[HTML][HTML] Industrial digital twins at the nexus of NextG wireless networks and computational intelligence: A survey
By amalgamating recent communication and control technologies, computing and data
analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber …
analytics techniques, and modular manufacturing, Industry 4.0 promotes integrating cyber …
Artificial intelligence/machine learning in energy management systems, control, and optimization of hydrogen fuel cell vehicles
Environmental emissions, global warming, and energy-related concerns have accelerated
the advancements in conventional vehicles that primarily use internal combustion engines …
the advancements in conventional vehicles that primarily use internal combustion engines …
The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions
SK Jagatheesaperumal, M Rahouti… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
An improved adaptive neuro fuzzy inference system model using conjoined metaheuristic algorithms for electrical conductivity prediction
I Ahmadianfar, S Shirvani-Hosseini, J He… - Scientific Reports, 2022 - nature.com
Precise prediction of water quality parameters plays a significant role in making an early
alert of water pollution and making better decisions for the management of water resources …
alert of water pollution and making better decisions for the management of water resources …
A machine learning-based approach for vital node identification in complex networks
Vital node identification is the problem of finding nodes of highest importance in complex
networks. This problem has crucial applications in various contexts such as viral marketing …
networks. This problem has crucial applications in various contexts such as viral marketing …
Multi-objective optimization of an innovative integrated system for production and storage of hydrogen with net-zero carbon emissions
Global energy consumption has been exponentially increasing, leading to the depletion of
conventional energy sources and a considerable increase in greenhouse gas emissions …
conventional energy sources and a considerable increase in greenhouse gas emissions …
Improving energy efficiency of carbon fiber manufacturing through waste heat recovery: A circular economy approach with machine learning
There remain major concerns over the increasing use and waste of materials and energy
resources in multiple manufacturing sectors. To address these concerns, some …
resources in multiple manufacturing sectors. To address these concerns, some …
[HTML][HTML] Machine learning and internet of things in industry 4.0: A review
Abstract Machine learning (ML), sensors networks, and Internet of Things (IoT) are the most
important contributor in the newest revolution in the industry. It is going towards a fully …
important contributor in the newest revolution in the industry. It is going towards a fully …
Multi-objective optimization of a novel hybrid structure for co-generation of ammonium bicarbonate, formic acid, and methanol with net-zero carbon emissions
B Ghorbani, S Zendehboudi… - Energy & …, 2023 - ACS Publications
Chemical storage of hydrogen, originated from renewable energy, is one of the most efficient
and reliable methods to absorb carbon dioxide (CO2) and easily transport large-scale …
and reliable methods to absorb carbon dioxide (CO2) and easily transport large-scale …
Thermo-economic optimization of a novel hybrid structure for power generation and portable hydrogen and ammonia storage based on magnesium–chloride …
Storage and transfer of hydrogen (H 2) from production sites/plants to large-scale
demanding industries are one of the most challenging obstacles to hydrogen adoption …
demanding industries are one of the most challenging obstacles to hydrogen adoption …