YOLOv8-OCHD: A Lightweight Wood Surface Defect Detection Method Based on Improved YOLOv8 by Zuxing Chen, Junjie Feng, Xueyan Zhu, Bin Wang

“…This effectively reduces the difficulty and cost of deployment on mobile terminals while significantly improving algorithm accuracy, meeting real-time requirements, and providing a more efficient and feasible technical solution for relevant applications. …”
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Multi-Agent Deep Reinforcement Learning for Scheduling of Energy Storage System in Microgrids by Sang-Woo Jung, Yoon-Young An, BeomKyu Suh, YongBeom Park, Jian Kim, Ki-Il Kim

“…To defeat the above issues, in this paper, we propose a new DRL-based scheduling algorithm using a multi-agent proximal policy optimization (MAPPO) framework that is combined with Pareto optimization. …”
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Methods for Improving Point Cloud Authenticity in LiDAR Simulation for Autonomous Driving: A Review by Yanzhao Yang, Jian Wang, Xinyu Guo, Xinyu Yang, Wei Qin

“…It also proposes future directions to bridge the gap between simulated and real-world data, aiming to optimize hybrid training models for improved autonomous driving applications.…”
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A Novel NSGA-III-GKM++ Framework for Multi-Objective Cloud Resource Brokerage Optimization by Ahmed Yosreddin Samti, Ines Ben Jaafar, Issam Nouaouri, Patrick Hirsch

“…This paper presents NSGA-III-GKM++, an advanced multi-objective optimization model that integrates the NSGA-III evolutionary algorithm with an enhanced K-means++ clustering technique to improve the convergence speed, solution diversity, and computational efficiency. …”
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Optimal Configuration of ESS in Distribution Network Considering Generation of PV-Load Time Series Scenarios by Xiaolong Xiao, Mingming Shi, Fan Wu, Yukai Wei, Bo Zhao, Fang Zhang

“…A distribution network ESS configuration model is constructed with the objectives of minimizing voltage fluctuation indicator, line loss rate, and minimizing ESS investment cost. To solve the high-dimensional multi-objective functions in the model, an non-dominated sorting genetic algorithm-III (NSGA-III) was employed, and the optimal solution is selected by using the entropy weight method (EWM). …”
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Maritime Port Freight Flow Optimization with Underground Container Logistics Systems Under Demand Uncertainty by Miaomiao Sun, Chengji Liang, Yu Wang, Salvatore Antonio Biancardo

“…The model is solved using a hybrid algorithm combining an improved Genetic Algorithm and Simulated Annealing (GA-SA) with Deep Q-Learning (DQN). …”
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Deep reinforcement learning-based resource joint optimization for millimeter-wave massive MIMO systems by LIU Qingli, LI Xiaoyu, LI Rui

“…Experimental results show that the proposed joint optimization method significantly improves the throughput and energy efficiency of the system compared with the single-stage all-digital precoding and hybrid precoding equal resource allocation methods and the particle swarm optimization-based resource allocation algorithm.…”
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Integration of Regression-Based Guidance Ant for Enhanced Exploration and Convergence in Ant Colony Optimization (ACO) by Desi W. Sari, Suci Dwijayanti, Bhakti Y. Suprapto

“…To address these limitations, this research incorporates a linear regression line as a directional guide for ants, helping them navigate toward the optimal path more efficiently. This paper presents an improved Ant Colony Optimization (I-ACO) algorithm by integrating regression-based guidance to enhance both exploration and convergence. …”
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Joint Optimization of Multienergy Virtual Power Plant Configuration and Operation Considering Electric Vehicle Access by Xianqiang Zeng, Chuangwei Xu, Tengfei Wei

“…Based on the gazelle algorithm and mixed integer linear programming (MILP), the capacity and output of the system energy equipment are jointly optimized, and the running curve of MEVPP in a typical quarter is analyzed. …”
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Toward Robust GNSS Real-Time Orbit Determination for Microsatellites Using Factor Graph Optimization by Cong Hou, Xiaojun Jin, Xiaopeng Yang, Tong Xiao

