Results 131 to 140 of about 1,444,667 (352)

A Multivariate Mixed‐Effects Regression Framework for Ground Motion Modeling: Integrating Parametric and Machine Learning Approaches

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Multivariate ground motion models (GMMs) that capture the correlation between different intensity measures (IMs) are essential for seismic risk assessment. Conventional GMMs are often developed using a two‐stage approach, where separate univariate models with predefined functional forms are fitted first, and correlation is addressed in a ...
Sayed Mohammad Sajad Hussaini, Shaghayegh Karimzadeh, Paulo B. Lourenço   +2 more
wiley   +1 more source

Research on the Laws of Destructive Patterns and Control Measures of Overlying Rock in High‐Efficiency Large‐Scale Mining Faces

Energy Science &Engineering, EarlyView.
With the advancement of coal mining technology driving the development of working faces toward increased mining heights and extended lengths, the enlargement of face dimensions has led to expanded overlying strata failure zones and intensified ground pressure manifestations. Consequently, traditional methods for determining hydraulic support resistance
Chen Gong, Peilin Gong, Kang Yi, Kaijie Duan, Lizhu Liu, Peng Li   +5 more
wiley   +1 more source

Towards risk-targeted seismic hazard models for Europe. [PDF]

Sci Rep, 2023
Monti G, Demartino C, Gardoni P.
europepmc   +1 more source

Seismic Hazard Assessment For Peninsular Malaysia Using Gumbel Distribution Method [PDF]

, 2005
This Paper Presents The Preliminary Study On Seismic Hazard Assessment Which Involved Developing Macrozonation Map For Two Hazard Levels, I.E. 10% And 2% Probabilities Of Exceedance In 50 Years For Bedrock Of Peninsular Malaysia.
Adnan, Azlan, Hendriyawan, Hendriyawan, Irsyam, Masyhur, Marto, Aminaton   +3 more
core  

Statistical modeling of ground motion relations for seismic hazard analysis

, 2013
We introduce a new approach for ground motion relations (GMR) in the probabilistic seismic hazard analysis (PSHA), being influenced by the extreme value theory of mathematical statistics. Therein, we understand a GMR as a random function.
B Efron, BV Gnedenko, CA Cornell, CB Crouse, CM Montgomery, D Enescu, D Giardini, D Stromeyer, DA Rhoades, DD Mari, DJ Dupuis, E Kalkan, F Scherbaum, FO Strasser, FO Strasser, GL Molas, GM Atkinson, GM Atkinson, GM Atkinson, J Beirlant, J Douglas, J Douglas, J Hüsler, JC Stepp, JG Anderson, JJ Bommer, JJ Bommer, JJ Bommer, K Beyer, K Campbell, K Sadigh, KW Campbell, L Al Atik, L Haan de, L Huyse, L Landry, LF Restrepo-Velez, M Falk, M Massa, M Raschke, M Raschke, M Raschke, M Raschke, M Sørensen, Mathias Raschke, MH Quenouille, MR Leadbetter, N Abrahamson, N Abrahamson, N Morikawa, NA Abrahamson, NA Abrahamson, NN Ambraseys, NN Ambraseys, NN Ambraseys, NN Ambraseys, P Billingsley, P Cosentino, P Spudich, PJ Stafford, PS Lin, RA Fisher, RK McGuire, RK McGuire, RL Smith, RR Youngs, S Castellaro, S Coles, T Chang, T Utsu, WB Joyner, WB Joyner, Y-H Chen, Z Kabluchko   +73 more
core   +1 more source

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Clustering Analysis of Seismicity in the Anatolian Region with Implications for Seismic Hazard. [PDF]

Entropy (Basel), 2023
Zaccagnino D, Telesca L, Tan O, Doglioni C.   +3 more
europepmc   +1 more source

Transposing an active fault database into a seismic hazard fault model for nuclear facilities – Part 1: Building a database of potentially active faults (BDFA) for metropolitan France

, 2017
. The French Institute for Radiation Protection and Nuclear Safety (IRSN), with the support of the Ministry of Environment, compiled a database (BDFA) to define and characterize known potentially active faults of metropolitan France.
H. Jomard, E. Cushing, L. Palumbo, S. Baize, C. David, T. Chartier   +5 more
semanticscholar   +1 more source

Smart Solar Power Site Selection Through a Hybrid Computational Framework of Neuro‐Fuzzy With Genetic Algorithm Optimization

Energy Science &Engineering, EarlyView.
Solar Power plants at various locations a: Pavagada SPP, Karnataka b: Bhadla SPP, Rajasthan c: West Bengal Solar Park ABSTRACT This paper presents a new neuro‐fuzzy multi‐criteria decision‐making (MCDM) framework designed to optimize the selection of solar power plant (SPP) sites across India.
Rajkumari Malemnganbi Devi, Benjamin A. Shimray, Ingudam Chitrasen Meitei, Khelchandra Thongam, Shuma Adhikari, Anuradha Laishram, Subir Datta, Ahmed Al Mansur, Taha Selim Ustun   +8 more
wiley   +1 more source

Stormwater Infrastructure Resilience Assessment against Seismic Hazard Using Bayesian Belief Network. [PDF]

Int J Environ Res Public Health, 2023
Garshasbi M, Kabir G, Dutta S.
europepmc   +1 more source