Research on Monthly Runoff Forecast in Dry Seasons Based on GEO-RVM Model by ZHANG Yajie, CUI Dongwen

“…To improve the accuracy of monthly runoff forecasts during dry seasons,this study proposes a forecasting method that combines the golden eagle optimization (GEO) algorithm and the relevance vector machine (RVM).On the basis of the runoff data of 67 a from a hydrological station in Yunnan Province,the monthly runoff with good correlation before the forecast month is selected as the influencing factor of forecasts,and the influencing factor is reduced in dimension by principal component analysis (PCA).The kernel width factor and hyperparameters of RVM are optimized by the GEO algorithm,and the GEO-RVM model is built to forecast the monthly runoff of the station during the dry season from November to April of the following year.Moreover,the forecast results are compared with those of the GEO-based support vector machine (SVM) model (GEO-SVM).The results demonstrate that the average relative errors of the GEO-RVM model for the monthly runoff forecasts from November to April of the following year are 8.59%,7.34%,5.97%,6.07%,5.99%,and 5.04%,respectively,which means the accuracy is better than that of the GEO-SVM model.The GEO algorithm can effectively optimize the kernel width factor and hyperparameters of RVM,and the GEO-RVM model has better forecast accuracy,which can be used for monthly runoff forecasting during dry seasons.…”
Get full text

A Classification-Based Blood–Brain Barrier Model: A Comparative Approach by Ralph Saber, Sandy Rihana

“…Feature selection algorithms play a crucial role in identifying the most relevant descriptors, thereby enhancing prediction accuracy. …”
Get full text

An efficient approach for mathematical modeling and parameter estimation of PEM fuel based on Young’s double-slit experiment algorithm by Basma S. Alqadi, Deema Mohammed Alsekait, Mohamed F. Issa, Essam H. Houssein, Fatma H. Ismail, Mokhtar Said, Nour Mostafa, Fahmi Elsayed

“…Abstract This paper introduces a novel optimization algorithm, Young’s double-slit experiment algorithm (YSDE), for accurately estimating the unknown parameters of Proton Exchange Membrane Fuel Cell (PEMFC) models. …”
Get full text

Finite-Time Control for Satellite Formation Reconfiguration and Maintenance in LEO: A Nonlinear Lyapunov-Based SDDRE Approach by Majid Bakhtiari, Amirhossein Panahyazdan, Ehsan Abbasali

“…This optimization process minimizes energy usage through a hybrid genetic algorithm and simulated annealing (HGASA), resulting in improved performance. …”
Get full text

A Bi-Objective Optimal Scheduling Method for the Charging and Discharging of EVs Considering the Uncertainty of Wind and Photovoltaic Output in the Context of Time-of-Use Electrici... by Xinfu Pang, Wen Jia, Haibo Li, Qingzhong Gao, Wei Liu

“…Then, the Monte Carlo method was employed to simulate electric vehicle loads and to facilitate the generation of and reduction in scenario scenes. Finally, the model was solved using an improved multi-objective barebones particle swarm optimization algorithm. …”
Get full text

DPF-Bi-RRT^*: An Improved Path Planning Algorithm for Complex 3D Environments With Adaptive Sampling and Dual Potential Field Strategy by Lin Ge, Swee King Phang, Nohaidda Sariff

“…The algorithm achieves a good trade off between the global path optimization and precise local obstacle avoidance by combining dual-attraction and dual-repulsion mechanisms. …”
Get full text

Cloud federation three-layer architecture: game-theoretic QoS modeling by MA Kun, HU Chuangyue, ZHANG Yuzhi, MA Fangchao, WANG Xiaodong, DANG Zhonghua, XIAO Wenhong, CHEN Shuangxi

Get full text

Development and implementation of an automated system of optimal bar cutting at the mill 370/150 at OJSC «BSW – Management Company of the Holding «BMC» by I. A. Pankovets

Get full text

Nonlinear Hysteresis Parameter Identification of Piezoelectric Actuators Using an Improved Gray Wolf Optimizer with Logistic Chaos Initialization and a Levy Flight Variant by Yonggang Yan, Kangqiao Duan, Jianjun Cui, Shiwei Guo, Can Cui, Yongsheng Zhou, Junjie Huang, Geng Wang, Dengpan Zhang, Fumin Zhang