“…However, the performance of EKF-RTOD is markedly degraded when the microsatellite deviates from a stable Earth-pointing attitude and employs a low-cost receiver. Factor graph optimization (FGO), which addresses nonlinear problems through multiple iterations and re-linearization, has demonstrated superior accuracy and robustness compared to EKF in challenging environments such as urban canyons. …”
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UV-Vis spectroscopy coupled with firefly algorithm-enhanced artificial neural networks for the determination of propranolol, rosuvastatin, and valsartan in ternary mixtures by Ahmed Serag, Maram H. Abduljabbar, Yusuf S. Althobaiti, Farooq M. Almutairi, Shaker T. Alsharif, Rami M. Alzhrani, Marwa F. Ahmed, Atiah H. Almalki

“…An experimental design of 25 samples was employed as a calibration set, and a central composite design of 20 samples was used as a validation set. The firefly algorithm (FA) was evaluated as a variable selection procedure to optimize the developed ANN models resulting in simpler models with improved predictive performance as evident by lower relative root mean square error of prediction (RRMSEP) values compared to the full spectrum ANN models. …”
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Research on the Operation Optimization of Public Building Systems in Extremely Cold Areas Based on Flexible Loads by Chuan Tian, Shunli Jiang, Shuai Li, Guohui Feng, Bin Yu

“…A two-stage operation optimization method is proposed: the first stage simulates the starting and stopping control conditions of equipment at varying temperatures and times, selecting the optimal time period to regulate the thermal loads; the second stage employs a multi-objective particle swarm optimization algorithm to optimize the scheduling of the system’s electrical load. …”
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Stable matching-enhanced MOEA/D for solving multi-objective optimal power flow problems by Ebrahim Akbari, Amin Khodabakhshian, Abolfazl Rahimnejad, Stephen Andrew Gadsden

“…The proposed method ensures a balanced and effective trade-off between solution accuracy and diversity in multi-objective optimization. Comparative evaluations against well-established algorithms demonstrate the superior performance of the proposed approach in approximating the Pareto front, improving computational efficiency, and maintaining solution diversity. …”
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Rolling optimization method of virtual power plant demand response based on Bayesian Stackelberg game by Binxi Huang

“…This is iteratively solved using the whale algorithm to determine the optimal power generation distribution scheme for each unit on both the supply side and demand sides. …”
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Inter-Satellite Handover Method Based Multi-Objective Optimization in Satellite-Terrestrial Integrated Network by Renpeng LIU, Bo HU, Hequn LI

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An improved permeability estimation model using integrated approach of hybrid machine learning technique and Shapley additive explanation by Christopher N. Mkono, Chuanbo Shen, Alvin K. Mulashani, Patrice Nyangi

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Artificial Intelligence to Analyze the Performance of the Ceramic-Coated Diesel Engine Using Digital Filter Optimization by P. Nirmala, G. Ramkumar, Satyajeet Sahoo, G. Anitha, S. Ramesh, S. Agnes Shifani, Agegnehu Shara Shata

“…PSO-GA (Particle Swarm Optimization and Genetic Algorithm) is utilized to analyze the performance. …”
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Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue by Chongde CHEN, Qiang GUO, Ziqiu SONG, Yang HU

“…The wind power offset was decomposed by a Butterworth low-pass filter, and the low-frequency and high-frequency components were used as the reference power of lithium battery energy storage and flywheel energy storage, respectively. In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. …”
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Flexibility Resource Planning and Stability Optimization Methods for Power Systems with High Penetration of Renewable Energy by Haiteng Han, Xiangchen Jiang, Yang Cao, Xuanyao Luo, Sheng Liu, Bei Yang

“…Furthermore, to mitigate the uncertainty and fault risks associated with extreme weather events, a CVaR-based risk quantification framework is incorporated into a bi-level optimization model, effectively balancing investment costs and operational risks under uncertainty. …”
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Optimized Software Implementation of Keccak, Kyber, and Dilithium on RV{32,64}IM{B}{V} by Jipeng Zhang, Yuxing Yan, Junhao Huang, Çetin Kaya Koç

“… With the standardization of NIST post-quantum cryptographic (PQC) schemes, optimizing these PQC schemes across various platforms presents significant research value. …”
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