Deep reinforcement learning in production systems: a systematic literature review
Shortening product development cycles and fully customisable products pose major
challenges for production systems. These not only have to cope with an increased product …
challenges for production systems. These not only have to cope with an increased product …
Recent advances in applications of artificial intelligence in solid waste management: A review
Efficient management of solid waste is essential to lessen its potential health and
environmental impacts. However, the current solid waste management practices encounter …
environmental impacts. However, the current solid waste management practices encounter …
[HTML][HTML] Artificial intelligence in pancreatic cancer
B Huang, H Huang, S Zhang, D Zhang, Q Shi, J Liu… - Theranostics, 2022 - ncbi.nlm.nih.gov
Pancreatic cancer is the deadliest disease, with a five-year overall survival rate of just 11%.
The pancreatic cancer patients diagnosed with early screening have a median overall …
The pancreatic cancer patients diagnosed with early screening have a median overall …
Text mining and natural language processing in construction
Text mining (TM) and natural language processing (NLP) have stirred interest within the
construction field, as they offer enhanced capabilities for managing and analyzing text …
construction field, as they offer enhanced capabilities for managing and analyzing text …
A survey on deep reinforcement learning for audio-based applications
Deep reinforcement learning (DRL) is poised to revolutionise the field of artificial intelligence
(AI) by endowing autonomous systems with high levels of understanding of the real world …
(AI) by endowing autonomous systems with high levels of understanding of the real world …
Supervised machine learning: a survey
With the fast up-growth and evolution of new information and communication technologies
and due to the factor of spread universal-connected objects, an ample amount of data has …
and due to the factor of spread universal-connected objects, an ample amount of data has …
Systematic review on impact of different irradiance forecasting techniques for solar energy prediction
As non-renewable energy sources are in the verge of exhaustion, the entire world turns
towards renewable sources to fill its energy demand. In the near future, solar energy will be …
towards renewable sources to fill its energy demand. In the near future, solar energy will be …
Application of reinforcement learning and deep learning in multiple-input and multiple-output (MIMO) systems
The current wireless communication infrastructure has to face exponential development in
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
mobile traffic size, which demands high data rate, reliability, and low latency. MIMO systems …
Reinforcement learning-based intelligent control strategies for optimal power management in advanced power distribution systems: A survey
Intelligent energy management in renewable-based power distribution applications, such as
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …
microgrids, smart grids, smart buildings, and EV systems, is becoming increasingly important …
The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …