Search Results - "bayesian algorithm"

Intelligent fault identification of hydraulic pump using deep adaptive normalized CNN and synchrosqueezed wavelet transform by Tang, Shengnan, Zhu, Yong, Yuan, Shouqi

“…•A normalized CNN is constructed for fault diagnosis of hydraulic piston pump.•Multiple signals are analyzed and used for intelligent fault diagnosis.•Bayesian…”
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Bayesian active machine learning for Cluster expansion construction by Chen, Hantong, Samanta, Sayan, Zhu, Siya, Eckert, Hagen, Schroers, Jan, Curtarolo, Stefano, van de Walle, Axel

“…The Cluster expansion (CE) is a powerful method for representing the energetics of alloys from a fit to first principles energies. However, many common fitting…”
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Biohydrogen from food waste: Modeling and estimation by machine learning based super learner approach by Sultana, Nahid, Hossain, S. M. Zakir, Aljameel, Sumayh S., Omran, M.E., Razzak, S.A., Haq, B., Hossain, M.M.

“…This study demonstrated the application of a hybrid Bayesian algorithm (BA) and support vector regression (SVR) as a potential super-learner tool (BA-SVR) to…”
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Multiple-signal defect identification of hydraulic pump using an adaptive normalized model and S transform by Zhu, Yong, Tang, Shengnan, Yuan, Shouqi

“…Axial piston pump plays a pivotal role in a hydraulic transmission system since it can supply the core power source. The complexity of structure and the…”
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Modeling of microbial fuel cell power generation using machine learning-based super learner algorithms by Zakir Hossain, S.M., Sultana, Nahid, Haji, Shaker, Talal Mufeez, Shaikha, Esam Janahi, Sara, Adel Ahmed, Noof

“…•Bayesian optimization algorithm (BA) was implemented to tune hyperparameters.•Super learner intelligence approaches (BA-SVR; BA-BRT) were developed to predict…”
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Prediction of effluent total nitrogen and energy consumption in wastewater treatment plants: Bayesian optimization machine learning methods by Ye, Gang, Wan, Jinquan, Deng, Zhicheng, Wang, Yan, Chen, Jian, Zhu, Bin, Ji, Shiming

“…[Display omitted] •The same input features enables prediction of effluent TN and TEC in the WWTPs.•The moving average method and Bayesian optimization to…”
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Diesel selective catalytic reduction emission prediction based on physical model data-driven and variational autoencoder-fully connected neural network-improved Bayesian algorithm (VAE-FCNN-IBO) by Wenlong liu, Gao, Ying, Zhu, Qi, You, Yuelin, Xia, Bocong

“…In order to accurately predict NOx and NH3 concentrations downstream of the diesel engine selective catalytic reduction (SCR) system and to improve…”
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Nonlinear Unmixing of Hyperspectral Images Using a Generalized Bilinear Model by Halimi, A., Altmann, Y., Dobigeon, N., Tourneret, J.

“…Nonlinear models have recently shown interesting properties for spectral unmixing. This paper studies a generalized bilinear model and a hierarchical Bayesian…”
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A Hybrid Short-Term Load Forecasting Approach for Individual Residential Customer by Lin, Xin, Zamora, Ramon, Baguley, Craig A., Srivastava, Anurag K.

“…This article proposes a hybrid method (HM) to improve the accuracy of short-term individual residential load forecasting. The HM includes an ensemble model…”
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Application of Variational AutoEncoder (VAE) Model and Image Processing Approaches in Game Design by Mak, Hugo Wai Leung, Han, Runze, Yin, Hoover H. F.

“…In recent decades, the Variational AutoEncoder (VAE) model has shown good potential and capability in image generation and dimensionality reduction. The…”
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A novel fault diagnosis method based on nonlinear-CWT and improved YOLOv8 for axial piston pump using output pressure signal by Xia, Shiqi, Huang, Weidi, Zhang, Jie

“…Axial piston pumps are key components in hydraulic systems. Their condition monitoring and fault diagnosis are essential in ensuring the safety and reliability…”
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Data-driven production optimization using particle swarm algorithm based on the ensemble-learning proxy model by Du, Shu-Yi, Zhao, Xiang-Guo, Xie, Chi-Yu, Zhu, Jing-Wei, Wang, Jiu-Long, Yang, Jiao-Sheng, Song, Hong-Qing

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Potential miRNA-disease association prediction based on kernelized Bayesian matrix factorization by Chen, Xing, Li, Shao-Xin, Yin, Jun, Wang, Chun-Chun

“…Many biological experimental studies have confirmed that microRNAs (miRNAs) play a significant role in human complex diseases. Exploring miRNA-disease…”
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Chisel bits cutting force estimation using XGBoost and different optimization algorithms by Rouhani, Mohammad Matin, Farrokh, Ebrahim

“…The design and selection of tools for mechanized excavations is a crucial topic in the field of tunneling. Chisel bits are commonly used tools for soft ground,…”
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Application of support vector regression and artificial neural network for prediction of specific heat capacity of aqueous nanofluids of copper oxide by Alade, Ibrahim Olanrewaju, Abd Rahman, Mohd Amiruddin, Abbas, Zulkifly, Yaakob, Yazid, Saleh, Tawfik A.

“…•The specific heat capacity (SCH) of CuO/water nanofluids was accurately modelled using SVR and ANN models.•The SVR model has a higher prediction accuracy than…”
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An approach to predict the isobaric specific heat capacity of nitrides/ethylene glycol-based nanofluids using support vector regression by Alade, Ibrahim Olanrewaju, Rahman, Mohd Amiruddin Abd, Saleh, Tawfik A.

“…•SVR model for specific heat capacity of nitrides/EG-based nanofluids is developed.•SVR model parameters were optimized using the Bayesian optimization…”
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Practices and Challenges of Artificial Intelligence-Assisted Teaching in Vocational Undergraduate Public English Classrooms by Wang, Yanhua, Cui, Cui

“…This paper first introduces the architecture of the natural language processing system and then analyzes how natural language processing decomposes the…”
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Dilemmas and Breakthroughs in the Legal Regulation of Artificial Intelligence Based on Deep Learning Models by Li, Yanggui

“…In this paper, we use big data analysis techniques combined with the TF-IDF algorithm to weigh the frequently occurring word frequency vectors in text and…”
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Bayesian Dynamic Matrix Factor Models by Qin, Lei, Wang, Yinzhi, Zhu, Yingqiu, Shia, Ben-Chang

“…The growth in data volume and the expansion in data dimensionality are challenging the analysis of high-dimensional matrix time series. Factor models for…”
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Accident causes data-driven coal and gas outburst accidents prevention: Application of data mining and machine learning in accident path mining and accident case-based deduction by Xuecai, Xie, Xueming, Shu, Gui, Fu, Shifei, Shen, Qingsong, Jia, Jun, Hu, Zhirong, Wu

“…Analyzing the causes of accidents, excavating accident paths, and applying accident prevention are important tasks in safety management. Focusing on coal and…”
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