[HTML][HTML] Artificial intelligence in E-Commerce: a bibliometric study and literature review
This paper synthesises research on artificial intelligence (AI) in e-commerce and proposes
guidelines on how information systems (IS) research could contribute to this research …
guidelines on how information systems (IS) research could contribute to this research …
Machine learning for anomaly detection: A systematic review
Anomaly detection has been used for decades to identify and extract anomalous
components from data. Many techniques have been used to detect anomalies. One of the …
components from data. Many techniques have been used to detect anomalies. One of the …
Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in supply chain management
Making appropriate decisions is indeed a key factor to help companies facing challenges
from supply chains nowadays. In this paper, we propose two data-driven approaches that …
from supply chains nowadays. In this paper, we propose two data-driven approaches that …
An overview on smart contracts: Challenges, advances and platforms
Smart contract technology is reshaping conventional industry and business processes.
Being embedded in blockchains, smart contracts enable the contractual terms of an …
Being embedded in blockchains, smart contracts enable the contractual terms of an …
Machine learning in natural and engineered water systems
R Huang, C Ma, J Ma, X Huangfu, Q He - Water Research, 2021 - Elsevier
Water resources of desired quality and quantity are the foundation for human survival and
sustainable development. To better protect the water environment and conserve water …
sustainable development. To better protect the water environment and conserve water …
[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 …
Deep learning and big data technologies for IoT security
Technology has become inevitable in human life, especially the growth of Internet of Things
(IoT), which enables communication and interaction with various devices. However, IoT has …
(IoT), which enables communication and interaction with various devices. However, IoT has …
Tadgan: Time series anomaly detection using generative adversarial networks
Time series anomalies can offer information relevant to critical situations facing various
fields, from finance and aerospace to the IT, security, and medical domains. However …
fields, from finance and aerospace to the IT, security, and medical domains. However …
Attack classification of an intrusion detection system using deep learning and hyperparameter optimization
A network intrusion detection system (NIDS) is a solution that mitigates the threat of attacks
on a network. The success of a NIDS depends on the success of its algorithm and the …
on a network. The success of a NIDS depends on the success of its algorithm and the …
A comprehensive study on current and future trends towards the characteristics and enablers of industry 4.0
Abstract Since the first Industrial Revolution the trends in manufacturing have evolved a lot,
from mechanical production to the era of smart manufacturing via technologies like Cyber …
from mechanical production to the era of smart manufacturing via technologies like Cyber …