Results 81 to 90 of about 79,920 (249)

An Enhanced Partial Search to Particle Swarm Optimization for Unconstrained Optimization

Mathematics, 2019
Particle swarm optimization (PSO) is a population-based optimization technique that has been applied extensively to a wide range of engineering problems. This paper proposes a variation of the original PSO algorithm for unconstrained optimization, dubbed
Shu-Kai S. Fan, Chih-Hung Jen
doaj   +1 more source

Rockburst prediction based on data preprocessing and hyperband‐RNN‐DNN

Deep Underground Science and Engineering, EarlyView.
A data preprocessing workflow is proposed to address challenges in rockburst data analysis. Coupled algorithms preprocess the data set, and hyperband optimization is used to enhance RNN performance. Results show that preprocessing improves accuracy, while dense layers enhance model stability and prediction performance.
Yong Fan, Chenxi Yin, Guangdong Yang, Shengyong Ding, Bin Tian   +4 more
wiley   +1 more source

Motion planning and control of an installation robot for attitude adjustment of arc parts in underground shield tunneling

Deep Underground Science and Engineering, EarlyView.
Inspired by spiders, the multilegged walk‐through assembling robot for arc parts achieves high‐precision synchronous control under heavy loads through dual‐layer hydraulic pose dynamics modeling and hierarchical pressure optimization, significantly enhancing shield tunneling assembly efficiency and precision.
Quan Xiao, Guofei Xiang, Liang Liao, Lai Wei, Hongli Wang, Songyi Dian   +5 more
wiley   +1 more source

A novel discrete particle swarm optimization for p-median problem

Journal of King Saud University: Engineering Sciences, 2014
p-Median problem is a well-known discrete optimization problem aiming to locate p number of facilities that satisfies the demand of multiple places with minimum cost.
Mehmet Sevkli, Ruslan Mamedsaidov, Fatih Camci   +2 more
doaj   +1 more source

Computationally Driven Advances in Cu‐CNT On‐Chip Interconnect Materials: From First Principles to Machine Learning

ENERGY &ENVIRONMENTAL MATERIALS, EarlyView.
A multiscale framework integrating electronic, mechanical, and thermal analysis with machine learning to optimize carbon nanotube interconnects. As the component dimensions in integrated circuits shrink to extreme scales, the complexity of interconnect systems is increasing significantly, necessitating an urgent and comprehensive upgrade of ...
Changhong Zhang, Jie Liang, Yi Li, Zhenyu Wang, Haoyuan Li, Zhen Yuan, Jiuren Zhou, Rongmei Chen, Wensheng Zhao, Lei Zhang, Hanshen Xin, Jianhua Zhang   +11 more
wiley   +1 more source

Application of a particle swarm optimization for shape optimization in hydraulic machinery

EPJ Web of Conferences, 2017
A study of shape optimization has become increasingly popular in academia and industry. A typical problem is to find an optimal shape, which minimizes (or maximizes) a certain cost function and satisfies given constraints.
Moravec Prokop, Rudolf Pavel
doaj   +1 more source

A novel statistically tracked particle swarm optimization method for automatic generation control

Journal of Modern Power Systems and Clean Energy, 2014
Particle swarm optimization (PSO) is one of the popular stochastic optimization based on swarm intelligence algorithm. This simple and promising algorithm has applications in many research fields.
Cheshta Jain, H. K. Verma, L. D. Arya
doaj   +1 more source

Numerical Simulation of Post‐Yield Hysteretic Behavior of Lap‐Spliced Reinforced Concrete Bridge Pier Walls Under Earthquake Loading

Earthquake Engineering &Structural Dynamics, EarlyView.
ABSTRACT Reinforced concrete pier walls designed before the 1970s often incorporate lap splice in potential plastic‐hinge regions. Previous experimental tests indicate that most of pier walls experienced post‐yield lap splice failure, necessitating a modeling approach that captures not only lap splice strength but also deformation capacity.
Gun Chan Lee, Sujith Mangalathu, Jong‐Su Jeon   +2 more
wiley   +1 more source

Analysis of Optimal Power Flow Using Combined PSO-GSA Technique [PDF]

ITM Web of Conferences
Using a hybrid approach that incorporates both particle swarm optimization (PSO) and gravitational search algorithms (GSA), this project aims to find the best way for power systems to distribute their energy.
Patel Nilesh M., Thangadurai N., Patel Chirag   +2 more
doaj   +1 more source

Probabilistic Multi‐Objective Energy Management System Model for an Energy Hub With PtG Technology for Cost Reduction and System Flexibility Improvement

Energy Science &Engineering, EarlyView.
Overview of the under‐study hub energy model showing the energy conversion and distribution among integrated sources and loads. ABSTRACT In this paper, a probabilistic bi‐objective energy management system (EMS) model is proposed for an energy hub (EH) equipped with renewable energy sources such as photovoltaic and wind turbine connected to the main ...
Mohammad Khoshabi, Mehrdad Ahmadi Kamarposhti, Mohsen Sedighi, Alireza Ghafouri   +3 more
wiley   +1 more source