Results 61 to 70 of about 19,980 (297)
An Improved Adaptive Trust-Region Method for Unconstrained Optimization
Mathematical Modelling and Analysis, 2014 In this study, we propose a trust-region-based procedure to solve unconstrained optimization problems that take advantage of the nonmonotone technique to introduce an efficient adaptive radius strategy.
Hamid Esmaeili, Morteza Kimiaei
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An Improved Chicken Swarm Optimization Algorithm and its Application in Robot Path Planning
IEEE Access, 2020 Chicken swarm optimization (CSO) algorithm is one of very effective intelligence optimization algorithms, which has good performance in solving global optimization problems (GOPs). However, the CSO algorithm performs relatively poorly in complex GOPs for
Ximing Liang, Dechang Kou, Long Wen
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The Hybrid BFGS-CG Method in Solving Unconstrained Optimization Problems
Abstract and Applied Analysis, 2014 In solving large scale problems, the quasi-Newton method is known as the most efficient method in solving unconstrained optimization problems. Hence, a new hybrid method, known as the BFGS-CG method, has been created based on these properties, combining ...
Mohd Asrul Hery Ibrahim +2 more
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HUBO formulations for solving the eigenvalue problem
Results in Control and Optimization, 2023 Solving the eigenvalue problem is particularly important in almost all fields of science and engineering. With the development of quantum computers, multiple algorithms have been proposed for this purpose.
Kyungtaek Jun, Hyunju Lee
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Advanced Robotics Research, EarlyView.An enhanced universal gripper combining rigid mechanics with self‐adaptable fingers is presented for industrial automation. The novel six‐bar linkage with integrated compliant pad eliminates mechanical interference while enabling passive shape adaptation.
Muhammad Usman Khalid +7 more
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Journal of MathematicsThis paper defines a strong convertible nonconvex (SCN) function for solving the unconstrained optimization problems with the nonconvex or nonsmooth (nondifferentiable) function.
Min Jiang +3 more
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Кібернетика та комп'ютерні технологіїIntroduction. Methods of unconstrained optimization play a significant role in machine learning [1–6]. When solving practical problems in machine learning, such as tuning nonlinear regression models, the extremum point of the chosen optimality criterion ...
Viktor Zadachyn
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LLM‐Integrated Human–Robot Interaction System for Microrobots
Advanced Robotics Research, EarlyView.This paper proposes an LLM‐based control framework for guiding microrobots using human natural language. This framework can convert the natural human speech into safe and executable command sets for reliable navigation in complex environments. The experimental results show high accuracy and robustness in task performance, demonstrating the potential of
Bairong Zhu, Amar Salehi, Tingting Yu
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Lifecycle-Based Swarm Optimization Method for Numerical Optimization
Discrete Dynamics in Nature and Society, 2014 Bioinspired optimization algorithms have been widely used to solve various scientific and engineering problems. Inspired by biological lifecycle, this paper presents a novel optimization algorithm called lifecycle-based swarm optimization (LSO ...
Hai Shen, Yunlong Zhu, Xiaodan Liang
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A new accelerated conjugate gradient method for large-scale unconstrained optimization
Journal of Inequalities and Applications, 2019 In this paper, we present a new conjugate gradient method using an acceleration scheme for solving large-scale unconstrained optimization. The generated search direction satisfies both the sufficient descent condition and the Dai–Liao conjugacy condition
Yuting Chen, Mingyuan Cao, Yueting Yang
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