Results 271 to 280 of about 1,171,833 (351)

Ensemble Deep Learning–Based Wind Power Forecasting With Self‐Adaptive Osprey Optimization Algorithm

Energy Science &Engineering, EarlyView.
Design of Self‐Adaptive Osprey (SAO) algorithm: The novel SAO algorithm is designed by integrating the exploration capability of the conventional Osprey algorithm by including the self‐adaptiveness for enhancing the convergence rate. Ensemble Deep Learning for wind power forecasting: The wind forecasting is employed using the proposed Ensemble learning
Johncy Bai Johnson, Sivarani Thankamony Saradha Devi, Kumar Chandrasekaran, Sourav Barua   +3 more
wiley   +1 more source

Analyzing the impact of clay minerals on the reservoir quality of the Lower Goru Formation using Unsupervised Machine Learning. [PDF]

PLoS One
Noreen K, Azeem T, Rehman F, Amin Y, Ahmad QA, Hussain M.   +5 more
europepmc   +1 more source

Investigating the Correlation Between Marketing Emails and Receivers Using Unsupervised Machine Learning on Limited Data : A comprehensive study using state of the art methods for text clustering and natural language processing

, 2016
Christoffer Pettersson
openalex   +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

Reflective Pathways: Integrating Empathy Into the STEM Student Experiences

Future in Educational Research, EarlyView.
ABSTRACT The growing demand for a globally competent STEM workforce showcases the importance of embedding empathy into undergraduate education. As a core dimension of global competence, empathy enables individuals to engage diverse perspectives and navigate collaborative challenges.
Aparajita Jaiswal, Nathan S. Bitner, Gaurav Nanda, Muna Sapkota   +3 more
wiley   +1 more source

Defining Clinically Meaningful Subgroups in Patients Undergoing Arthroscopic Rotator Cuff Repair Using Unsupervised Machine Learning. [PDF]

Orthop J Sports Med
Lu Y, Berlinberg EJ, Alder K, Chervonski E, Patel HH, Rice M, Yanke AB, Cole BJ, Verma NN, Hevesi M, Forsythe B.   +10 more
europepmc   +1 more source

Machine Learning Approaches for GC–MS Data Interpretation in Flavour and Fragrance Analysis

Flavour and Fragrance Journal, EarlyView.
The review explores machine learning integration in GC‐MS data analysis for the fragrance and flavour industry, highlighting recent advances and techniques in a context constrained by data scarcity and intellectual property concerns. ABSTRACT This review explores the integration of machine learning (ML) in the analysis of mass spectrometry data ...
Jean‐Baptiste Coffin, Romain Krafft, Sylvain Antoniotti, Sébastien Fiorucci   +3 more
wiley   +1 more source

Using country-level variables to discover country clusters beyond traditional health policy and performance metrics: An unsupervised machine learning approach for HIV healthcare delivery and financing. [PDF]

PLOS Glob Public Health
Alexiou ZW, Dixit S, Ogbuoji O, Kohler S, Atun R, Terris-Prestholt F, Semini I, Bulstra CA, Bärnighausen T.   +8 more
europepmc   +1 more source

Multifactorial Screening for Fine‐Scale Selection of CCS Industrial Clusters and Hubs in Brazil

Greenhouse Gases: Science and Technology, EarlyView.
ABSTRACT As Brazil moves toward implementing its decarbonization commitments, carbon capture and storage (CCS) hubs are emerging as a key pathway for large‐scale CO2 abatement in hard‐to‐abate sectors. This paper presents a multifactorial, data‐driven framework to screen and prioritize potential CCS industrial clusters and hubs across Brazilian regions,
Gustavo P. Oliveira, Beatriz R. Almeida, Thiago R. C. Justino, Carlos A. S. Santos, Alex A. Santos, Fabiana Philipi   +5 more
wiley   +1 more source

Calculating a Phase Diagram of a Simple Water Model Using Unsupervised Machine Learning on Simulation Data. [PDF]

J Chem Theory Comput
Ogrin P, Urbic T.
europepmc   +1 more source