutional neural networks (CNNs) have gained remarkable success on many image
classification tasks in recent years. However, the performance of CNNs highly relies upon …
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 …
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 …
electronic and information technologies, machine vision combined with image processing …
[HTML][HTML] Machine learning in chemoinformatics and drug discovery
Highlights•Chemical graph theory and descriptors in drug discovery.•Chemical fingerprint
and similarity analysis.•Machine learning models for virtual screening.•Future challenges …
and similarity analysis.•Machine learning models for virtual screening.•Future challenges …
Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning
Rapidly discovering functional materials remains an open challenge because the traditional
trial-and-error methods are usually inefficient especially when thousands of candidates are …
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 …
reasons for alarmingly high electricity consumption in the current times. So far, various …