Results 11 to 20 of about 6,285,273 (279)

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   +1 more source

Proportionate Minimum Error Entropy Algorithm for Sparse System Identification

Entropy, 2015
Sparse system identification has received a great deal of attention due to its broad applicability. The proportionate normalized least mean square (PNLMS) algorithm, as a popular tool, achieves excellent performance for sparse system identification.
Zongze Wu, Siyuan Peng, Badong Chen, Haiquan Zhao, Jose C. Principe   +4 more
doaj   +1 more source

Performance Analysis of Interferometer Algorithm under Phase Measurement Error

Applied Sciences, 2021
Direction finding has been extensively studied over the past decades and a number of algorithms have been developed. In direction finding, theoretic performance prediction is a fundamental problem.
Chan-Bin Ko, Joon-Ho Lee
doaj   +1 more source

Mean metrics values—Mean squared error (MSE), mean absolute error (MAE) and coefficient of determination (R²) for individual models sorted by validation MSE.

, 2023
Mean metrics values—Mean squared error (MSE), mean absolute error (MAE) and coefficient of determination (R2) for individual models sorted by validation MSE.
Tomasz Gutowski (17200042), Stanisław Szlufik (4804167), Ryszard Antkiewicz (17200045)   +2 more
core   +1 more source

Stochastic analysis of an error power ratio scheme applied to the affine combination of two LMS adaptive filters [PDF]

, 2011
The affine combination of two adaptive filters that simultaneously adapt on the same inputs has been actively investigated. In these structures, the filter outputs are linearly combined to yield a performance that is better than that of either filter ...
Jean-Yves Tourneret, Bermudez, José Carlos Moreira, Tourneret, Jean-Yves, José Carlos M. Bermudez, Bershad, Neil J., Neil J. Bershad   +5 more
core   +1 more source

Nonlinear Equalization for Optical Communications Based on Entropy-Regularized Mean Square Error [PDF]

, 2022
An entropy-regularized mean square error (MSE-X) cost function is proposed for nonlinear equalization of short-reach optical channels. For a coherent optical transmission experiment, MSE-X achieves the same bit error rate as the standard MSE cost ...
Diedolo, Francesca, Schädler, Maximilian, Calabró, Stefano, Böcherer, Georg   +3 more
core  

Mean metrics values—Mean squared error (MSE), mean absolute error (MAE) and coefficient of determination (R²) for impulse models sorted by MSE in validation set.

, 2023
Mean metrics values—Mean squared error (MSE), mean absolute error (MAE) and coefficient of determination (R2) for impulse models sorted by MSE in validation set.
Tomasz Gutowski (17200042), Stanisław Szlufik (4804167), Ryszard Antkiewicz (17200045)   +2 more
core   +1 more source

Correlation Analysis of Factors Affecting Firm Performance and Employees Wellbeing: Application of Advanced Machine Learning Analysis

Algorithms, 2022
Given the importance of identifying key performance points in organizations, this research intends to determine the most critical intra- and extra-organizational elements in assessing the performance of firms using the European Company Survey (ECS) 2019 ...
Jozsef Pap, Csaba Mako, Miklos Illessy, Zef Dedaj, Sina Ardabili, Bernat Torok, Amir Mosavi   +6 more
doaj   +1 more source

Storage Time prediction of Frozen Meat using Artificial Neural Network modeling with Color values

Revista Científica, 2023
Among the various methods available to determine the storage time of frozen meat, including analyses based on physical and chemical properties, sensory analysis, particularly color changes, is an important aspect of meat acceptability for consumers.
Saliha Lakehal, Brahim Lakehal
doaj   +1 more source

Forecast Error Calculation with Mean Squared Error (MSE) and Mean Absolute Percentage Error (MAPE)

JINAV: Journal of Information and Visualization, 2020
Calculation errors in forecasting a data are very important from a forecasting process. The high level of forecasting accuracy will affect the level of confidence in forecasting decision making.
openaire   +1 more source