Adaptive Virtual Inertia and Voltage Estimation: Enabled Model Predictive Control for Improved Performance in Islanded DC Microgrids by Salisu Abdullahi, Khaled Eltag, Lei Weining, Chen Xiaohu

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Fractional Order Accumulation NGM (1, 1, k) Model with Optimized Background Value and Its Application by Jun Zhang, Yanping Qin, Xinyu Zhang, Bing Wang, Dongxue Su, Huaqiong Duo

“…The particle swarm optimization algorithm is used to estimate the parameters of the proposed model. …”
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Dynamic Environmental Economic Dispatch Considering the Uncertainty and Correlation of Photovoltaic–Wind Joint Power by Yi Ru, Ying Wang, Weijun Mao, Di Zheng, Wenqian Fang

“…Furthermore, when compared to other optimization algorithms, the improved adaptive multi-objective fireworks algorithm proves to be more efficient in addressing the dynamic environmental economic dispatch challenges within the power system.…”
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Research on highway road condition intelligent assessment and optimization system based on deep learning and internet of things by Tingquan He, Changhai Wang, Riyan Lan, Haiyu Luo

“…Experimental verification shows that the model significantly improves prediction performance. …”
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Integrating GIS, 3D-Isovist, and an NSGA-II multi-objective optimization algorithm for automation of design process in urban parks and public open spaces by Karim Zandniapour, Akram Soroush, Ehsan Khezerlu Agdam, Haniyeh Sanaieian

“…The results showed that the NSGA-II was able to solve the complex design problem with 185 trees and 66 observers. The algorithm produced a Pareto-frontier consisting of four optimal solutions that, compared to the existing state of the park, showed more than 18% and 12 % improvement according to Tree View and Building View, respectively. …”
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Optimization of extraction in supercritical fluids in obtaining Pouteria lucuma seed oil by response surface methodology and artificial neuronal network coupled with a genetic algo... by Alex Chauca-Cerrutti, Marianela Inga, José Luis Pasquel-Reátegui, Indira Betalleluz-Pallardel, Gustavo Puma-Isuiza

“…LS was previously characterized, and the extraction parameters were optimized using a Box-Behnken design, considering temperature (40–60°C), pressure (100–300 bar), and CO2 flow rate (3–7 mL/min), applying the response surface methodology (RSM) and neural networks with genetic algorithm (ANN+GA). …”
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A Discrete Brain Storm Optimization Algorithm for Hybrid Flowshop Scheduling Problems with Batch Production at Last Stage in the Steelmaking-Refining-Continuous Casting Process by Kunkun Peng, Chunjiang Zhang, Weiming Shen, Xinfu Pang, Yanlan Mei, Xudong Deng

“…In this paper, a Discrete Brain Storm Optimization (DBSO) algorithm is proposed to handle SRCC scheduling problems. …”
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Optimal energy management of distributed generation resources in a microgrid under various load and solar irradiance conditions using the artificial bee colony algorithm by Tareq Hamadneh, Omar Alsayyed, Belal Batiha, El Manaa Barhoumi, Mehrdad Ahmadi Kamarposhti, Hassan Haghighi, Phatiphat Thounthong, Ilhami Colak

“…The results demonstrate that the proposed algorithm consistently achieves superior performance in minimizing the total operation cost compared to traditional bio-inspired optimization techniques such as genetic algorithms, particle swarm optimization, and a modified bat algorithm. …”
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Real-Time Optimization of Discrete Element Models for Studying Asphalt Mixture Compaction Characteristics at the Meso-Scale by Xue Wang, Zifang Wang, Xuanye Luo

“…After calibration, particle rotation in the optimized DEM model more closely matched the laboratory SmartKli sensing data. …”
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RIME optimization with dynamic multi-dimensional random mechanism and Nelder–Mead simplex for photovoltaic parameter estimation by Yuanping Zheng, Fangjun Kuang, Ali Asghar Heidari, Lipei Yuan, Siyang Zhang, Huiling Chen

