2020
DOI: 10.1016/j.pnucene.2020.103308
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Determination of alarm templates for decision support in nuclear power plants alarm floods using evolutionary computation

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Cited by 9 publications
(4 citation statements)
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“…Content may change prior to final publication. [160] Colored Petri Nets [193], [197], [198] Tree Methods [50], [200] Unsupervised Learning [161], [181] Fuzzy Methods [159], [182]- [189], [192], [195], [201] Other Models/Algorithms Physical Plant-centered [39], [53], [86]- [88], [123], [127]- [129], [150], [175], [193] Cyber System Layer & Physical System Layer ANN [105], [160] Fuzzy Colored Petri Nets (FCPN) [106] Reinforcement Learning (RL) [107], [108], [134]- [137] Recurrent Neural Network (RNN) [95], [97], [138], [138], [139], [146] Convolutional Neural Network (CNN) [140]- [142] Deep Belief Network [90], [121] SVM [118], [119], [122] Tree Methods [124]-…”
Section: Discussionmentioning
confidence: 99%
See 1 more Smart Citation
“…Content may change prior to final publication. [160] Colored Petri Nets [193], [197], [198] Tree Methods [50], [200] Unsupervised Learning [161], [181] Fuzzy Methods [159], [182]- [189], [192], [195], [201] Other Models/Algorithms Physical Plant-centered [39], [53], [86]- [88], [123], [127]- [129], [150], [175], [193] Cyber System Layer & Physical System Layer ANN [105], [160] Fuzzy Colored Petri Nets (FCPN) [106] Reinforcement Learning (RL) [107], [108], [134]- [137] Recurrent Neural Network (RNN) [95], [97], [138], [138], [139], [146] Convolutional Neural Network (CNN) [140]- [142] Deep Belief Network [90], [121] SVM [118], [119], [122] Tree Methods [124]-…”
Section: Discussionmentioning
confidence: 99%
“…The decision making would become more reliable and efficient with such risk estimation and a better maintenance strategy could be taken. Roberto et al [201], however, apply Quantum Evolutionary Algorithm (QEA) in the decision support system in order to handle alarm floods. More recent researches attempt to design a deeper integration system of AI and traditional NPPs' decision-making systems.…”
Section: ) Decision-making Assistancementioning
confidence: 99%
“…However, due to the complexity and large scale of the power grid, there may be various abnormal situations in the power system, such as equipment failures, voltage fluctuations, current overload, etc. If these abnormal data cannot be detected and processed in a timely manner, it will have a negative impact on the normal operation and power supply reliability of the power grid [1][2][3]. However, traditional manual analysis methods have problems such as low efficiency and low reliability.…”
Section: Introductionmentioning
confidence: 99%
“…They effectively identified corresponding alarms and their evolution path . Schirru et al adopted quantum evolutionary algorithms to determine a minimum alarm set to isolate one fault from others and provided critical information enabling operators to effectively implement measures to mitigate current failures. In addition, there are a large number of data-driven causal algorithms, e.g., the gray theory, which is based on discrete data sequence modeling, the Granger causality analysis algorithm, which calculates the scale of the relationship between sequences, and the intuitive Bayesian network technique …”
Section: Introductionmentioning
confidence: 99%