Advanced Control Technique for Optimal Power Management of a Prosumer-Centric Residential Microgrid by Peter Anuoluwapo Gbadega, Yanxia Sun, Olufunke Abolaji Balogun

“…To solve the multi-objective power management optimization problem, the Teaching-Learning-Based Optimization (TLBO) algorithm was implemented. …”
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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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A Bi-Level Optimization Model for Flexible Capacity Allocation with Coordinated Planning and Operation by Xinyu Yin, Xiaoyan Bian, Qinran Zhu, Jinbin Zhao, Shunfu Lin, Kwok L. Lo

“…The upper planning level introduces the economic costs, flexibility resource capacity, and flexibility index which are used as the evaluation index of system flexibility, while in the lower operation level, a morphological clustering algorithm based on the multiscale and entropy weight method is proposed for obtaining typical scenarios of flexibility demand. …”
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Eight-Figure Pattern for Enhancing the Searching Process of Grey Wolf Optimization (Eight-GWO) by Lec. Ali Hakem Alsaeedi, Suha Muhammed Hadi, Yarub Alazzawi, Emad Badry Badry

“…The proposed model is based on simulating eight pattern movements and embedded with a Grey Wolf Optimizer algorithm (GWO). It is called the Eight-Figure Grey Wolf Optimizer (Eight-GWO). …”
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Class-aware multi-source domain adaptation algorithm for medical image analysis using reweighted matrix matching strategy. by Huiying Zhang, Yongmeng Li, Lei He, Wenbo Zhang, Yuchen Shen, Lumin Xing

“…Additionally, first-order and second-order moment matching strategies are applied to effectively align the source and target domains, while an adaptive weighting mechanism is utilized to optimize the contributions of different source domains to the target domain. …”
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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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Optimizing Strategies in Patients Affected by Tumors Infiltrating the Skull: A Single Center Experience by Giuseppe Emmanuele Umana, Sruthi Ranganathan, Salvatore Marrone, Jessica Naimo, Matteo Giunta, Angelo Spitaleri, Marco Fricia, Gianluca Ferini, Gianluca Scalia

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Green logistics optimization for coal supply in a power plant connecting maritime port by Mingsheng Qiu, Liping Gao, Zhouyong Lin, Minghong Zheng, Qingzhong Lin

“…This paper introduces an integrated optimization model grounded in green logistics and employs an Improved Particle Swarm Optimization (IPSO) algorithm to efficiently manage the coal supply chain from unloading at ports to loading into generators. …”
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Throughput-Delay Trade-Off for Cognitive Radio Networks: A Convex Optimization Perspective by Hang Hu, Hang Zhang, Hong Yu

“…It is proved that the maximum achievable throughput and the minimum transmission delay cannot be obtained simultaneously. An efficient algorithm is proposed to optimize the sensing bandwidth and the final decision threshold jointly such that the throughput is maximized while the delay is constrained. …”
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Coordinated Optimal Dispatch of Distribution Grids and P2P Energy Trading Markets by Jing Deng, Fawu He, Qingbin Zeng, Jie Yan, Rangxiong Liu, Dongsheng He, Song Zhou

“…To address the nonlinear, high‐dimensional optimization challenges, an improved Convex‐Soft Actor‐Critic (C‐SAC) algorithm is developed, combining deep reinforcement learning with convex optimization to achieve privacy‐preserving distributed coordination. …”
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Metamodel-Based Optimization Method for Traffic Network Signal Design under Stochastic Demand by Wei Huang, Xuanyu Zhang, Haofan Cheng, Jiemin Xie

“…A gradient-based metamodel algorithm is then proposed. In the numerical example, a six-node test network is used to examine the proposed metamodel-based optimization method. …”
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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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Bayesian Optimized GridDehazeNet for Adaptive Haze Removal in Real-World Applications by Sungkwan Youm

“…By employing our algorithm, we effectively identify the best architectural parameters, achieving higher Peak Signal-to-Noise Ratio (PSNR) and Structural Similarity Index Measure (SSIM) compared to models without this optimization. …”
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Chiến lược tối ưu đa mục tiêu nhằm tăng cường hiệu suất hệ thống điện phân phối khi tích hợp nguồn điện phân tán by Tôn Ngọc Triều, Lê Minh Phong, Lê Minh Tân

“…Thuật toán Raccoon Optimization Algorithm (ROA) là một phương pháp tối ưu meta-heuristic mới, được áp dụng và đối chiếu với các thuật toán như Firefly Algorithm (FA), Moth Flame Optimization (MFO), Salp Swarm Algorithm (SSA), và Whale Optimization Algorithm (WOA). …”
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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.…”
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Structural Optimization and Experimental Validation of a Composite Engine Mount Designed for VTOL UAV by Milica Milić, Jelena Svorcan, Toni Ivanov, Ivana Atanasovska, Dejan Momčilović, Željko Flajs, Boško Rašuo

“…This paper presents the optimization of one of the vital aircraft parts, the composite engine mount, based on the genetic algorithm (GA) combined with the defined finite element (FE) parameterized model. …”
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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. …”
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An Optimized FPGA-Based FDIR System for Sensor Fault Detection in Satellite Attitude Estimation by Xianliang Chen, Zhicheng Xie, Jiashu Wu, Xiaofeng Wu

“…This paper addresses these challenges by optimizing FDIR hardware implementation through reshaping, parallelism, and pipelining to reduce computational load and latency while enhancing efficiency and processing speed. …”
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Secure ISAC MIMO systems: exploiting interference with Bayesian Cramér–Rao bound optimization by Nanchi Su, Fan Liu, Christos Masouros, George C. Alexandropoulos, Yifeng Xiong, Qinyu Zhang

“…In particular, assuming that the distribution of each parameter to be estimated is known a priori, we focus on optimizing the targets’ sensing performance. To this end, we derive and minimize the Bayesian Cramér–Rao bound, while ensuring certain communication quality of service by exploiting constructive interference. …”
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An analytical optimal calibration framework of bonded particle model for rock strength envelop modelling by Xiaoxiong Zhou, Hongyi Xu, Qiuming Gong, Yanan Ma, Weiqiang Xie

“…Adaptive moment estimation (Adam) was chosen as the iterative optimization algorithm to avoid the vanishing gradient problem. …”
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