A5015951797- Probabilistic and Robust Engineering Design
- Advanced Multi-Objective Optimization Algorithms
- Structural Health Monitoring Techniques
- Fatigue and fracture mechanics
- Optimal Experimental Design Methods
- Structural Response to Dynamic Loads
- Concrete Corrosion and Durability
- Reliability and Maintenance Optimization
- Control Systems and Identification
- Statistical Distribution Estimation and Applications
- Risk and Safety Analysis
- Non-Destructive Testing Techniques
- Fault Detection and Control Systems
- Neuroendocrine regulation and behavior
- Solid State Laser Technologies
- Topic Modeling
- Model Reduction and Neural Networks
- Stress Responses and Cortisol
- Geological and Geochemical Analysis
- Reinforcement Learning in Robotics
- Neural Networks and Applications
- Speech and Audio Processing
- Speech Recognition and Synthesis
- Neural dynamics and brain function
- Sleep and Work-Related Fatigue
Northwestern Polytechnical University
2016-2025
Binzhou University
2025
Binzhou Medical University
2025
Shenzhen Institutes of Advanced Technology
2018-2024
Chinese Academy of Sciences
2008-2024
Dalian National Laboratory for Clean Energy
2020-2024
Collaborative Innovation Center of Chemistry for Energy Materials
2024
Digital Research Alliance of Canada
2022-2024
CE Technologies (United Kingdom)
2023-2024
Dalian Institute of Chemical Physics
2020-2024
The Bayesian failure probability inference (BFPI) framework provides a well-established approach to quantifying our epistemic uncertainty about the resulting from limited number of performance function evaluations. However, it is still challenging perform active learning by taking advantage BFPI framework. In this work, three methods are proposed under name 'partially cubature' (PBALC), based on cleaver use for structural reliability analysis, especially when small probabilities involved....
Line sampling (LS) is a powerful stochastic simulation method for structural reliability analysis, especially assessing small failure probabilities. To further improve the performance of traditional LS, Bayesian active learning idea has been successfully pursued. This work presents another alternative, called 'Bayesian line with log-normal process' (BAL-LS-LP), to LS. In this method, we assign an LP prior instead Gaussian process over distance function so as account its non-negativity...
The sluggish kinetics for anodic oxygen evolution reaction (OER) and insufficient catalytic performance over the corresponding Ir-based catalysts are still enormous challenges in proton exchange membrane water electrolyzer (PEMWE). Herein, it is reported that KIr
The accurate and timely monitoring evaluation of the regional grain crop yield is more significant for formulating import export plans agricultural products, regulating markets adjusting planting structure. In this study, an improved Carnegie–Ames–Stanford approach (CASA) model was coupled with time-series satellite remote sensing images to estimate winter wheat yield. Firstly, in 2009 entire growing season two districts Tongzhou Shunyi Beijing divided into 54 stages at five-day intervals....
Imprecise probabilities have gained increasing popularity for quantitatively modeling uncertainty under incomplete information in various fields. However, it is still a computationally challenging task to propagate imprecise because double-loop procedure usually involved. In this contribution, fully decoupled method, termed as active learning–augmented probabilistic integration (ALAPI), developed efficiently estimate the failure probability function (FPF) presence of probabilities....
The concept of Bayesian active learning has recently been introduced from machine to structural reliability analysis. Although several specific methods have successfully developed, significant efforts are still needed fully exploit their potential and address existing challenges. This work proposes a quasi-Bayesian method, called 'Quasi-Bayesian Active Learning Cubature', for analysis with extremely small failure probabilities. method is established based on cleaver use the probability...
The effect of nanoparticle size (4~44 nm) on the thermal conductivities heat transfer oils has been systematically examined using iron oxide nanoparticles. Such Fe(3)O(4) nanoparticles were synthesized by a simple one-pot pyrolysis method. (16~44 nm), shape and assembly patterns monodisperse modulated only controlling amount Fe(acac)(3). After as-prepared NPs dispersed in oils, prepared magnetic nanofluids exhibit higher conductivity than enhanced values increase with decrease particle size....
Estimating the functional relation between probabilistic response of a computational model and distribution parameters inputs is especially useful for 1) assessing contribution to uncertainty output (parametric global sensitivity analysis), 2) identifying optimized efficiently cheaply reduce optimization). In this paper, extended Monte Carlo simulation method developed purpose, which provides four benefits parametric analysis optimization problems. First, able provide an unbiased or...
Accurate and dynamic monitoring of crop nitrogen status is the basis scientific decisions regarding fertilization. In this study, we compared analyzed three types spectral variables: Sensitive bands, position features, typical hyperspectral vegetation indices. First, Savitzky-Golay technique was used to smooth original spectrum, following which parameters describing characteristics were extracted. Next, successive projections algorithm (SPA) adopted screen out sensitive variable set from...