Ensemble Learning-Based Wine Quality Prediction Using Optimized Feature Selection and XGBoost by Sonam Tyagi, Ishwari Singh Rajput, Bhawnesh Kumar, Harendra Singh Negi

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Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

“…Hybrid renewable energy systems (HRESs) are being incorporated and evaluated within seaports to realize efficiencies, reduce dependence on grid electricity, and reduce operating costs. The paper adopts a genetic algorithm (GA)-based optimization framework to assess four energy management scenarios that embed wind turbines (WTs), photovoltaic energy (PV), an energy storage system (ESS), and an energy management system (EMS). …”
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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.…”
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Building Energy Optimization Using an Improved Exponential Distribution Optimizer Based on Golden Sine Strategy Minimizing Energy Consumption Under Uncertainty by Mohammad Ali Karbasforoushha, Mohammad Khajehzadeh, Suraparb Keawsawasvong, Lapyote Prasittisopin, Thira Jearsiripongkul

“…In this study, a new improved meta-heuristic algorithm is proposed for solving the energy building optimization (EBO) and also hybrid energy systems optimization considering uncertainty of conditioned surface area subjected to temperature control for BEO and renewable power and load uncertainties for hybrid system. …”
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An Enhanced Distribution System Performance with Optimization Techniques for Location of Electrical Vehicle Charging Stations by Sainadh Singh Kshatri, Venkata Anjani Kumar G, Chilakapati Lenin Babu, Palepu Suresh Babu

“…The proposed methodology leverages the Grey Wolf Optimization (GWO) metaheuristic algorithm, enthused by the grey wolves hunting, to identify the most strategic locations for EVCSs. …”
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Research of UAV 3D path planning based on improved Dwarf mongoose algorithm with multiple strategies by Lixin Mu, Wenhui Liu, Haocheng Wang, Yu Zhang

“…To enhance UAV adaptability in such environments, improve rapid and efficient path planning capabilities, and reduce operational costs, this paper proposes a 3D UAV path planning algorithm based on an improved Dwarf Mongoose Optimization (DMO) algorithm enhanced with multiple strategies. …”
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Optimization method improvement for nonlinear constrained single objective system without mathematical models by HOU Gong-yu, XU Zhe-dong, LIU Xin, NIU Xiao-tong, WANG Qing-le

“…In addition, samples are needed to solve such system optimization problems. Therefore, to improve the optimization accuracy of nonlinear constrained single objective systems that are without accurate mathematical models while considering the cost of obtaining samples, a new method based on a combination of support vector machine and immune particle swarm optimization algorithm (SVM-IPSO) is proposed. …”
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FedDBO: A Novel Federated Learning Approach for Communication Cost and Data Heterogeneity Using Dung Beetle Optimizer by Dongyan Wang, Limin Chen, Xiaotong Lu, Yidi Wang, Yue Shen, Jingjing Xu

“…However, it also faces challenges such as high communication costs and heterogeneous client data.In order to address the above issues. …”
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Magnetic targets positioning method based on multi-strategy improved Grey Wolf optimizer by Binjie Lu, Zongji Li, Xiaobing Zhang

“…Therefore, a Multi-Strategy Improved Grey Wolf Optimizer (MSIGWO) algorithm has been proposed to enhance the accuracy of magnetic target state estimation. …”
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Improved Multiobjective Genetic Algorithm for Partitioning Distributed Photovoltaic Clusters: Balancing Spatial Distance and Power Similarity by Yansen Chen, Kai Cheng, Zhuohuan Li, Shixian Pan, Xudong Hu

“…This cluster segmentation algorithm significantly reduces the complexity and investment cost of the prediction system.…”
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Two-stage robust planning for wind power-photovoltaic-thermal power-pumped storage-battery hybrid system by LUO Yuanxiang, FAN Lidong, WANG Yuhang, LIU Cheng, JIAO Yinghe, WANG Yunlong

“…In the first stage, the capacity configuration of the hybrid system is aiming at minimizing the sum of investment cost and operation and maintenance cost. In the second stage, under a given capacity configuration, the optimal scheduling scheme is determined by constructing an uncertain set of wind power-photovoltaic output, aiming at minimizing the sum of environmental cost and cost of wind power-photovoltaic abandonment. …”
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Optimizing Assembly Error Reduction in Wind Turbine Gearboxes Using Parallel Assembly Sequence Planning and Hybrid Particle Swarm-Bacteria Foraging Optimization Algorithm by Sydney Mutale, Yong Wang, De Tian

“…The methodology results in a 38% reduction in total assembly errors, improving both process accuracy and efficiency. Specifically, the PSBFO algorithm reduced errors from an initial value of 50 to a final value of 5 across 20 iterations, with components such as the low-speed shaft and planetary gear system showing the most substantial reductions. …”
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Improved Virtual Potential Field Algorithm Based on Probability Model in Three-Dimensional Directional Sensor Networks by Junjie Huang, Lijuan Sun, Ruchuan Wang, Haiping Huang

“…Furthermore, cross-set test is used to determine whether the sensory region has any overlap and coverage impact factor is introduced to reduce profitless rotation from coverage optimization, thereby the energy cost of nodes was restrained and the performance of the algorithm was improved. …”
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A design method of composite pixel-like antenna based on improved bald eagle search algorithm by WANG Yongqiang, LIU Bingqi, ZHU Bolin

“…This method not only retains the good convergence of the original algorithm, but also partially improves the global search ability. …”
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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

“…To address this issue, a process optimization framework that couples machine learning and genetic algorithms was proposed and successfully applied to the optimization of femtosecond laser-induced groove structures on TC4 alloy surfaces. …”
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Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

“…This paper presents a reinforcement learning-based approach to automate the tuning of a 6thorder combline bandpass filter, operating at 941 MHz, using a Q-learning algorithm. To reduce complexity, only two tuning screws are considered in the optimization. …”
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Enhanced air quality prediction using adaptive residual Bi-LSTM with pyramid dilation and optimal weighted feature selection by R. Sudha, Ajith Damodaran, Gunaselvi Manohar

“…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. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. …”
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Optimization of artificial intelligence in localized big data real-time query processing task scheduling algorithm by Maojin Sun, Luyi Sun

“…This research not only improves the efficiency of task processing, but also provides new ideas for optimizing future scheduling algorithms.…”
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Improved genetic algorithm based on Shapley value for a virtual machine scheduling model in cloud computing by Lili Chen, Lili Chen, Yuxia Niu

“…IntroductionIn cloud computing, a common idea to reduce operation costs and improve service quality is to study task scheduling algorithms.MethodsTo better allocate virtual machine resources, a virtual machine resource scheduling algorithm, Shapley value method–genetic algorithm (SVM-GA) is proposed. …”
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