Search Results - "supervised algorithm"

A dynamic anomaly detection method of building energy consumption based on data mining technology by Lei, Lei, Wu, Bing, Fang, Xin, Chen, Li, Wu, Hao, Liu, Wei

“…Due to the equipment failure and inappropriate operation strategy, it is often difficult to achieve energy-efficient building. Anomaly detection of building…”
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Infrared spectroscopic evaluation for catalytic hydrogenation of biomass and coal using unsupervised and supervised algorithms by Zou, Hai-Xu, Bai, Xiang, Fan, Xing, Wang, Min-Hua, Xu, Yang-Yang, Ma, Feng-Yun, Wei, Xian-Yong, Kuznetsov, Peter N.

“…•Functional groups are effective variables of machine learning for FTIR spectra.•OH is a key factor discriminating the samples because of deoxidation…”
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A Memristive Spiking Neural Network Circuit with Selective Supervised Attention Algorithm by Deng, Zekun, Wang, Chunhua, Lin, Hairong, Sun, Yichuang

“…Spiking neural networks (SNNs) are biologically plausible and computationally powerful. The current computing systems based on the von Neumann architecture are…”
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From flow physics to machine learning: A comprehensive review and future perspectives on axial flow and centrifugal compressors by Li, Quan, An, Guangyao, Ooi, Kim Tiow, Zhang, Qian, Lang, Jinhua, Yuan, Wei, Yan, Junhao, Zhang, Lei

“…Axial flow and centrifugal compressors (AF & CCs) have ushered in a technological revolution in the fields of thrust generation, power storage, and…”
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A self‐supervised strategy for fully automatic segmentation of renal dynamic contrast‐enhanced magnetic resonance images by Huang, Wenjian, Li, Hao, Wang, Rui, Zhang, Xiaodong, Wang, Xiaoying, Zhang, Jue

“…Purpose An automated accurate segmentation for dynamic contrast‐enhanced magnetic resonance (DCE‐MR) image sequences is essential for quantification of renal…”
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Multi-branch global Transformer‐assisted network for fault diagnosis by Shao, Xiaorui, Kim, Chang-Soo

“…Fault Diagnosis (FD) is critical in smart manufacturing, enabling predictive maintenance, reducing operational costs, and enhancing system reliability. To deal…”
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Self-supervised spectral clustering with exemplar constraints by Bai, Liang, Zhao, Yunxiao, Liang, Jiye

“…•Define an exemplar constraint for self-supervised spectral clustering.•Construct an optimization model of self-supervised spectral clustering.•Show the…”
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Supervised Weighting-Online Learning Algorithm for Short-Term Traffic Flow Prediction by Young-Seon Jeong, Young-Ji Byon, Mendonca Castro-Neto, Manoel, Easa, Said M.

“…Prediction of short-term traffic flow has become one of the major research fields in intelligent transportation systems. Accurately estimated traffic flow…”
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Bank Customer Segmentation Model Using Machine Learning by Bunga Tiara, Vira, Siregar, Amril Mutoi, Kusumaningrum, Dwi Sulistya Kusumaningrum, Rohana, Tatang

“…Banks generally carry out marketing strategies by offering deposit products directly to customers. However, this method is less effective because it requires…”
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DC-net: Dual-Consistency semi-supervised learning for 3D left atrium segmentation from MRI by Wang, Junying, Liu, Xiaoli, Yin, Jianqin, Ding, Pengxiang

“…Left atrial segmentation is very important for the treatment of atrial fibrillation. One factor limiting the automatic segmentation of the left atrium is that…”
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Predicting postural risk level with computer vision and machine learning on multiple sources of images by Doong, Shing Hwang

“…Postural risk level assesses the degree of potential harms to a human body due to bad postures often encountered in workplaces. If accurate 3-dimensional…”
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Anomaly detection in NetFlow network traffic using supervised machine learning algorithms by Fosić, Igor, Žagar, Drago, Grgić, Krešimir, Križanović, Višnja

“…Anomaly detection is an important method for monitoring network traffic where is important to successfully distinguish normal traffic from abnormal traffic…”
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Intelligent threat detection framework for serverless cloud computing architecture using supervised ML algorithms by Kasuba, Tulasi, Saravanan, S., Balaram, V. V. S. S. S.

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Self-supervised spectral clustering with spectral embedding for hyperspectral image classification by Wu, Chengmao, Zhang, Jiale

“…Spectral clustering, as an algorithm based on graph theory and spectral theory, has shown excellent performance in the classification tasks of hyperspectral…”
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An application of machine learning with feature selection to improve diagnosis and classification of neurodegenerative disorders by Álvarez, Josefa Díaz, Matias-Guiu, Jordi A., Cabrera-Martín, María Nieves, Risco-Martín, José L., Ayala, José L.

“…Background The analysis of health and medical data is crucial for improving the diagnosis precision, treatments and prevention. In this field, machine learning…”
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A machine learning framework to classify Southeast Asian echolocating bats by Yoh, Natalie, Kingston, Tigga, McArthur, Ellen, Aylen, Oliver E., Huang, Joe Chun-Chia, Jinggong, Emy Ritta, Khan, Faisal Ali Anwarali, Lee, Benjamin P.Y.H., Mitchell, Simon L., Bicknell, Jake E., Struebig, Matthew J.

“…•We present a hierarchical framework for designing automated bat call classifiers.•Our classifier identifies 85% of calls correctly to 1 of 4 ecological…”
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Companion: A Social Support Generating Application for Lonely and Socially Isolated Individuals using Lazy Supervised Algorithm by Buctuanon, Marisa, Comabig, Xavier, Mayola, Wavina Vivienne

“…The adverse effect of depression, which is a significant health problem associated with loneliness and social isolation, leads to suicidal ideation, alcohol…”
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A Model to Detect the Fraud of Electronic Payment Card Transactions Based on Stream Processing in Big Data by Banirostam, Hamid, Banirostam, Touraj, Pedram, Mir Mohsen, Rahmani, Amir Masoud

“…With the growing use of electronic cash cards, the number of transactions with these cards has also increased rapidly, so the importance of using fraud…”
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A Clinical Data Analysis Based Diagnostic Systems for Heart Disease Prediction Using Ensemble Method by Kumar, Ankit, Singh, Kamred Udham, Kumar, Manish

“…The correct diagnosis of heart disease can save lives, while the incorrect diagnosis can be lethal. The UCI machine learning heart disease dataset compares the…”
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Learning structured medical information from social media by Hasan, Abul, Levene, Mark, Weston, David

“…Our goal is to summarise and aggregate information from social media regarding the symptoms of a disease, the drugs used and the treatment effects both…”
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