Adaptive energy loss optimization in distributed networks using reinforcement learning-enhanced crow search algorithm by S. Bharath, A. Vasuki

“…Unlike traditional methods such as Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and standard Crow Search Algorithm (CSA), which suffer from premature convergence and limited adaptability to real-time variations, Reinforcement Learning Enhanced Crow Search Algorithm (RL-CSA) which is proposed in this research work solves network reconfiguration optimization problem and minimize energy losses. …”
Get full text

Optimized solar PV integration for voltage enhancement and loss reduction in the Kombolcha distribution system using hybrid grey wolf-particle swarm optimization by Awot Getachew Abera, Tefera Terefe Yetayew, Assen Beshr Alyu

“…A hybrid optimization approach combining Particle Swarm Optimization and Grey Wolf Optimization algorithms is proposed for determining optimal sizing and placement of PV-based DGs. …”
Get full text

An improved ant colony optimization strategy for dual-objective high-speed train scheduling by Hui Zhao, Jiahuan Zhang, Haixing Li, Dong Li

“…Then, an improved ant colony optimization algorithm is proposed to solve the model. …”
Get full text

A multi-strategy improved snake optimizer and its application to SVM parameter selection by Hong Lu, Hongxiang Zhan, Tinghua Wang

“…Nevertheless, SO has the shortcomings of weak population initialization, slow convergence speed in the early stage, and being easy to fall into local optimization. To address these problems, an improved snake optimizer algorithm (ISO) was proposed. …”
Get full text

Research on improving the ranging accuracy of ships with stereo vision through Kalman filter optimization. by Zhongbo Peng, Jie Han, Liang Tong, Lumeng Wang, Dan Liu, Shijie Sun

Get full text

Multi-objective optimization placement strategy for SDN security controller considering Byzantine attributes by Tao WANG, Hongchang CHEN

“…By giving the software defined network distributed control plane Byzantine attributes, its security can be effectively improved.In the process of realizing Byzantine attributes, the number and location of controllers, and the connection relationship between switches and controllers can directly affect the key network performance.Therefore, a controller multi-objective optimization placement strategy for SDN security controllers considering Byzantine attributes was proposed.Firstly, a Byzantine controller placement problem (MOSBCPP) model that comprehensively considered interaction delay, synchronization delay, load difference and the number of controllers was constructed.Then, a solution algorithm based on NASG-II was designed for this model, which included the initialization function, the mutation function, the fast non-dominated sorting function and the elite strategy selection function.Simulation results show that this strategy can effectively reduce interaction delay, synchronization delay, load difference and the number of controllers, while improving control plane security.…”
Get full text

CFD-based aerodynamic optimization of the fairing for a high-speed elevator by Xiawei Shen, Aimin Wang, Wanbing Liu, Rongyang Wang

“…The cross-section of the fairing is parameterized by NURBS curves; then, the Latin experimental design method is used to generate test sample points, a mathematical model is formulated utilizing the response surface model approximation, and global optimization is conducted through the application of a multi-island genetic algorithm. …”
Get full text

Parameter Optimization of Milling Process for Surface Roughness Constraints by GUO Bin, YUE Caixu, ZHANG Anshan, JIANG Zhipeng, YUE Daxun, QIN Yiyuan

“… In the milling process of 6061 aluminum considering the requirement of controlling the surface roughness of workpiece, artificially selected milling parameters may be conservative, resulting in low material removal rate and high manufacturing cost.Taking the surface roughness as the constraint condition and the maximum material removal rate as the goal, the surface roughness regression model is established based on extreme gradient boosting (XGBOOST) with the spindle speed, feed speed and cutting depth as the optimization objects.The milling parameters of spindle speed, feed speed and cutting depth are optimized by genetic algorithm.The optimal milling parameters are obtained by using the multi objective optimization characteristics of genetic algorithm.It can be seen from the four groups of optimization results that the maximum change of surface roughness is only 0.048μm, while the minimum material removal rate increases by 2458.048mm3/min.While achieving surface roughness, the processing efficiency is improved, and the manufacturing costs are reduced, resulting in good optimization effects, which has a certain guiding role in the actual processing.…”
Get full text