“…Abstract Solar photovoltaic technology is efficient and clean, but extracting photovoltaic cell parameters is challenging due to various influencing factors. The rime optimization algorithm (RIME) is a recently proposed metaheuristic algorithm (MAs). …”
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Soybean Yield Estimation Using Improved Deep Learning Models With Integrated Multisource and Multitemporal Remote Sensing Data by Jian Li, Junrui Kang, Ji Qi, Jian Lu, Hongkun Fu, Baoqi Liu, Xinglei Lin, Jiawei Zhao, Hengxu Guan, Jing Chang, Zhihan Liu

“…Empirical analyses showed that TransBiHGRU-PSO demonstrated improved estimation capability and generalizability compared to multiple benchmark models. …”
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An improved MP-NMO correction method based on multiparameter fitting and its application by Xiaohui YANG, Pengfei YU, Jiawei ZHANG

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Optimization Model of Time-of-Use Electricity Pricing Considering Dynamical Time Delay of Demand-Side Response by Yanru Ma, Pingping Wang, Dengshan Hou, Yue Yu, Shenghu Li, Tao Gao

“…An improved non-dominated sorting genetic algorithm (NSGA-II) is applied to find the Pareto front solution and obtain the optimal price of the TOU. …”
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A CCP-Based Decentralized Optimization Approach for Electricity–Heat Integrated Energy Systems with Buildings by Xiangyu Zhai, Xuexue Qin, Jiahui Zhang, Xiaoyang Liu, Xiang Bai, Song Zhang, Zhenfei Ma, Zening Li

“…To address the disadvantages of high computational complexity and poor information privacy in centralized optimization, an accelerated asynchronous decentralized alternating direction method of multipliers (A-AD-ADMM) algorithm is proposed, which decomposes the original optimization problem into sub-problems of ES and TS for distributed solving, significantly improving solution efficiency. …”
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Parameter Sensitivity Analysis and Irrigation Regime Optimization for Jujube Trees in Arid Regions Using the WOFOST Model by Shihao Sun, Yingjie Ma, Pengrui Ai, Ming Hong, Zhenghu Ma

“…The subsequent multi-objective optimization of yield and crop water productivity of dates under different combinations of water and potassium treatments under a bi-objective optimization model based on the NSGA-II algorithm showed that the optimal strategy was irrigation at 80% ET_c combined with 300 kg/ha of potassium application. …”
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Cross-social-network user alignment research based on multi-dimensional user features by Tao Zhao, Heng Gao, Zecheng Wang, Dianjie Bi, Xuemin Chen

“…This method improves the performance of traditional particle swarm optimization algorithms. …”
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Short-Term Prediction of Ship Heave Motion Using a PSO-Optimized CNN-LSTM Model by Guowei Li, Gang Tang, Jingyu Zhang, Qun Sun, Xiangjun Liu

“…The PSO algorithm is then employed to optimize the network structure and hyperparameters of the convolutional neural network. …”
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Heating, Ventilation, and Air Conditioning (HVAC) Temperature and Humidity Control Optimization Based on Large Language Models (LLMs) by Xuanrong Zhu, Hui Li

“…Simulated experimental results demonstrate that the improved control strategy, optimized through LLM-enhanced Model Predictive Control (MPC), significantly enhances the energy efficiency and stability of HVAC system control. …”
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A multi-task genetic programming approach for online multi-objective container placement in heterogeneous cluster by Ruochen Liu, Haoyuan Lv, Ping Yang, Rongfang Wang

“…MOCP-MTGP can automatically generate multiple groups of allocation rules from historical workload patterns and different cluster states, and capture the similarities between all online tasks to guide the transfer of general knowledge during optimization. Comprehensive experiments show that the proposed algorithm can improve the resource utilization of clusters, reduce the number of physical machines, and effectively meet resource constraints and high availability requirements.…”
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P4CN-YOLOv5s: a passion fruit pests detection method based on lightweight-improved YOLOv5s by Zhiping Tan, Zhiping Tan, Dapeng Ye, Jiancong Wang, Wenxiang Wang

“…Secondly, after analyzing the image set characteristics to be detected in this research, the point-line distance bounding box loss function is utilized to calculate the coordinate distance of the prediction box and target box, and aimed at improving detection speed. Subsequently, a convolutional block attention module (CBAM) and optimized anchor boxes are employed to reduce the false detection rate of the model. …”
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