A Mixed-Integer Linear Programming Model for Addressing Efficient Flexible Flow Shop Scheduling Problem with Automatic Guided Vehicles Consideration by Dekun Wang, Hongxu Wu, Wengang Zheng, Yuhao Zhao, Guangdong Tian, Wenjie Wang, Dong Chen

Get full text

Stability analysis and controller parameter optimization method for ship power electronic propulsion system based on Middlebrook criterion by Chenghu XU, Weibo LI, Hao ZHANG, Zhiming PENG, Hualiang FANG

“…Finally, a simulation model of the DC propulsion system is constructed to simulate and analyze the influence of the support capacitance and equivalent resistance and inductance of the DC bus on the stability of the system.ResultsThe simulation results show that the system's stability margin is obviously improved after the controller parameters are optimized by the particle swarm algorithm, which in turn lowers the value of support capacitance and reduces the overall size of the DC propulsion system's converter.ConclusionThe findings of this study can provide useful references for research on voltage oscillations and their suppression in integr-ated power systems with a significant proportion of power electronic devices.…”
Get full text

Detection of Welding Defects Tracked by YOLOv4 Algorithm by Yunxia Chen, Yan Wu

Get full text

Enhancing agricultural research with an Attention-Based Hybrid Model for precise classification of rice varieties by Nuzhat Noor Islam Prova

Get full text

Multi-fault diagnosis and damage assessment of rolling bearings based on IDBO-VMD and CNN-BiLSTM by Lihai Chen, Xiaolong Bai, Yonghui He, Dong Jia, Yican Li, Zhenshui Li

“…Chaotic mapping, Golden sine algorithm and cosine iteration strategy are introduced to improve the performance of DBO, and the hyperparameters of VMD are optimised using IDBO to improve the signal pre-processing. …”
Get full text

Performance of pelican optimizer for energy losses minimization via optimal photovoltaic systems in distribution feeders. by Zuhair Alaas, Ghareeb Moustafa, Hany Mansour

“…The PO is a novel bio-inspired optimization algorithm that draws inspiration from pelicans' intelligence and behavior which incorporates unique methods for exploration and exploitation, improving its effectiveness in various optimization challenges. …”
Get full text

Artificial Intelligence and/or Machine Learning Algorithms in Microalgae Bioprocesses by Esra Imamoglu

“…Commonly employed ML algorithms, including the support vector machine (SVM), genetic algorithm (GA), decision tree (DT), random forest (RF), artificial neural network (ANN), and deep learning (DL), each have unique strengths but also present challenges, such as computational demands, overfitting, and transparency. …”
Get full text

Photovoltaic Power Generation Forecasting Based on Secondary Data Decomposition and Hybrid Deep Learning Model by Liwei Zhang, Lisang Liu, Wenwei Chen, Zhihui Lin, Dongwei He, Jian Chen

“…This paper proposes a learning model named CECSVB-LSTM, which integrates several advanced techniques: a bidirectional long short-term memory (BILSTM) network, Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), variational mode decomposition (VMD), and the Sparrow Search Algorithm (CSSSA) incorporating circle chaos mapping and the Sine Cosine Algorithm. …”
Get full text

Stability analysis of semi-submersible floating wind turbines based on gyro-turbine coupled dynamics model by Wancheng Wang, Hao Li, Yihang Yang, Kai Sheng, Lijing Chen

“…Based on this model, an innovative PSO-optimized fuzzy control strategy is proposed, utilizing intelligent particle swarm optimization algorithms to adjust controller parameters for optimal performance under various environmental conditions. …”
Get full text

Size optimization method of the Watt-II six-bar mechanism based on particle swarm optimization by H. Ye, H. Ye, Z. Niu, Z. Niu, D. Han, D. Han, X. Su, X. Su, W. Chen, W. Chen, G. Tu, G. Tu, T. Zhu, T. Zhu

“…<p>Aiming at the difficult problem of comprehensive scale design of the six-bar mechanism in engineering practice, kinematic and dynamic analysis and modeling of the Watt-II six-bar mechanism were carried out and combined with the particle swarm optimization (PSO) algorithm, the size optimization model of the Watt-II six-bar mechanism was established, and the size optimization of the Watt-II six-bar mechanism was completed. …”
Get full text

