4篇
您的检索式：作者名="Ruilong DENG"
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| 1 | Minimax entropy-based co-training for fault diagnosis of blast furnace显示文摘Due to the problems of few fault samples and large data fluctuations in the blast furnace(BF)ironmaking process,some transfer learning-based fault diagnosis methods are proposed.The vast majority of such methods perform distribution adaptation by reducing the distance between data distributions and applying a classifier to generate pseudo-labels for self-training.However,since the training data is dominated by labeled source domain data,such classifiers tend to be weak classifiers in the target domain.In addition,the features generated after domain adaptation are likely to be at the decision boundary,resulting in a loss of classification performance.Hence,we propose a novel method called minimax entropy-based co-training(MMEC)that adversarially optimizes a transferable fault diagnosis model for the BF.The structure of MMEC includes a dual-view feature extractor,followed by two classifiers that compute the feature's cosine similarity to representative vector of each class.Knowledge transfer is achieved by alternately increasing and decreasing the entropy of unlabeled target samples with the classifier and the feature extractor,respectively.Transfer BF fault diagnosis experiments show that our method improves accuracy by about 5%over state-of-the-art methods. | Dali Gao Chunjie Yang Bo Yang Yu Chen Ruilong Deng | 2023 | Chinese Journal of Chemical Engineering2023，59，7： | 0 |
| 2 | Sliding window games for cooperative building temperature control using a distributed learning method显示文摘In practice, an energy consumer often consists of a set of residential or commercial buildings, with individual units that are expected to cooperate to achieve overall optimization under modern electricity operations,such as time-of-use price. Global utility is decomposed to the payoff of each player, and each game is played over a prediction horizon through the design of a series of sliding window games by treating each building as a player.During the games, a distributed learning algorithm based on game theory is proposed such that each building learns to play a part of the global optimum through state transition. The proposed scheme is applied to a case study of three buildings to demonstrate its effectiveness. | Zhaohui ZHANG Ruilong DENG Tao YUAN S.Joe QIN | 2017 | Frontiers of Engineering Management2017，4，3： | 0 |
| 3 | Detecting the One-Shot Dummy Attack on the Power Industrial Control Processes With an Unsupervised Data-Driven Approach显示文摘Dear Editor,Dummy attack(DA), a deep stealthy but impactful data integrity attack on power industrial control processes, is recently recognized as hiding the corrupted measurements in normal measurements. In this letter, targeting a more practical case, we aim to detect the oneshot DA, with the purpose of revealing the DA once it is launched.Specifically, we first formulate an optimization problem to generate one-shot DAs. Then, an unsupervised data-driven approach based on a modified local outlier factor(MLOF) is proposed to detect them. | Zhenyong Zhang Yan Qin Jingpei Wang Hui Li Ruilong Deng | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，2： | 0 |
| 4 | Impact Analysis of MTD on the Frequency Stability in Smart Grid显示文摘Dear Editor, In order to accommodate the effects of false data injection attacks(FDIAs), the moving target defense(MTD) strategy is recently proposed to enhance the security of the smart grid by perturbing branch susceptances. However, most pioneer work only focus on the defending performance of MTD in terms of detecting FDIAs and the impact of MTD on the static factors such as the power and economic losses. | Zhenyong Zhang Ruilong Deng | 2023 | IEEE/CAA Journal of Automatica Sinica2023，10，1： | 0 |
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