Suchergebnisse - Physics-embedded algorithm structure

Physics-informed machine learning in prognostics and health management: State of the art and challenges von DENG, Weikun, NGUYEN, Khanh T.P., MEDJAHER, Kamal, GOGU, Christian, MORIO, Jérôme

“… •Systematic bibliometric analysis of PIML in PHM.•Novel perspectives for PIML from the “Informed knowledge forms” and “Informed methods”.•Taxonomy of PIML …”
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A review of physics-informed machine learning for building energy modeling von Ma, Zhihao, Jiang, Gang, Hu, Yuqing, Chen, Jianli

“… ) algorithms in recent years, several challenges remain to apply these data-driven approaches in BEM, including the necessity of obtaining sufficient and high-quality training data in algorithm …”
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Physics-embedded inverse analysis with algorithmic differentiation for the earth’s subsurface von Wu, Hao, Greer, Sarah Y., O’Malley, Daniel

“… We use a physics-embedded generative model, which takes statistically simple parameters as input and outputs subsurface properties (e.g …”
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Layered Soil Remote Sensing With Multichannel Passive Microwave Observations Using a Physics-Embedded Artificial Intelligence Framework: A Theoretical Study von Bai, Xuyang, Tan, Shurun

“… using multichannel passive microwave observations. To enhance the inversion efficiency and accuracy, a novel physics-embedded artificial neural network (P-ANN …”
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Physics‐Embedded Machine Learning for Fatigue Cumulative Damage Prediction von Gao, Zhiyuan, Jiang, Xiaomo, Guo, Yifan, Cui, Mingqing, Wang, Shengbo

“… This study proposes an innovative physics‐embedded machine learning (ML) framework to enhance residual fatigue damage prediction by integrating the Manson–Halford (MH …”
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Physics-embedded deep learning inversion for transient electromagnetic method survey data von Li, Ruiyou, Zhang, Yong, Ju, Jiayi, Liu, Rongqiang

“… The transient electromagnetic method (TEM) is a widely used geophysical technique for investigating complex geological conditions. Deep learning (DL) provides …”
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Layered Soil Remote Sensing with Multi-Channel Passive Microwave Observations Using A Physics Embedded Artificial Intelligence Framework: A Theoretical Study von Bai, Xuyang, Tan, Shurun

“… using multi-channel passive microwave observations. To enhance the inversion efficiency and accuracy, a novel Physics-Embedded Artificial Neural Network (P-ANN …”
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A physics-embedded deep-learning framework for efficient multi-fidelity modeling applied to guided wave based structural health monitoring von Nerlikar, Vivek, Miorelli, Roberto, Recoquillay, Arnaud, d’Almeida, Oscar

“… Health monitoring of structures using ultrasonic guided waves is an evolving technology with potential applications in monitoring pipelines, civil bridges, and aircraft components …”
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Data-Driven Perovskite Design via High-Throughput Simulation and Machine Learning von Wang, Yidi, Sun, Dan, Zhao, Bei, Zhu, Tianyu, Liu, Chengcheng, Xu, Zixuan, Zhou, Tianhang, Xu, Chunming

“… ) in accelerating perovskite discovery. By harnessing existing experimental datasets and high-throughput computational results, ML models elucidate structure-property relationships and predict performance metrics for solar cells, (photo …”
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A Planar Array Synthesis Method Based on Deep Learning and Radiation Pattern Superposition Method von Huang, Jianming, Liu, Rui, Zhang, Naibo, Cui, Yansong, Ren, Weizheng, Guo, Qiuquan, Du, Yanjun, Zhao, Jiayu

“… A dual-branched convolutional neural network (CNN) integrated with hybrid training criteria is proposed for real-time multibeam synthesis in planar uniform …”
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Rings: An efficient Java/Scala library for polynomial rings von Poslavsky, Stanislav

“… Rings can be easily interacted or embedded in applications in high-energy physics and other research areas via a simple API with fully typed hierarchy of algebraic structures and algorithms for commutative algebra …”
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A Model-Driven Realization of AUV Controllers Based on the MDA/MBSE Approach von Van Thuan Truong, Ngoc Tam Bui, Ngo Van Hien

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Rings: an efficient Java/Scala library for polynomial rings von Poslavsky, Stanislav

“… \Rings can be easily interacted or embedded in applications in high-energy physics and other research areas via a simple API with fully typed hierarchy of algebraic structures and algorithms for commutative algebra …”
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Computational techniques for studying protein-protein interactions

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Chapter 9 - Computational techniques for studying protein-protein interactions von Al-Khafaji, Khattab, Taskin-Tok, Tugba

“… The developers, engineers, and scientists are working to develop algorithms and methodological strategies for PPIs analysis, where the laws …”
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