Results 61 to 70 of about 6,285,273 (279)

Standardized mean square error (MSE) and standardized bias for corrected (Corr.) and uncorrected (Unc.) variance estimates from the bias-correction simulations.

, 2015
Standardized mean square error (MSE) and standardized bias for corrected (Corr.) and uncorrected (Unc.) variance estimates from the bias-correction simulations.
Patrick J. Monnahan (735483), John K. Kelly (117806)   +1 more
core   +1 more source

High‐Throughput Screening and Interpretable Machine Learning for Rational Design of Bimetallic Catalysts for Methane Activation

Advanced Science, EarlyView.
ABSTRACT Methane's efficient catalytic removal is vital for sustainable development. Bimetallic catalysts, though promising for methane activation, pose a design challenge due to their complex compositional space. This work introduces an integrated framework that combines high‐throughput density functional theory (DFT) and interpretable machine ...
Mingzhang Pan, Tian Zhang, Jiawei Dong, Yubao Xie, Kaifeng Zhong, Wei Guan, Haiqiao Wei, Changcheng Fu, Yaqiong Su   +8 more
wiley   +1 more source

PENGGUNAAN MEAN SQUARE ERROR (MSE) DALAM MENENTUKAN PENDUGA RASIO YANG EFISIEN PADA SAMPLING ACAK BERSTRATA [PDF]

, 2010
Penelitian ini akan membahas tentang penduga rasio yang effisien pada sampling acak berstrata. Dari beberapa penduga rasio pada sampling acak berstrata, penulis mengambil tiga penduga rasio yaitu penduga rasio gabungan, penduga rasio yang diajukan oleh ...
Yetti Murni
core  

Machine Learning‐Assisted KCl‐CaCl2‐LiCl Electrolyte Design for Low‐Temperature, High‐Performance Calcium‐Based Liquid Metal Batteries

Advanced Science, EarlyView.
A machine learning‐assisted framework optimizes the KCl‐CaCl2‐LiCl ternary electrolyte. The optimized 13:35:52 mol% composition enables Ca‐based liquid metal batteries to operate stably at 480 °C, with >99.5% coulombic efficiency, ultralow self‐discharge, and excellent cycling stability, advancing low‐temperature large‐scale energy storage.
Xinglin Zhou, Lei Huang, Yan Zhou, Xiaohui Ning   +3 more
wiley   +1 more source

Determination the smoothing constant that minimizes mean absolute error and mean square deviation

, 2021
Exponential smoothing technique has become one of the quantitative techniques are very important in forecasting. The accuracy of forecasting based on this method depends on a parameter called the smoothing constant.
Mukarromah, Z., Susilo, I.G., Pratama, D.A., Bon, A.T., Prabowo, A., Mamat, M., Sukono, ., Tripena, A.   +7 more
core   +1 more source

Worst-case mean square error (MSE) transceiver design for imperfect estimate multi-input-multi-output communication channels

IET Communications, 2012
The authors consider the worst-case transceiver design problem under spectrum bounded channel uncertainty matrices. Their design aims to minimise the trace and the determinant of the estimate error covariance matrix, respectively. The authors relax the formulated problem into an optimisation problem with bilinear matrix inequality constraints (i.e. BMI
openaire   +2 more sources

Learning Moisture‐Induced Damage From Vision: Diffusion Models for Real‐Time Monitoring of Additive Manufacturing Processes

Advanced Science, EarlyView.
We introduce a vision‐based real‐time monitoring system for additive manufacturing that detects subtle moisture‐induced degradation via a diffusion model‐based framework. The approach enables nondestructive assessment of moisture‐induced damage level and mechanical performance and establishes a practical route toward more intelligent, reliable, and ...
Jiyoung Jung, Yuna Yoo, Dharneedar Ravichandran, Dahyun Daniel Lim, Grace X. Gu   +4 more
wiley   +1 more source

EndoTac: An Endoscopic Camera‐Based Tactile Sensor with High Sensitivity for Minimally Invasive Surgery

Advanced Science, EarlyView.
EndoTac presents a trocar‐compatible endoscopic vision‐based tactile sensor that uses a convex mirror to enlarge side‐facing tactile coverage during minimally invasive vessel palpation. Distorted tactile images are unwarped and processed by a learning model to estimate vascular deformation, enabling sensitive, spatially distributed tactile perception ...
Yupeng Wang, Nicolas Raison, Xuyang Zhang, Aijia Yang, Lukas Lindenroth, Shan Luo   +5 more
wiley   +1 more source

Proving the Efficiency of Alternative Linear Regression Model Based on Mean Square Error (MSE) and Average Width using Aquaculture Data

International Journal of Recent Technology and Engineering, 2019
Multiple linear regressions (MLR) model is an important tool for investigating relationships between several response variables and some predictor variables. This method is very powerful and commonly used in finance, economic, medical, agriculture and many more.
openaire   +1 more source

The steady-state mean-square error analysis for least mean p-order algorithm

, 2009
Based on series expansion, the steady-state mean-square error (MSE) analysis for real and complex least mean p-order (LMP) algorithm is developed, and some closed-form analytical expressions for the steady-state MSE and the corresponding restrictive ...
Wang, X, He, R, Lin, B, Wang, B
core   +1 more source