Co-Optimization of Market and Grid Stability in High-Penetration Renewable Distribution Systems with Multi-Agent by Dongli Jia, Zhaoying Ren, Keyan Liu

“…The methodological innovations primarily include an enhanced scheduling algorithm for coordinated optimization of renewable energy and energy storage, and a dynamic coordinated optimization method for EV clusters. …”
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Optimization design of combustion chamber for a non-road diesel engine in high-altitude region by Yibing Hou, Jun Wang, Jilin Lei, Liang Chen

“…Subsequently, a Latin hypercube sampling (LHS) approach was employed for experimental design, and a back-propagation (BP) neural network was utilized to develop a surrogate model. Finally, the non-dominated sorting genetic algorithm II (NSGA-II) was employed to perform multi-objective optimization, and the technique for order preference by similarity to ideal solution (TOPSIS) was utilized to select the optimal combustion chamber structural parameters suitable for high-altitude regions. …”
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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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Application research of convolutional neural network and its optimization in lightning electric field waveform recognition by Caixia Wang, Xiaoyi Zhang, Hui Yang, Jinyuan Guo, Jia Xu, Zhuling Sun

“…In this paper, based on the electric field observation of the Beijing lightning location website of the Institute of Atmospheric Physics, Chinese Academy of Sciences, a recognition and classification method of pulse signal waveform based on Convolutional Neural Network(CNN) algorithm is designed and implemented. The CNN network model and its parameters were optimized from three aspects: dataset, model parameters, and network structure, achieving a recognition rate of over 90%. …”
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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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Lithium-Ion Battery State of Health Estimation Based on CNN-LSTM-Attention-FVIM Algorithm and Fusion of Multiple Health Features by Guoju Liu, Zhihui Deng, Yonghong Xu, Lianfeng Lai, Guoqing Gong, Liang Tong, Hongguang Zhang, Yiyang Li, Minghui Gong, Mengxiang Yan, Zheng Ye

“…This paper proposes a novel SOH predication method by combing the four-vector intelligent metaheuristic (FVIM) with the CNN-LSTM-Attention basic model. The model adopts the collaborative architecture of a convolutional neural network and time series module, strengthens the cross-level feature interaction by introducing a multi-level attention mechanism, then uses the FVIM optimization algorithm to optimize the key parameters to realize the overall model architecture. …”
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Fine-Grained Classification of Pressure Ulcers and Incontinence-Associated Dermatitis Using Multimodal Deep Learning: Algorithm Development and Validation Study by Alexander Brehmer, Constantin Seibold, Jan Egger, Khalid Majjouti, Michaela Tapp-Herrenbrück, Hannah Pinnekamp, Vanessa Priester, Michael Aleithe, Uli Fischer, Bernadette Hosters, Jens Kleesiek

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Exploring Machine Learning Models for Vault Safety in ICL Implantation: A Comparative Analysis of Regression and Classification Models by Qing Zhang, Qi Li, Zhilong Yu, Ruibo Yang, Emmanuel Eric Pazo, Yue Huang, Hui Liu, Chen Zhang, Salissou Moutari, Shaozhen Zhao

“…Regression and classification models were developed using gradient boosting, random forest, and CatBoost algorithms. …”
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Multi-layer Embedded Optimization of Microgrid Capacity Considering Price and Incentive/Compensation Coupling Mechanism by Xianhui ZHU, Xu HU, Nan SHI, Yao ZHANG, Jingwen ZHONG

“…Finally, the optimization models of both the source and load are coupled through the multi-layer embedded mechanism, and a solution model is constructed, which combines the multi-objective particle swarm optimization (MOPSO) algorithm and the particle swarm optimization–imperial competition algorithm (PSO-ICA). …”
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Distributed Risk-Averse Optimization Scheduling of Hybrid Energy System with Complementary Renewable Energy Generation by Yanbo Jia, Bingqing Xia, Zhaohui Shi, Wei Chen, Lei Zhang

“…A risk-averse operation optimization model is proposed using conditional value at risk to quantify the uncertainty of renewable energy generation. …”
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A Novel RMS-Driven Deep Reinforcement Learning for Optimized Portfolio Management in Stock Trading by Asma Sattar, Amna Sarwar, Saira Gillani, Maryam Bukhari, Seungmin Rho, Muhammad Faseeh

“…This study proposed an improved stock market trading framework termed the RMS-Driven Deep Reinforcement Learning (DRL) model for optimal portfolio management. …”
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Research on the role of multi-sensor system information fusion in improving hardware control accuracy of intelligent system by Li Xin, Li Yuesong

“…According to the key frames saved in the previous steps, feature points in local maps, sensor information, and loop information, a global optimization algorithm based on graph optimization model is constructed to optimize the position and pose of intelligent hardware system and the position of spatial feature points. …”
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A GIS-based integrative approach for land use optimization in a semi-arid watershed by S.M. Tajbakhsh, H. Memarian, A. Kheyrkhah

“…In line with the management of natural resources, land use optimization can be highly useful. The aim of the present study is to propose an appropriate integrative model for optimized allocation of lands for surface runoff and sediment load minimization and net income maximization in Bayg watershed, Iran. …”
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Shield tunneling efficiency and stability enhancement based on interpretable machine learning and multi-objective optimization by Wenli Liu, Yang Chen, Tianxiang Liu, Wen Liu, Jue Li, Yangyang Chen

“…On this basis, a multi-objective intelligent optimization model is established to solve the optimized operating parameters of shield machine by non-dominated sorting genetic algorithm II and technique for order preference by similarity to ideal solution to reduce GS and improve drilling efficiency. …”
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Student dropout prediction through machine learning optimization: insights from moodle log data by Markson Rebelo Marcolino, Thiago Reis Porto, Tiago Thompsen Primo, Rafael Targino, Vinicius Ramos, Emanuel Marques Queiroga, Roberto Munoz, Cristian Cechinel

“…The proposed model trained with all weeks’ data demonstrated superior performance, showing significant improvements in F1-scores and recall, particularly for the minority class of at-risk students. …”
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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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Performance optimization of active RIS-assisted near-shore dual-function radar communicaiton system by XU Miao, YUE Dianwu, SUN Yu, WU Xiangkai, YUAN Meng

“…An alternating optimization algorithm based on fractional programming theory and the Lagrangian operator method was proposed. …”
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Wear analysis and optimization of nanoclay and copper coated carbon fiber strengthened hybrid aluminium composite by N. Senthilkumar, K. Gajalakshmi, K. Palanikumar, B. Deepanraj, Abdul Rahman Afzal

“…The adopted metaheuristic nature-inspired evaporation rate-based water cycle algorithm yields identical results and quickly converges to optimal conditions, resulting in a combined objective function of 157.67.…”
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UAV-based multitier feature selection improves nitrogen content estimation in arid-region cotton by Fengxiu Li, Fengxiu Li, Chongqi Zhao, Chongqi Zhao, Yingjie Ma, Yingjie Ma, Ning Lv, Yanzhao Guo, Yanzhao Guo

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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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