“…This paper proposes an improved Gray Wolf Optimization (GWO) algorithm for high-accuracy identification of hysteresis model parameters based on the Bouc–Wen (BW) differential equation. …”
Get full text

Machine learning-based prediction of optimal antenatal care utilization among reproductive women in Nigeria by Jamilu Sani, Adeyemi Oluwagbemiga, Mohamed Mustaf Ahmed

Get full text

Dynamic reconfiguration of the distribution systems with Load Duration Curve (LDC) model for reducing the losses and improving the voltage profile by Sana Sadeghi, Alireza Jahangiri, Ahmad Ghaderi Shamim

“…Simulations were conducted on the well-established IEEE 33-bus test system, employing MATLAB software in conjunction with a genetic algorithm to minimize losses and optimize voltage profiles. …”
Get full text

Structural Parameter Optimization of the Vector Bracket in a Vertical Takeoff and Landing Unmanned Aerial Vehicle by Wenshuai Liu, Wenyong Quan, Junli Wang, Xiaomin Yao, Qingzheng Liu, Qiang Liu, Yuxiang Tian

“…A kriging algorithm was subsequently applied to construct response surface models based on the results. …”
Get full text

The Optimization of Supply–Demand Balance Dispatching and Economic Benefit Improvement in a Multi-Energy Virtual Power Plant within the Jiangxi Power Market by Tang Xinfa, Wang Jingjing, Wang Yonghua, Wan Youwei

“…The results demonstrate that the proposed scheduling optimization method significantly improves economic benefits while ensuring grid stability. …”
Get full text

Algorithms for Load Balancing in Next-Generation Mobile Networks: A Systematic Literature Review by Juan Ochoa-Aldeán, Carlos Silva-Cárdenas, Renato Torres, Jorge Ivan Gonzalez, Sergio Fortes

“…The need for enhanced radio resource allocation schemes, improved user mobility and increased throughput, driven by a rising demand for data, has necessitated the development of diverse algorithms that optimize output values based on varied input parameters. …”
Get full text

An Improved UNet-Based Path Recognition Method in Low-Light Environments by Wei Zhong, Wanting Yang, Junhuan Zhu, Weidong Jia, Xiang Dong, Mingxiong Ou

“…The optimal attention mechanism is incorporated into the optimized network to enhance the model’s ability to detect path edges and improve detection performance. …”
Get full text

Predicting Endpoint Temperature of Molten Steel in VD Furnace Refining Process Using Metallurgical Mechanism and Bayesian Optimization XGBoost by Ji XU, Zicheng XIN, Mo LAN, Wenhui LIN, Bo ZHANG, Qing LIU

“…The results indicated that BO hyperparameter optimization is the most effective, providing the model with the best performance and higher prediction accuracy than the other two optimization algorithms. …”
Get full text

Deep Learning-Augmented Evolutionary Strategies for Intelligent Global Optimization by Absalom El-Shamir Ezugwu, Olaide Nathaniel Oyelade, Jeffrey Ovre Agushaka, Apu Kumar Saha

“…Friedman’s test ranked SIRO 4th overall, with SSA as the top-performing algorithm. Additionally, SIRO was tested on real-world optimization problems, including mechanical engineering design, hyperparameter tuning, and feature selection for medical image classification. …”
Get full text

An Application of Quasi Newton Algorithm and Improvement of Sliding Surface for Robot Control by Chi-Ngon Nguyen, Thanh Tung Pham

Get full text

A Numerical Modeling Study of a New Type of Hydraulic Mechanical Continuously Variable Transmission (HMCVT) with Optimized Transmission Efficiency by Zexin Ma, Zhengyu Li, Deming Sun, Yanbin Cai, Jiwei Zhang, Hongyu Liu, Qingxin Wang, He Li, Long Zhou, Wenbin Yu, Feiyang Zhao

Get full text

Quaternion generative adversarial -driven Soc estimation using Tyrannosaurus optimizer for improving hybrid electric vehicles renewably powered energy management by M. Sivaramkrishnan, Jaganathan Subramani, Mohammad Mukhtar Alam, Liew Tze Hui

“…For more accurate SOC estimate, the proposed approach employs a Quaternion Generative Adversarial Network (QGAN) model. When hyper parameter tuning, the prototype is invigorated employing the Tyrannosaurus optimization algorithm (TOA) to fine-tune SOC estimate outcomes of the QGAN model. …”
Get full text