Results 221 to 230 of about 4,452 (291)

How to improve statistical power in a trial with SCA2 patients using natural history data. [PDF]

Trials
Tran M, Poulet PE, Petit E, Durr A, Klockgether T, Ashizawa T, Coarelli G, du Montcel ST.   +7 more
europepmc   +1 more source

Surface Consistent Seismic Hazard Assessment in the Shillong Plateau, Northeast India: A Probabilistic Approach Using Multiple Source Models and a Logic Tree Framework

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT We perform probabilistic seismic hazard analysis (PSHA) in the Shillong Plateau by clubbing the up‐to‐date earthquake data and seismotectonic properties of the study area. Twenty‐one areal seismic sources are delineated based on the updated earthquake catalog, tectonic, and fault plane solutions.
Mohd Shahabuddin, William Kumar Mohanty, Eleftheria Papadimitriou   +2 more
wiley   +1 more source

Assessment of Lasso and Ridge models for soil swelling potential prediction. [PDF]

Sci Rep
Bility MT, Vora T, Lakhani PN, Bhogayata AC, Bhagat SK.   +4 more
europepmc   +1 more source

A Review of Overcurrent Protection in Smart Grids Under Cyber‐Physical Threats With a Cyber‐Physical Evaluation Framework

Energy Science &Engineering, EarlyView.
By manipulating current and voltage measurements, an assailant can induce unwanted relay action while attempting to avoid detection. Detecting advanced cyber intrusions in power protection environments requires specialised data analysis and anomaly detection methods.
Feras Alasali, Anas AlMajali, Naser Naily, Hassen Loukil, Salah AbuGhalyon, William Holderbaum, Abdelaziz Salah Saidi   +6 more
wiley   +1 more source

Acoustic impedance inversion via voting stacked regression (VStaR) algorithms. [PDF]

Sci Rep
Surachman LM, Kaka SI, Al-Shuhail A.
europepmc   +1 more source

Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning

Energy Science &Engineering, EarlyView.
The transport sector accounts for approximately one‐quarter of Iran's final energy consumption. The energy demand in this sector has the least variation, with petroleum products accounting for more than 85% of the demand. Furthermore, the accelerated growth of energy consumption and the sector's reliance on fossil fuels, which are the main cause of ...
Amir Hossein Akbari, Seyyed Mohammad Hashemi, Meisam Farajollahi   +2 more
wiley   +1 more source

High-resolution photovoltaic power forecasting using machine learning models under seasonal and stress conditions. [PDF]

Sci Rep
Mansour HSE, Mohamed AS, Farh HMH, Ibrahim AW, Al-Shaalan AM, Kunya AB, Elnashar HS.   +6 more
europepmc   +1 more source

Daily Residential Natural Gas Demand Forecasting Using Machine Learning Regression: Comparative Evaluation With a Case Study in Qazvin Province, Iran

Energy Science &Engineering, EarlyView.
This graphical abstract summarizes the proposed framework for improving short‐term residential natural gas consumption forecasting by integrating a novel socioeconomic indicator, the subscription growth ratio (SGR), with conventional meteorological variables.
Ali Pirzad, Mostafa Khanzadi
wiley   +1 more source

Some simulations of age-period-cohort analysis applying Bayesian regularization: Conditions for using random walk model. [PDF]

PLoS One
Matsumoto Y.
europepmc   +1 more source

Tree‐Boost–Guided CNN–BiLSTM–Transformer for Solar Irradiance Forecasting: Cross‐Regional Evidence for Sustainable Energy Planning

Energy Science &Engineering, EarlyView.
This graphical abstract illustrates a reproducible pipeline that combines gradient‐boosting‐based feature selection with a CNN–BiLSTM–Transformer model to forecast solar irradiance across multi‐site satellite and ground datasets, delivering robust, high‐accuracy predictions that support sustainable grid planning and reliable PV integration.
Muhammad Farhan Hanif, Usama Hassan, Javid Hussain, Irfan Ali Khan, Yuldasheva Gulora, Syed Masood Arif Bukhari   +5 more
wiley   +1 more source