Results 101 to 110 of about 9,585 (266)

Kinetic Contribution to the Arbitrary Order Odd Frequency Moments of the Dynamic Structure Factor

Contributions to Plasma Physics, EarlyView.
ABSTRACT An exact expression is derived for the kinetic contribution to the odd (arbitrary order) frequency moments of the dynamic structure factor via a finite summation that features averages of even (all lower orders) powers of the momentum over the exact momentum distribution.
Panagiotis Tolias, Tobias Dornheim, Jan Vorberger   +2 more
wiley   +1 more source

Logarithmic Kernel Relaxed Collaborative Representation With Scaled MST Dictionary Construction for Hyperspectral Anomaly Detection

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Representation-based anomaly detection methods are one of the most popular methods in hyperspectral anomaly detection. Nevertheless, linear models of have difficulties in adequately describing complex data and generating a decision boundary for anomaly ...
Yang Zhao, Hongjun Su, Zhaoyue Wu, Zhaohui Xue, Qian Du   +4 more
doaj   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

An analysis of two dimensional integral equations of the second kind

Le Matematiche, 2007
In this article, a numerical method is used to solve the two dimensionalFredholm integral equation of the second kind with weak singular kernel using the Toeplitz matrix and product Nystrom method.
M. M. El-Borai, M. A. Abdou, M. Basseem
doaj  

On a generalized logarithmic kernel and its potentials [PDF]

Annales Polonici Mathematici, 1981
Anandam, Victor, Brelot, Marcel
openaire   +2 more sources

Covariance Structure Modeling of Engineering Demand Parameters in Cloud‐Based Seismic Analysis

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Probabilistic seismic demand modeling aims to estimate structural demand as a function of ground motion intensity—a critical stage in seismic risk assessment. Although many models exist to describe the structural demand, few consider the covariance among engineering demand parameters, potentially overlooking a key factor in improving the ...
Archie Rudman, Enrico Tubaldi, Roberto Gentile, John Douglas   +3 more
wiley   +1 more source

The Impact of Resource Endowment and Digital Transformation on the Efficiency of Energy Transition

Energy Science &Engineering, EarlyView.
Resource endowment has a significant positive direct effect and a stronger spatial spillover effect on ETE, while digital transformation can improve local efficiency but has some negative spillover effects on neighboring regions. ABSTRACT In contemporary society, improving energy transition efficiency (ETE) has become a necessary measure to ensure the ...
Junding Yang, Yanfeng Guan, Rong Wang, Tong Zhao, Guilan Huang, Ming Ding   +5 more
wiley   +1 more source

Shielding properties of a conducting bar calculated with a boundary integral method [PDF]

Advances in Radio Science, 2005
A plane rectangular bar of conducting and permeable material is placed in an external low-frequency magnetic field. The shielding properties of this object are investigated by solving the given plane eddy current problem for the vector potential with the
L. O. Fichte, S. Lange, Th. Steinmetz, M. Clemens   +3 more
doaj  

A Comparison of Realized Measures of Integrated Volatility: Price Duration‐ vs. Return‐Based Approaches

Journal of Forecasting, EarlyView.
ABSTRACT We study the accuracy of a variety of parametric price duration‐based realized variance estimators constructed via various financial duration models and compare their forecasting performance with the performance of various nonparametric return‐based realized variance estimators.
Björn Schulte‐Tillmann, Mawuli Segnon, Timo Wiedemann   +2 more
wiley   +1 more source

Machine Learning Approaches to Forecast the Realized Volatility of Crude Oil Prices

Journal of Forecasting, EarlyView.
ABSTRACT This paper presents an evaluation of the accuracy of machine learning (ML) techniques in forecasting the realized volatility of West Texas Intermediate (WTI) crude oil prices. We compare several ML algorithms, including regularization, regression trees, random forests, and neural networks, to several heterogeneous autoregressive (HAR) models ...
Talha Omer, Kristofer Månsson, Pär Sjölander, Gazi Salah Uddin   +3 more
wiley   +1 more source