Results 71 to 80 of about 1,977,959 (288)
An Adaptive Particle Swarm Optimization Algorithm for Unconstrained Optimization
Complexity, 2020 Conventional optimization methods are not efficient enough to solve many of the naturally complicated optimization problems. Thus, inspired by nature, metaheuristic algorithms can be utilized as a new kind of problem solvers in solution to these types of
Feng Qian +4 more
doaj +1 more source
Sufficient descent directions in unconstrained optimization
Unconstrained optimization, Sufficient descent direction, PSB method, Global convergence, Superlinear convergence,
Dong-Hui Li, Yunhai Xiao, Xiao-Min An
core +1 more source
Advanced Robotics Research, EarlyView.Intelligent Sky Guardians (InSkyGuard) is introduced as a four‐drone swarm that autonomously detects, tracks, and safely captures rogue drones using a coordinated net system. Computer vision and leader–follower control architecture enable synchronized enclosure, while integrated failsafes enhance system reliability. Validated through closed‐environment
Joshua Hastings +6 more
wiley +1 more source
Toward Mechanical Intelligence in Robotics
Advanced Robotics Research, EarlyView.Robots can use their physical bodies to perform functions usually assigned to electronic sensors and controllers. This perspective defines mechanical intelligence through three core operations: filtering inputs, routing mechanical signals, and switching between states.
Xinyi Yang +5 more
wiley +1 more source
Second-order mollified derivatives and optimization [PDF]
The class of strongly semicontinuous functions is considered. For these functions the notion of mollified derivatives, introduced by Ermoliev, Norkin and Wets, is extended to the second order.
Rocca Matteo +2 more
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Advanced Robotics Research, EarlyView.A balanced multimodal food‐waste dataset and a novel Split Spatial‐Spectral Attention fusion framework are presented for robotic contaminant detection. Separate processing of RGB, thermal, and multispectral inputs preserves subtle material signatures before feature integration, reducing modality interference and improving classification and ...
Matthew Vestal +5 more
wiley +1 more source
Distributed Inexact Consensus-Based ADMM Method for Multi-Agent Unconstrained Optimization Problem
IEEE Access, 2019 Recently, the alternating direction method of multipliers (ADMM) has been used effectively to solve the multi-agent unconstrained optimization problems, where the objective function is the sum of privately known local objective functions of agents.
Long Jian +3 more
doaj +1 more source
Broadening Hard‐Magnet Discovery Beyond Symmetry Constraints via Unified Effective Anisotropy
Advanced Science, EarlyView.A unified effective‐anisotropy descriptor (Keff) extends hard‐magnet screening across all seven crystal systems, beyond the uniaxial restriction of conventional searches. Machine‐learning screening of 9320 known ferromagnets and diffusion‐model generation together yield 38 rare‐earth‐free or ‐lean candidates with DFT‐validated magnetic hardness (κ > 1),
Hojae Kim +5 more
wiley +1 more source
A Linesearch Algorithm with Memory for Unconstrained Optimization [PDF]
, 1998 This paper considers algorithms for unconstrained nonlinear optimization where the model used by the algorithm to represent the objective function explicitly includes memory of the past iterations. This is intended to make the algorithm less “myopic” in the sense that its behaviour is not completely dominated by the local nature of the objective ...
GOULD N. +3 more
openaire +3 more sources
Efficiency of coordinate descent methods on huge-scale optimization problems [PDF]
In this paper we propose new methods for solving huge-scale optimization problems. For problems of this size, even the simplest full-dimensional vector operations are very expensive.
NESTEROV, Yurii
core