Source-storage-load optimization control technology of DC microgrid with virtual energy storage by WANG Chang, JIANG Yu, FU Shouqiang, SHU Yinan, ZHANG Xiangyu

“…On this basis, under the coordinated control of source and storage of DC microgrid, particle swarm optimization algorithm is used to optimize the design of virtual capacitance values in different periods of time to improve the economic benefits of the system. …”
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Enhancing Drone Detection via Transformer Neural Network and Positive–Negative Momentum Optimizers by Pavel Lyakhov, Denis Butusov, Vadim Pismennyy, Ruslan Abdulkadirov, Nikolay Nagornov, Valerii Ostrovskii, Diana Kalita

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Optoelectronic optimization of graded-bandgap CdTeSe thin-film solar cells by Faiz Ahmad, Akhlesh Lakhtakia, Peter B Monk

“…Optimization using the differential evolution algorithm indicates that linearly and nonlinearly graded CdTeSe photon-absorbing layers of 3000 nm thickness can deliver an efficiency of 21.79% and 21.22%, respectively, when the selenium-to-tellurium ratio is not allowed to exceed 2/3. …”
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Hub-and-spoke network design to optimize government subsidy costs for maritime transportation in Indonesia by Windra Priatna Humang, Djoko Prijo Utomo, Hasriwan Putra, Dedy Arianto, Rutma Pujiwat, Sucipto, Dwi Phalita Upahita, Nur Fitriana, Maharani Almira Salsabilla, Yustina Niken Raharina Hendra, Asep Yayat Nurhidayat, Mega Novetrishka Putri, Mohamad Ivan Aji Saputro, Amelia Santoso, Ivan Kristianto Singgih, Dina Natalia Prayogo, Indri Hapsari, Olyvia Novawanda, Stefanus Soegiharto, Jerry Agus Arlianto

“…A deterministic optimization approach was adopted, leveraging Genetic Algorithm (GA) techniques to formulate optimal shipping routes and strategically position hub ports. …”
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Joint Configuration and Optimization of Multi-microgrid Shared Energy Storage Based on Coalition Game by Congwei JIANG, Qinghe OU, Zhongchao WU, Jian ZHANG, Shu YANG, Jianan ZHU, Qian AI

“…Based on the NSGA2 algorithm, the Pareto frontier of the coalition’s overall energy storage planning is obtained. …”
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Improved Iterative CD-Spline Approach for Building Boundary Regularization Using Airborne LiDAR Data by Renato Cesar dos Santos, Ayman F. Habib, Mauricio Galo

“…To overcome this limitation, we proposed the Improved Iterative Changeable Degree-Spline (IICDS) that consists of testing several CP configurations, resulting in multiple contour models for each building. …”
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Data enhanced iterative few-sample learning algorithm-based inverse design of 2D programmable chiral metamaterials by Zhao Zeyu, You Jie, Zhang Jun, Du Shiyin, Tao Zilong, Tang Yuhua, Jiang Tian

“…In this way, the DEIFS algorithm replaces the time-consuming iterative optimization process with a faster and simpler approach that achieves accurate inverse design with dataset whose amount is at least one to two orders of magnitude less than most previous deep learning methods, reducing the dependence on simulated spectra. …”
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Optimizing Small Cell Performance: A New MIMO Paradigm With Distributed ASTAR-RISs by Shakil Ahmed, Ahmed E. Kamal, Mohamed Y. Selim, Md Akbar Hossain, Saifur Rahman Sabuj

“…Our proposed method uses an alternating optimization algorithm to optimize the phase shift matrix at the ASTAR-RIS and the hybrid beamforming at the mBS. …”
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A Sequential Generation Redispatch Algorithm to Ensure Power System Small Signal Stability under Low-Frequency Oscillations by Hassan Golzari-Kolur, Seyed Mohammad-Taghi Bathaee, Turaj Amraee

“…Then, in the process of improving the small signal stability, the modal analysis specifies the system stability status in each step, and the proposed second-order convex redispatch model defines the optimal direction of generation rescheduling. …”
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A Day-Ahead Optimal Battery Scheduling Considering the Grid Stability of Distribution Feeders by Umme Mumtahina, Sanath Alahakoon, Peter Wolfs

