Results 131 to 140 of about 1,354,279 (305)

Optimum thresholding using mean and conditional mean squared error [PDF]

Journal of Econometrics, 2017
J. E. Figueroa-L'opez, C. Mancini
semanticscholar   +1 more source

Model identification of Solid Oxide Fuel Cell using hybrid Elman Neural Network/Quantum Pathfinder algorithm

Energy Reports, 2021
In this research, a new efficient method is introduced for model assessment of Solid Oxide Fuel Cell (SOFC) model using a new hybrid Elman Neural Network (ENN).
Hailong Jia, Bahman Taheri
doaj  

Minimum mean‐square error speech enhancement using hidden Markov models [PDF]

, 1989
Y. Ephraim
openalex   +1 more source

Data‐driven forecasting of ship motions in waves using machine learning and dynamic mode decomposition

International Journal of Adaptive Control and Signal Processing, EarlyView.
Summary Data‐driven forecasting of ship motions in waves is investigated through feedforward and recurrent neural networks as well as dynamic mode decomposition. The goal is to predict future ship motion variables based on past data collected on the field, using equation‐free approaches.
Matteo Diez, Mauro Gaggero, Andrea Serani   +2 more
wiley   +1 more source

A Comparative Analysis of Machine Learning and Deep Learning Techniques for Accurate Market Price Forecasting

Analytics
This study compares three machine learning and deep learning models—Support Vector Regression (SVR), Recurrent Neural Networks (RNN), and Long Short-Term Memory (LSTM)—for predicting market prices using the NGX All-Share Index dataset.
Olamilekan Shobayo, Sidikat Adeyemi-Longe, Olusogo Popoola, Obinna Okoyeigbo   +3 more
doaj   +1 more source

Retrotransposon Expression Is Upregulated in Adulthood and Suppressed during Regeneration of the Limb in the Axolotl (Ambystoma mexicanum)

Advanced Biology, EarlyView.
The axolotl's remarkable regenerative abilities decline with age, the causes may include the numerous repetitive elements within its genome. This study uncovers how Ty3 retrotransposons and coexpression networks involving muscle and immune pathways respond to aging and regeneration, suggesting that transposons respond to physiological shifts and may ...
Samuel Ruiz‐Pérez, Nicolás Alcaraz, Karla Torres‐Arciga, José Antonio Ocampo‐Cervantes, Alejandra Cervera, Clementina Castro‐Hernández, Cynthia Gabriela Sámano‐Salazar, Ernesto Soto‐Reyes, Rodrigo González‐Barrios   +8 more
wiley   +1 more source

From Damage to Functionality: Remanufacturing of Thrust Roller Bearings by Tailored Forming

Advanced Engineering Materials, EarlyView.
Herein, the wear and fatigue behavior of repaired bearing raceways with a new powder alloy is investigated using a FE8 test‐rig and an oscillating tribometer. The tests are compared with industrial manufactured bearings to evaluate the repair quality. The repair can extend the service life of the repaired bearing to that of a new bearing and improves ...
Felix Saure, Florian Pape, Gerhard Poll, Max Marian   +3 more
wiley   +1 more source

Hybrid deep learning CNN-LSTM model for forecasting direct normal irradiance: a study on solar potential in Ghardaia, Algeria

Scientific Reports
This paper provides an in-depth analysis and performance evaluation of four Solar Radiance (SR) prediction models. The prediction is ensured for a period ranging from a few hours to several days of the year.
Boumediene Ladjal, Mohamed Nadour, Mohcene Bechouat, Nadji Hadroug, Moussa Sedraoui, Abdelaziz Rabehi, Mawloud Guermoui, Takele Ferede Agajie   +7 more
doaj   +1 more source

PERFORMANCE ANALYSIS OF GRADIENT BOOSTING MODELS VARIANTS IN PREDICTING THE DIRECTION OF STOCK CLOSING PRICES ON THE INDONESIA STOCK EXCHANGE

Barekeng
Accurately predicting stock market trends remains a significant challenge for investors due to its dynamic nature. This study explores the performance of Gradient Boosting models, including XGBoost, XGBoost Random Forest, CatBoost, and Gradient Boosting ...
Delvian Christoper Kho, Hindriyanto Dwi Purnomo, Hendry Hendry   +2 more
doaj   +1 more source

Lower bound on the mean-squared error in oversampled quantization of periodic signals using vector quantization analysis [PDF]

, 1996
N.T. Thao, Martin Vetterli
openalex   +1 more source