Editorial to special issue on hybrid artificial intelligence and machine learning technologies in intelligent systems
Article
Pandey, H., Bessis, N., Das, S., Windridge, D. and Chaudhary, A. 2020. Editorial to special issue on hybrid artificial intelligence and machine learning technologies in intelligent systems. Neural Computing and Applications. 32 (12), pp. 7743-7745. https://doi.org/10.1007/s00521-020-04903-w
Type | Article |
---|---|
Title | Editorial to special issue on hybrid artificial intelligence and machine learning technologies in intelligent systems |
Authors | Pandey, H., Bessis, N., Das, S., Windridge, D. and Chaudhary, A. |
Abstract | Artificial intelligence (AI) has grown widely across domains. The current trends of AI and machine learning (ML) techniques are centered toward hybridization to improve performance of the systems. Our society will shortly become populated with intelligent systems that are able to perform tasks without human intervention and communicate with their surroundings, which totally transforming the century-old traditional human-based system. Despite the immense growth of the various AI and ML techniques, there are many challenges and threats which limit the performance of these techniques. However, due to the increasing demands, we have noticed the evolution of the intelligent systems which are empowered by AI and ML techniques, some of them are hybrid metaheuristic algorithms, classification, clustering, Bayesian hierarchical modeling, deep learning and re-enforcements learning. There exist several scientific projects in progress for the development/enhancement of intelligent systems. We also noticed that few on-going scientific projects are based on simulation hypothesis where biological inspired dream simulation mechanism has been incorporated to handle off-line simulation. |
Publisher | Springer, London |
Journal | Neural Computing and Applications |
ISSN | 0941-0643 |
Electronic | 1433-3058 |
Publication dates | |
Online | 18 Apr 2020 |
30 Jun 2020 | |
Publication process dates | |
Deposited | 14 May 2021 |
Accepted | 31 Mar 2020 |
Output status | Published |
Digital Object Identifier (DOI) | https://doi.org/10.1007/s00521-020-04903-w |
Web of Science identifier | WOS:000527905700001 |
Language | English |
https://repository.mdx.ac.uk/item/895xq
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