Research on Multi-Model Fusion for Multi-Indicator Collaborative Anomaly Prediction in IoT Devices. Conference Paper. May 2024. Donghao Wang · Tengjiang Wang ...
Jan 7, 2022 · This paper predicts the anomalies on the 350K data set using the Machine Learning models and compares its performance based on the state of arts.
A stacked ensemble meta-learning (SEM) model [98] is proposed to boost the effectiveness of the base machine learning model for IoT device anomaly detection.
Compared with other algorithms, this model with multi-mode data fusion CNN algorithm improves the data transmission rate, reduces the average data delay, and ...
Nov 16, 2023 · In this paper, we proposed intelligent anomaly detection and classification based on deep learning (DL) using multi-modal fusion.
Missing: Collaborative | Show results with:Collaborative
Oct 21, 2024 · Adaptive anomaly detection for IoT: We designed an edge collaborative framework based on adaptive parameter adjustment. This framework can ...
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Therefore, this paper presents a systematic mapping study on AD for industrial machinery using IoT devices and ML algorithms to address this gap. Our primary ...
Jul 12, 2024 · This paper proposes a multi-information fusion model based on a convolutional neural network and AutoEncoder.
Missing: Indicator Collaborative
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Our research has investigated the use of active learning-based algorithms for anomaly detection in IoT systems.
Nov 30, 2023 · This research has examined the use of deep learning models for prediction, anomaly detection, and correction of data generated by IoT devices.
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