Results 31 to 40 of about 1,840,782 (294)

Gravitational Co-evolution and Opposition-based Optimization Algorithm [PDF]

International Journal of Computational Intelligence Systems, 2013
In this paper, a Gravitational Co-evolution and Opposition-based Optimization (GCOO) algorithm is proposed for solving unconstrained optimization problems.
Yang Lou, Junli Li, Yuhui Shi, Linpeng Jin   +3 more
doaj   +1 more source

LARGE SCALE UNCONSTRAINED OPTIMIZATION

, 2009
This work is a survey on the methods for large scale unconstrained optimization. Besides its own theoretical importance, the growing interest in the last years in solving problems with a larger and larger number of variables are arising very frequently ...
ROMA, Massimo
core   +1 more source

A Novel Self-Adaptive Trust Region Algorithm for Unconstrained Optimization

Journal of Applied Mathematics, 2014
A new self-adaptive rule of trust region radius is introduced, which is given by a piecewise function on the ratio between the actual and predicted reductions of the objective function.
Yunlong Lu, Wenyu Li, Mingyuan Cao, Yueting Yang   +3 more
doaj   +1 more source

The Diagonal Update for Unconstrained Optimization [PDF]

مجلة التربية والعلم, 2012
In this research we introduced a new update of the Hessian matrix or we updating only the diagonal elements of Hessian matrix, and make the non-diagonal elements always equal to zero and in this case we can preserve the sparse property so called the ...
Saad Shakir Mahmood, Ali Ibrahim Mansour, Haydir Ali Hassan   +2 more
doaj   +1 more source

Deep Learning Pose Estimation for Phenotyping of Co‐Occurring Hyperkinetic Movement Disorders

Annals of Clinical and Translational Neurology, EarlyView.
ABSTRACT Objective To explore whether routine outpatient video combined with deep learning‐based pose estimation and clinically interpretable kinematic features can support multi‐label phenotyping of co‐occurring hyperkinetic movement disorders (HMDs).
Laura Cif, Diane Demailly, Gabriella A. Horvàth, Juan Dario Ortigoza Escobar, Nathalie Dorison, Mayté Castro Jiménez, Cécile A. Hubsch, Thomas Wirth, Gun‐Marie Hariz, Sophie Huby, Morgan Dornadic, Zohra Souei, Muhammad Mushhood Ur Rehman, Simone Hemm, Mehdi Boulaymen, Eduardo M. Moraud, Jocelyne Bloch, Xavier Vasques   +17 more
wiley   +1 more source

A THREE-TERM CONJUGATE GRADIENT METHOD FOR LARGE-SCALE MINIMIZATION IN ARTIFICIAL NEURAL NETWORKS

Barekeng
Conjugate Gradient (CG) methods are widely used for solving unconstrained optimization problems due to their efficiency and low memory requirements. However, standard CG methods may not always guarantee sufficient descent condition, which can impact ...
Umar A Omesa, Muhammad Y. Waziri, Issam A. R. Moghrabi, Sulaiman M. Ibrahim, Gudu E B, Fakai S L, Rabiu Bashir Yunus, Elissa Nadia Madi   +7 more
doaj   +1 more source

DigiChrom: A Domain Ontology for Semantic Representation of Trivalent Chromium Platings and Its Large Language Model‐Based Alignment With Multiple Mid‐Level Ontologies

Advanced Engineering Materials, EarlyView.
Digitalizing electroplating requires both domain knowledge and interoperability. This work introduces PlatOn, a domain ontology for trivalent chromium plating and coating characterization, and a hybrid pipeline that aligns it to a mid‐level reference ontology by combining eight similarity metrics with language model reasoning. Expert‐validated mappings
Janik Harter, Elena Garcia Trelles, Christoph Schweizer, Thomas Seifert, Christoph Baumer, Mahmoud Elkady, Katja Feige, Daniel Grimme, Edgar Hoffmann, Andreas Waibel, Anke Walter   +10 more
wiley   +1 more source

Speedup of high-order unconstrained binary optimization using quantum $${{\mathbb{Z}}}_{2}$$ Z 2 lattice gauge theory

Communications Physics
An important and difficult problem in optimization is the high-order unconstrained binary optimization, which can represent many optimization problems more efficiently than quadratic unconstrained binary optimization, but how to quickly solve it has ...
Bi-Ying Wang, Xiaopeng Cui, Qingguo Zeng, Yemin Zhan, Man-Hong Yung, Yu Shi   +5 more
doaj   +1 more source

An Efficient Algorithm for Unconstrained Optimization [PDF]

Mathematical Problems in Engineering, 2015
This paper presents an original and efficient PSO algorithm, which is divided into three phases: (1) stabilization, (2) breadth-first search, and (3) depth-first search. The proposed algorithm, called PSO-3P, was tested with 47 benchmark continuous unconstrained optimization problems, on a total of 82 instances.
de-los-Cobos-Silva, Sergio Gerardo, Gutiérrez-Andrade, Miguel Ángel, Mora-Gutiérrez, Roman Anselmo, Lara-Velázquez, Pedro, Rincón-García, Eric Alfredo, Ponsich, Antonin   +5 more
openaire   +2 more sources

Physics‐Grounded Materials Artificial Intelligence for Reliable Materials Discovery

Advanced Functional Materials, EarlyView.
Physics‐Grounded Materials AI (PhysMat AI) integrates physical priors, descriptors, constraints, verification, and data infrastructure into a unified full‐stack framework, enabling reliable, interpretable, and autonomous AI‐driven materials discovery.
Yuhang Wang, Qian Wang, Seong‐Hoon Jang, Hao Li   +3 more
wiley   +1 more source