Load forecasting of microgrid based on an adaptive cuckoo search optimization improved neural network by Liping Fan, Pengju Yang

“…Finally, the weights and biases of the forecasting model were optimized by the improved cuckoo search algorithm. …”
Get full text

Optimization method for educational resource recommendation combining LSTM and feature weighting by Meixia Yang

“…Finally, the bidirectional long short-term memory network algorithm is used for encoding iteration to minimize data omission and improve data interactivity, achieving accurate recommendation of educational resources. …”
Get full text

On the Use of an Improved Artificial Fish Swarm Algorithm-Backpropagation Neural Network for Predicting Dam Deformation Behavior by Bo Dai, Hao Gu, Yantao Zhu, Siyu Chen, E. Fernandez Rodriguez

“…The hybrid model’s preciseness is verified against the radial displacements of a pendulum in a concrete arch dam and simulations of four models: statistical model, BP-ANN optimized by genetic algorithm (GA), particle swarm optimization (PSO), and AFSA. …”
Get full text

Detecting cyber attacks in vehicle networks using improved LSTM based optimization methodology by C. Jayasri, V. Balaji, C. M. Nalayini, S. Pradeep

“…Detection is executed through an Improved Long Short-Term Memory (ILSTM) model, whose parameters are optimized using the Crocodile Optimization Algorithm (COA), aiming to maximize classification accuracy. …”
Get full text

Comparative analysis of FACT devices for optimal improvement of power quality in unbalanced distribution systems by Ahmed M. Elkholy, Dmitry I. Panfilov, Ahmed E. ELGebaly

“…To improve network asymmetry, an optimization analysis is carried out to ascertain how each proposed device will work. …”
Get full text

Angular Random Walk Improvement of Resonator Fiber Optic Gyro by Optimizing Modulation Frequency by Wei Gao, Zhuo Wang, Guochen Wang, Weiqi Miao

“…In order to make this method effective, we use the particle swarm optimization algorithm to optimize the multi-parameter involved in ARW. …”
Get full text

Improved Data Transmission Scheme of Network Coding Based on Access Point Optimization in VANET by Zhe Yang, Lingzhi Li, Wenqiang Yao, Kaisheng Xu, Dongxin Tang

“…So the AP deployment is one of the key issues to improve the communication performance of VANET. In this paper, an access point optimization method is proposed based on particle swarm optimization algorithm. …”
Get full text

Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection by R. Sudha, Ajith Damodaran, Gunaselvi Manohar

“…At first, the data for predicting air quality are collected from the relevant data sources. The proposed model introduces a novel methodology for weighted feature selection utilizing an Improved Gannet Optimization Algorithm (IGOA) aimed at enhancing the performance of data classification. …”
Get full text

5G-Practical Byzantine Fault Tolerance: An Improved PBFT Consensus Algorithm for the 5G Network by Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

“…With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant consensus algorithm with three ways to improve PBFT. …”
Get full text

An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis by Yao Zhang, Xu Wang, Haohua Xiu, Wei Chen, Yongxin Ma, Guowu Wei, Lei Ren, Luquan Ren

“…Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. …”
Get full text

Machine Learning-Assisted Optimization of Femtosecond Laser-Induced Superhydrophobic Microstructure Processing by Lifei Wang, Yucheng Gu, Xiaoqing Tian, Jun Wang, Yan Jia, Junjie Xu, Zhen Zhang, Shiying Liu, Shuo Liu

“…Furthermore, by utilizing this small sample dataset, various machine learning algorithms were employed to establish a prediction model for the contact angle, among which support vector regression demonstrated the optimal predictive accuracy. …”
Get full text

Impact of Coordinated Electric Ferry Charging on Distribution Network Using Metaheuristic Optimization by Rajib Baran Roy, Sanath Alahakoon, Piet Janse Van Rensburg

“…Using DIgSILENT PowerFactory integrated with MATLAB Simulink and a Python-based control system, four proposed ferry terminals equipped with BESSs (Battery Energy Storage Systems) are simulated. A dynamic model of BESS operation is optimized using a balanced hybrid metaheuristic algorithm combining GA-PSO-BFO (Genetic Algorithm-Particle Swarm Optimization-Bacterial Foraging Optimization). …”
Get full text