Results 71 to 80 of about 81,531 (237)

A hidden Markov model and reinforcement learning‐based strategy for fault‐tolerant control

The Canadian Journal of Chemical Engineering, EarlyView.
Abstract This study introduces a data‐driven control strategy integrating hidden Markov models (HMM) and reinforcement learning (RL) to achieve resilient, fault‐tolerant operation against persistent disturbances in nonlinear chemical processes. Called hidden Markov model and reinforcement learning (HMMRL), this strategy is evaluated in two case studies
Tamera Leitao, Debaprasad Dutta, Simant R. Upreti   +2 more
wiley   +1 more source

A Dynamic Multistage Hybrid Swarm Intelligence Optimization Algorithm for Function Optimization

Discrete Dynamics in Nature and Society, 2012
A novel dynamic multistage hybrid swarm intelligence optimization algorithm is introduced, which is abbreviated as DM-PSO-ABC. The DM-PSO-ABC combined the exploration capabilities of the dynamic multiswarm particle swarm optimizer (PSO) and the ...
Daqing Wu, Jianguo Zheng
doaj   +1 more source

Probability prediction of true‐triaxial compressive strength of intact rocks based on the improved PSO‐RVM model

Deep Underground Science and Engineering, EarlyView.
In this work, we propose an improved particle swarm optimization (PSO) algorithm and develop an improved PSO‐relevance vector machine (RVM) model as a substitute for traditional true‐triaxial testing. The model's high prediction accuracy was validated through comparisons with two other machine learning methods and five three‐dimensional Hoek–Brown type
Qi Zhang, Maohui Wang, Ning Wang, Yixin Shen, Xuzhen He   +4 more
wiley   +1 more source

A Multipopulation PSO Based Memetic Algorithm for Permutation Flow Shop Scheduling

The Scientific World Journal, 2013
The permutation flow shop scheduling problem (PFSSP) is part of production scheduling, which belongs to the hardest combinatorial optimization problem.
Ruochen Liu, Chenlin Ma, Wenping Ma, Yangyang Li   +3 more
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

Application of Dynamic Mutated Particle Swarm Optimization Algorithm to Design Water Distribution Networks [PDF]

آب و فاضلاب, 2015
This paper proposes the application of a new version of the heuristic particle swarm optimization (PSO) method for designing water distribution networks (WDNs).
Kazem Mohammadi- Aghdam, Iraj Mirzaei, Nader Pourmahmood, Mohammad Pourmahmood-Aghababa   +3 more
doaj  

Constrained Engineering Optimization Algorithm Based on Elite Selection

Journal of Algorithms & Computational Technology, 2014
Many engineering optimization problems can be state as function optimization with constrained, intelligence optimization algorithm can solve these problems well.
Xuesong Yan, Wenjing Luo, Chengyu Hu, Hong Yao, Qinghua Wu   +4 more
doaj   +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

Curve-Fitting on Graphics Processors Using Particle Swarm Optimization [PDF]

International Journal of Computational Intelligence Systems, 2014
Curve fitting is a fundamental task in many research fields. In this paper we present results demonstrating the fitting of 2D images using CUDA (compute unified device architecture) on NVIDIA graphics processors via particle swarm optimization (PSO ...
R. T. Kneusel
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