Results 211 to 220 of about 5,204,898 (289)

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

Euclidean consistency-driven dual-layer information fusion framework for UAV-based traffic accident scene reconstruction. [PDF]

PLoS One
Xie Z, Xia W, He C, Qiu T.
europepmc   +1 more source

Machine Learning-Based Prediction of Textural Properties and Nonlinear Regulatory Pattern Analysis of 3D-Printed Dough Containing Konjac Glucomannan. [PDF]

Foods
Leng W, Sun Y, Xie J, Pang J.
europepmc   +1 more source

Nonlinear association of the non-high-density lipoprotein cholesterol-to-high-density lipoprotein cholesterol ratio with cognitive function in older Chinese adults: A prospective cohort study. [PDF]

J Int Med Res
Cong X, Yang S, Chen Y, Bi Y.
europepmc   +1 more source

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Quadratic programming for nonlinear regression

Communications of the ACM, 1972
A quadratic programming algorithm is described for use with the magnified diagonal method of nonlinear regression with linear constraints. The regression method is published in JACM, July 1970.
Richard I Shrager
exaly   +3 more sources

Linear and Nonlinear Regression-Based Maximum Correntropy Extended Kalman Filtering

IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021
The extended Kalman filter (EKF) is a method extensively applied in many areas, particularly, in nonlinear target tracking. The optimization criterion commonly used in EKF is the celebrated minimum mean square error (MMSE) criterion, which exhibits ...
Xi Liu, Zhigang Ren, Hongqiang Lyu, Zhihong Jiang, Pengju Ren, Badong Chen   +5 more
semanticscholar   +1 more source

Near-optimal Nonlinear Regression Trees

Operations Research Letters, 2021
We propose Near-optimal Nonlinear Regression Trees with hyperplane splits (NNRTs) that use a polynomial prediction function in the leaf nodes, which we solve by stochastic gradient methods.
D. Bertsimas, Jack Dunn, Yuchen Wang
semanticscholar   +1 more source

Nonlinear Regression

Handbook of Regression Analysis With Applications in R, 2012
M. Fortin
openaire   +2 more sources