Matches in SemOpenAlex for { <https://semopenalex.org/work/W3167241232> ?p ?o ?g. }
- W3167241232 endingPage "17" @default.
- W3167241232 startingPage "17" @default.
- W3167241232 abstract "Artificial Intelligence (AI) is playing a dominant role in the 21<sup>st</sup> century. Organizations have more data than ever, so it’s crucial to ensure that the analytics team should differentiate between Interesting Data and Useful Data. Amongst the important aspects in Machine Learning are “Feature Selection” and “Feature Extraction”. We are now witnessing the emerging fourth industrial revolution and a considerable number of evolutionary changes in machine learning methodologies to achieve operational excellence in operating and maintaining the industrial assets efficiently, reliably, safely and cost-effectively. AI techniques such as, knowledge based systems, expert systems, artificial neural networks, genetic algorithms, fuzzy logic, case-based reasoning and any combination of these techniques (hybrid systems), machine learning, biomimicry such as swarm intelligence and distributed intelligence. are widely used by multi-disciplinarians to solve a whole range of hitherto intractable problems associated with the proactive maintenance management of industrial assets. In this paper, an attempt is made to review the role of artificial intelligence in condition monitoring and diagnostic engineering management of modern engineering assets. The paper also highlights that unethical and immoral misuse of AI is dangerous." @default.
- W3167241232 created "2021-06-22" @default.
- W3167241232 creator A5081212525 @default.
- W3167241232 date "2021-01-01" @default.
- W3167241232 modified "2023-10-01" @default.
- W3167241232 title "The Role of Artificial Intelligence (AI) in Condition Monitoring and Diagnostic Engineering Management (COMADEM): A Literature Survey" @default.
- W3167241232 cites W1485268022 @default.
- W3167241232 cites W1556057767 @default.
- W3167241232 cites W1606563312 @default.
- W3167241232 cites W1969575648 @default.
- W3167241232 cites W1992115988 @default.
- W3167241232 cites W2002906715 @default.
- W3167241232 cites W2003341526 @default.
- W3167241232 cites W2003916732 @default.
- W3167241232 cites W2022748240 @default.
- W3167241232 cites W2034551923 @default.
- W3167241232 cites W2034704790 @default.
- W3167241232 cites W2055040905 @default.
- W3167241232 cites W2056938850 @default.
- W3167241232 cites W2061831044 @default.
- W3167241232 cites W2063789075 @default.
- W3167241232 cites W2082985613 @default.
- W3167241232 cites W2086688788 @default.
- W3167241232 cites W2089501235 @default.
- W3167241232 cites W2096557925 @default.
- W3167241232 cites W2099308299 @default.
- W3167241232 cites W2103260896 @default.
- W3167241232 cites W2109169458 @default.
- W3167241232 cites W2121826611 @default.
- W3167241232 cites W2125290375 @default.
- W3167241232 cites W2142845742 @default.
- W3167241232 cites W2149631558 @default.
- W3167241232 cites W2160203079 @default.
- W3167241232 cites W2168586043 @default.
- W3167241232 cites W2168891878 @default.
- W3167241232 cites W2231980452 @default.
- W3167241232 cites W2323341821 @default.
- W3167241232 cites W2549204907 @default.
- W3167241232 cites W2566790218 @default.
- W3167241232 cites W2578847807 @default.
- W3167241232 cites W2584915873 @default.
- W3167241232 cites W2593657034 @default.
- W3167241232 cites W2597962469 @default.
- W3167241232 cites W2606213502 @default.
- W3167241232 cites W2613720938 @default.
- W3167241232 cites W2772511931 @default.
- W3167241232 cites W2789728736 @default.
- W3167241232 cites W2792146332 @default.
- W3167241232 cites W2793062918 @default.
- W3167241232 cites W2794053249 @default.
- W3167241232 cites W2804780212 @default.
- W3167241232 cites W2883271815 @default.
- W3167241232 cites W2888056532 @default.
- W3167241232 cites W2890190333 @default.
- W3167241232 cites W2909823287 @default.
- W3167241232 cites W2912998911 @default.
- W3167241232 cites W2970789818 @default.
- W3167241232 cites W2971463251 @default.
- W3167241232 cites W2982476072 @default.
- W3167241232 cites W2989944765 @default.
- W3167241232 cites W2994186506 @default.
- W3167241232 cites W3138496105 @default.
- W3167241232 cites W32688559 @default.
- W3167241232 cites W80111725 @default.
- W3167241232 doi "https://doi.org/10.11648/j.ajai.20210501.12" @default.
- W3167241232 hasPublicationYear "2021" @default.
- W3167241232 type Work @default.
- W3167241232 sameAs 3167241232 @default.
- W3167241232 citedByCount "6" @default.
- W3167241232 countsByYear W31672412322021 @default.
- W3167241232 countsByYear W31672412322022 @default.
- W3167241232 countsByYear W31672412322023 @default.
- W3167241232 crossrefType "journal-article" @default.
- W3167241232 hasAuthorship W3167241232A5081212525 @default.
- W3167241232 hasBestOaLocation W31672412321 @default.
- W3167241232 hasConcept C108583219 @default.
- W3167241232 hasConcept C119857082 @default.
- W3167241232 hasConcept C154945302 @default.
- W3167241232 hasConcept C157170001 @default.
- W3167241232 hasConcept C17744445 @default.
- W3167241232 hasConcept C199539241 @default.
- W3167241232 hasConcept C2777352838 @default.
- W3167241232 hasConcept C2778827112 @default.
- W3167241232 hasConcept C41008148 @default.
- W3167241232 hasConceptScore W3167241232C108583219 @default.
- W3167241232 hasConceptScore W3167241232C119857082 @default.
- W3167241232 hasConceptScore W3167241232C154945302 @default.
- W3167241232 hasConceptScore W3167241232C157170001 @default.
- W3167241232 hasConceptScore W3167241232C17744445 @default.
- W3167241232 hasConceptScore W3167241232C199539241 @default.
- W3167241232 hasConceptScore W3167241232C2777352838 @default.
- W3167241232 hasConceptScore W3167241232C2778827112 @default.
- W3167241232 hasConceptScore W3167241232C41008148 @default.
- W3167241232 hasIssue "1" @default.
- W3167241232 hasLocation W31672412321 @default.
- W3167241232 hasOpenAccess W3167241232 @default.
- W3167241232 hasPrimaryLocation W31672412321 @default.
- W3167241232 hasRelatedWork W2911455822 @default.