“…This study presents a comprehensive framework for optimizing energy management systems by integrating advanced methodologies for weather forecasting, energy cost analysis, and grid stability using a mixed-integer linear programming (MILP) algorithm. …”
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Optimal design and performance prediction of stepped honeycomb labyrinth seal using CFD and ANN by Geunseo Park, Min Seok Hur, Tong Seop Kim

“…An ANN-based performance prediction metamodel was developed, and a genetic algorithm was applied to the metamodel to optimize seal geometry, achieving a 12.34% improvement in leakage performance over the reference seal. …”
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Application of adaptive virtual synchronous generator based on improved active power loop in photovoltaic storage systems by Youzhuo Zheng, Yutao Xu, Yekui Yang, Long Hua, Yuqing Yang

“…Then, the adaptive inertia algorithm is incorporated into the active power loop of the VSG control, and an adaptive inertia control method based on the improved active power loop is proposed. …”
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Implementation of personalized customization and enhanced experiences for cultural tourism resources using genetic algorithm-based virtual reality technology by Huiya Xing, Xiangyi Li, Min Liu, Yicong Zhong

“…By adjusting to these individual parameters, the algorithm cleverly optimizes tourist itineraries. The DDE-GA-powered VR system works better than current methods, according to experimental data, with improvements in reaction time (1.1 s), accuracy (98 %), precision (97 %), and modeling error (0.10). …”
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Comparison of Support Vector Machine and Decision Tree Algorithm Performance with Undersampling Approach in Predicting Heart Disease Based on Lifestyle by Gusti Ayu Putu Febriyanti, Anna Baita

“…The K-fold cross-validation method with K=10 and hyperparameter tuning were applied to obtain the optimal performance of both models. The results showed that SVM without undersampling achieved 92% accuracy, while with undersampling the accuracy decreased to 76%. …”
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Flaw-YOLOv5s: A Lightweight Potato Surface Defect Detection Algorithm Based on Multi-Scale Feature Fusion by Haitao Wu, Ranhui Zhu, Hengren Wang, Xiangyou Wang, Jie Huang, Shuwei Liu

“…To elevate detection accuracy as well as shorten the computational load of the model, this paper proposes a lightweight Flaw-YOLOv5s algorithm for potato surface defect detection. …”
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Classification of Anxiety Levels of IGD Patients at RSU Royal Prima Medan Using Support Vector Machine (SVM) Algorithm by Kharisma Gunanta Ginting, Nugroho Prasetyo, Al Vino Gunawan, Magdalena Sihombing, Adli Abdillah Nababan

“…The preprocessing process includes imputing missing values and normalizing numerical features so that the model can learn optimally. Performance evaluation shows that the use of SMOTE increases classification accuracy from 95% to 97%, as well as improving precision, recall, and F1-score metrics at almost all anxiety levels. …”
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Adversarial Reinforcement Learning-Based Converged Communication Efficiency Improvement Method for Power Distribution Network by Linyu PENG, Xu LIU, Wei TANG, Qing LIU, Hao FANG, Guanghui ZHANG

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Multi-Objective Optimization of Insulation Thickness with Respect to On-Site RES Generation in Residential Buildings by Agis M. Papadopoulos, Konstantinos Polychronakis, Elli Kyriaki, Effrosyni Giama

“…This paper investigates the optimization of insulation thickness with respect to the integration of renewable energy systems in residential buildings in order to improve energy efficiency, maximize the contribution of renewables and reduce life cycle costs. …”
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BIT*+TD3 Hybrid Algorithm for Energy-Efficient Path Planning of Unmanned Surface Vehicles in Complex Inland Waterways by Yunze Xie, Yiping Ma, Yiming Cheng, Zhiqian Li, Xiaoyu Liu

“…To address the limitations of traditional path planning algorithms in dynamic environments, the proposed BIT*+TD3 model leverages the BIT* algorithm to generate initial paths in static environments through elliptical informed sampling and heuristic search. …”
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Data Mining Techniques for Early Detection and Classification of Plant Diseases: An Optimization-Based Approach by Wagh Swapnil, Sharma Ruchi

“…Furthermore, low-level optimization techniques like genetic algorithms as well as particle swarm optimization are used to fine tune the specific model parameters and to reduce the computational overhead for improving the detection efficacy still more. …”
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