Neural Networks | Journal | ScienceDirect.com by Elsevier
Neural Networks provides a forum for developing and nurturing an international community of scholars and practitioners who are interested in all aspects of neural networks, including deep learning and related approaches to artificial intelligence and machine learning. Neural Networks welcomes submissions that contribute to the full range of neural networks research, from cognitive modeling and com
リリース、障害情報などのサービスのお知らせ
最新の人気エントリーの配信
j次のブックマーク
k前のブックマーク
lあとで読む
eコメント一覧を開く
oページを開く
Local estimation of failure probability function by weighted approach
Kriging-based adaptive Importance Sampling algorithms for rare event estimation
On the assessment of marginal life saving costs for risk acceptance criteria
A new adaptive response surface method for reliability analysis
Stochastic reduced order models for random vectors: Application to random eigenvalue problems
A novel probabilistic method for robust parametric identification and outlier detection
The variability of deformation demand with ground motion intensity
Generation of response-spectrum-compatible artificial earthquake accelerograms with random joint time–frequency distributions
Modelling and simulation of spatially varying earthquake ground motions at sites with varying conditions
Statistical moving load identification including uncertainty
An improved approximation for the spectral representation method in the simulation of spatially varying ground motions
Use of Engineering Seismology Tools in Ground Shaking Scenarios
Uncertainty about the uncertainty in seismic hazard analysis
Regional and local seismic hazard assessment
Development of probabilistic seismic hazard analysis for international sites, challenges and guidelines
Deterministic versus probabilistic seismic hazard analysis for critical structures
How to combine deterministic and probabilistic methods for assessing earthquake hazards
A deterministic–probabilistic approach for seismic hazard assessment
Benefits of scenario ground motion maps