Current state and prospects of development of energy-optimal control systems for 2ES6 electric locomotives by S. G. Istomin, K. I. Domanov, A. P. SHATOKHIN, I. N. Denisov

“…Further research would be focused on the development of technology for building dynamic models of energy-optimal real-time locomotive movement with train.…”
Get full text

Future Smart Grids Control and Optimization: A Reinforcement Learning Tool for Optimal Operation Planning by Federico Rossi, Giancarlo Storti Gajani, Samuele Grillo, Giambattista Gruosso

“…In this context, it is crucial to integrate technological advancements with innovative planning algorithms, particularly those based on artificial intelligence (AI). …”
Get full text

Pre-disaster evacuation transport network design under uncertain demand and connectivity reliability: a novel bi-level programming model by Junxiang Xu, Divya Jayakumar Nair, S. Travis Waller

“…For the solution of this model, an Improved Genetic Algorithm combined with Non-dominated Sorting Genetic Algorithm II(IGA-NSGA-II) is designed. …”
Get full text

Integration of Hybrid Machine Learning and Multi-Objective Optimization for Enhanced Turning Parameters of EN-GJL-250 Cast Iron by Yacine Karmi, Haithem Boumediri, Omar Reffas, Yazid Chetbani, Sabbah Ataya, Rashid Khan, Mohamed Athmane Yallese, Aissa Laouissi

“…The results showed that the coated Si₃N₄ tool achieved the best surface finish, with minimal cutting force and power consumption, while the uncoated Si₃N₄ and CBN tools performed slightly worse. Advanced optimization models including improved grey wolf optimizer–deep neural networks (DNN-IGWOs), genetic algorithm–deep neural networks (DNN-GAs), and deep neural network–extended Kalman filters (DNN-EKF) were compared with traditional methods like Support Vector Machines (SVMs), Decision Trees (DTs), and Levenberg–Marquardt (LM). …”
Get full text

Enhancing stochastic optimal power flow with modified cheetah optimizer for integrating renewable energy sources by Majid Saeidi, Taher Niknam, Mohsen Zare, Zulfiqar Ali Memon

“…Abstract In this paper, a modified cheetah optimizer (MCO) algorithm is presented, which has been designed to address the optimal power flow (OPF) problem in power grids that utilize renewable energy sources (RES). …”
Get full text

Feature-based enhanced boosting algorithm for depression detection by Muhammad Sadiq Rohei, Kasturi Dewi Varathan, Shivakumara Palaiahnakote, Nor Badrul Anuar

“…Thus, this study has developed a novel feature-based enhanced boosting algorithm (F-EBA). The proposed model covers two pipelines, the feature engineering pipeline which improves the quality of features by picking up the most relevant features while the classification pipeline uses an ensemble approach designed to boost/elevate the model’s performances. …”
Get full text

Reduced-Complexity and Robust Surface Water Path Delineation for Large Real-World Terrain Using Boundary Element Method by Ajalawit Chantaveerod, Kampol Woradit, Andrew Seagar, Thunyawat Limpiti

Get full text

Provident garbage collection algorithm for SSD storage system by Xuezhen TU, Zhenjiang Huang, Zhengguang CHEN

“…A predictive based proactive garbage collection algorithm was proposed.Firstly,the data was separated according to different heat factors,then the upper and lower predictions were performed on the number of different types of page allocation requests (PAR) that would be reached in the future.While satisfying the page allocation request lower prediction,the PAR upper prediction requirement was maximally satisfied,the WA problem was optimized,and invalid effective data migration was reduced,thereby maximizing the garbage collection utility.A mathematical model was defined for this problem,and an algorithm for obtaining the approximate optimal solution was given.The applicable scenario of the model was analyzed.The practical results show that the algorithm can obtain the maximum benefit and can significantly improve the performance of SSD and reduce the cost.…”
Get full text

Congestion Influence on Optimal Bidding in a Competitive Electricity Market using Particle Swarm Optimization by OICC Press Authors

“…In this paper, the bidding strategy problem with congestion management is modeled as an optimization problem and solved using Particle Swarm Optimization (PSO).  …”
Get full text

Democratization of Crop Irrigation: A Socio-Technical Optimization Approach Using Particle Swarm Optimization by Hasna Elalaoui Elabdallaoui, Youssef Mourdi, Abdelaziz ElFazziki, Mohamed Sadgal

Get full text