Výsledky vyhledávání - "Sparse denoising autoencoder"

Stacked pruning sparse denoising autoencoder based intelligent fault diagnosis of rolling bearings Autor Zhu, Haiping, Cheng, Jiaxin, Zhang, Cong, Wu, Jun, Shao, Xinyu

“…This paper proposes a new stacked pruning sparse denoising autoencoder (sPSDAE) model for intelligent fault diagnosis of rolling bearings. Different from the…”
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A stacked convolutional sparse denoising autoencoder model for underwater heterogeneous information data Autor Wang, Xingmei, Zhao, Yixu, Teng, Xuyang, Sun, Weiqi

“…•A novel stacked convolutional sparse denoising autoencoder (SCSDA) model is proposed.•The unrelated dataset was developed to simulate the underwater…”
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Early fault detection method for nuclear power plants based on sparse denoising autoencoder and kernel principal component analysis Autor Yin, Wenzhe, Xia, Hong, Huang, Xueying, Shan, Longfei, Ran, Wenhao, Jia, Zhujun

“…•A data-driven fault detection method is proposed, which can accurately detect early faults in nuclear power plants.•The proposed grouping strategy effectively…”
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Harnessing feature pruning with optimal deep learning based DDoS cyberattack detection on IoT environment Autor Yang, Eunmok, Jeong, Sooyong, Seo, Changho

“…The swift development of the Internet of Things (IoT) devices has created a pressing need for effective cybersecurity measures. They are vulnerable to…”
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An improved pollution forecasting model with meteorological impact using multiple imputation and fine-tuning approach Autor Samal, K. Krishna Rani, Panda, Ankit Kumar, Babu, Korra Sathya, Das, Santos Kumar

“…Air pollution forecasting is a significant step for air quality pollution management to mitigate pollution’s negative impact on the environment and people’s…”
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Effective Flood prediction model based on Twitter Text and Image analysis using BMLP and SDAE-HHNN Autor Kamoji, Supriya, Kalla, Mukesh

“…In recent years, social media platforms such as Twitter have garnered a lot of interest as a new source of text data for quick flood awareness and effective…”
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Maximal overlap discrete wavelet transform and deep learning for robust denoising and detection of power quality disturbance Autor Xiao, Fei, Lu, Tianguang, Wu, Mingli, Ai, Qian

“…This study presents a new technique for power quality (PQ) disturbance detection. The technique focuses on voltage sags and interruptions that are related to…”
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Enhanced CNN for Fruit Disease Detection and Grading Classification Using SSDAE-SVM for Postharvest Fruits Autor Patel, Himanshu B., Patil, Nitin J.

“…In the realm of agriculture, leveraging image processing has become pivotal for robust image analysis, especially in detecting fruit diseases. However,…”
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Self-Supervised Marine Noise Learning with Sparse Autoencoder Network for Generative Target Magnetic Anomaly Detection Autor Wang, Shigang, Zhang, Xiangyuan, Zhao, Yifan, Yu, Haozi, Li, Bin

“…As an effective physical field feature to perceive ferromagnetic targets, magnetic anomaly is widely used in covert marine surveillance tasks. However, its…”
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Intelligent Fault Diagnosis Method for Blade Damage of Quad-Rotor UAV Based on Stacked Pruning Sparse Denoising Autoencoder and Convolutional Neural Network Autor Yang, Pu, Wen, Chenwan, Geng, Huilin, Liu, Peng

“…This paper introduces a new intelligent fault diagnosis method based on stack pruning sparse denoising autoencoder and convolutional neural network…”
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A Novel Day- ahead Electricity Price Forecasting Using multi-modal combined Integration via Stacked Pruning Sparse Denoising Auto Encoder Autor Liangping Sun, Leiming Li, Bingquan Liu, Sara Saeedi

“…One of the best options for managing energy markets and power system performance optimization is precise Electricity Price Forecasting (EPF). In detecting the…”
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The fault diagnosis method of rolling bearing under variable working conditions based on deep transfer learning Autor Dong, Shaojiang, He, Kun, Tang, Baoping

“…The vibration signals of rolling bearing obtained under variable working conditions do not obey the same independent distribution so that the traditional…”
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Fault diagnosis of aircraft engines based on multi-sensor fusion sparse denoising autoencoder Autor He, ShiJie, Wang, Zhi-Ming, Liu, Kun-Zhi, Sun, Xi-Ming

“…As the heart of an aircraft, it is crucial to accurately grasp the operational status of aeroengines. However, it is difficult to fully reflect the accurate…”
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Fault Diagnosis of Rolling Bearing Based on Multiscale Intrinsic Mode Function Permutation Entropy and a Stacked Sparse Denoising Autoencoder Autor Dai, Juying, Tang, Jian, Shao, Faming, Huang, Shuzhan, Wang, Yangyang

“…Effective intelligent fault diagnosis of bearings is important for improving safety and reliability of machine. Benefiting from the training advantages, deep…”
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自编码网络在JavaScript恶意代码检测中的应用研究 Autor 龙廷艳, 万良, 丁红卫

“…TP391; 针对传统机器学习特征提取方法很难发掘JavaScript恶意代码深层次本质特征的问题,提出基于堆栈式稀疏降噪自编码网络(sSDAN)的JavaScript恶意代码检测方法.首先…”
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The optimally designed autoencoder network for compressed sensing Autor Zhang, Zufan, Wu, Yunfeng, Gan, Chenquan, Zhu, Qingyi

“…Compressed sensing (CS) is a signal processing framework, which reconstructs a signal from a small set of random measurements obtained by measurement matrices…”
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Deep Learning-Based Machinery Fault Diagnostics

“…This book offers a compilation for experts, scholars, and researchers to present the most recent advancements, from theoretical methods to the applications of…”
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Application of stack marginalised sparse denoising auto-encoder in fault diagnosis of rolling bearing Autor Zhang, Junling, Chen, Zhigang, Du, Xiaolei, Xu, Xu, Yu, Miao

“…When a fracturing vehicle is working, it generally needs to bear high loads, media corrosion and erosion. For this special working environment, this study…”
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MOCSC: a multi-omics data based framework for cancer subtype classification Autor Ma, Yuanling, Guan, Jinting

“…Using multi-omics data to achieve the classification of cancer subtypes from the perspective of machine learning can facilitate the understanding of cancer…”
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Denoising hybrid noises in image with stacked autoencoder Autor Xiufen Ye, Lin Wang, Huiming Xing, Le Huang

“…A method based on sparse denoising autoencoder for denoising hybrid noises in image is proposed in this paper. The method is experimented on natural images and…”
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