zhouzhouwen
UTokyo PhD; AI for fluid mechanics, two-phase flow, thermal hydraulics, and nuclear. Email: philzhouwen@gmail.com
Tokyo
Pinned Repositories
Advanced-AI-Segmentation-of-Air-Entrainment-Motion-YOLO-with-Attention-Mechanism-and-NSGA-III-BPNN
An-AI-method-for-the-HCSB-blanket-based-on-an-improved-NSGA-III-and-an-adaptive-BPNN
An-improved-PINNs-with-the-adaptive-weight-sampling-and-DE-algorithm
An improved and generic PINNs for fluid dynamic analysis is proposed. This approach incorporates three key improvements: residual-based adaptive sampling, which automatically samples points in areas with larger residuals; adaptive loss weights, which balance the loss terms effectively; and the utilization of the DE optimization algorithm
BF-GAN
BF-GAN: Development of an AI-driven Bubbly Flow Image Generation Model Using Bubbly Generative Adversarial Networks
BP-neural-network-based-reconstruction-method-for-radiation-field-applications
Bubble_detection_and_tracking_AI_based_YOLO_tracking_alogrithm
Bubble feature extraction in subcooled flow boiling using AI-based object detection and tracking techniques
cutting-edge-artificial-intelligence-methods-for-prediction-of-critical-heat-flux
The-Robust-Development-of-a-TH-Analysis-Method-for-Bubbles-Using-AI
two-phase-flow-by-self_adaptive-and-time_divide_conquer-PINNs
zhouzhouwen
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zhouzhouwen's Repositories
zhouzhouwen/An-improved-PINNs-with-the-adaptive-weight-sampling-and-DE-algorithm
An improved and generic PINNs for fluid dynamic analysis is proposed. This approach incorporates three key improvements: residual-based adaptive sampling, which automatically samples points in areas with larger residuals; adaptive loss weights, which balance the loss terms effectively; and the utilization of the DE optimization algorithm
zhouzhouwen/two-phase-flow-by-self_adaptive-and-time_divide_conquer-PINNs
zhouzhouwen/BF-GAN
BF-GAN: Development of an AI-driven Bubbly Flow Image Generation Model Using Bubbly Generative Adversarial Networks
zhouzhouwen/Advanced-AI-Segmentation-of-Air-Entrainment-Motion-YOLO-with-Attention-Mechanism-and-NSGA-III-BPNN
zhouzhouwen/cutting-edge-artificial-intelligence-methods-for-prediction-of-critical-heat-flux
zhouzhouwen/An-AI-method-for-the-HCSB-blanket-based-on-an-improved-NSGA-III-and-an-adaptive-BPNN
zhouzhouwen/BP-neural-network-based-reconstruction-method-for-radiation-field-applications
zhouzhouwen/Bubble_detection_and_tracking_AI_based_YOLO_tracking_alogrithm
Bubble feature extraction in subcooled flow boiling using AI-based object detection and tracking techniques
zhouzhouwen/The-Robust-Development-of-a-TH-Analysis-Method-for-Bubbles-Using-AI
zhouzhouwen/zhouzhouwen
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zhouzhouwen/BubbleML
SciML for multi-phase boiling problems
zhouzhouwen/PINN-for-turbulence
A pytorch implementation of several approaches using PINN to slove turbulent flow
zhouzhouwen/RayTrace
基于OpenGL实现的光线追踪算法
zhouzhouwen/stock-price-prediction-BPNN-LSTM
Use BPNN and LSTM to forecast stock price. 使用BP神经网络和LSTM预测股票价格,注释拉满。
zhouzhouwen/test