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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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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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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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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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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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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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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Metaparameter optimized hybrid deep learning model for next generation cybersecurity in software defined networking environment by C. Labesh Kumar, Suresh Betam, Denis Pustokhin, E. Laxmi Lydia, Kanchan Bala, Rajanikanth Aluvalu, Bhawani Sankar Panigrahi

“…For the DDoS attack classification process, the attention mechanism with convolutional neural network and bidirectional gated recurrent units (CNN-BiGRU-AM) is employed. To ensure optimal performance of the CNN-BiGRU-AM model, hyperparameter tuning is performed by utilizing the seagull optimization algorithm (SOA) model to enhance the efficiency and robustness of the detection system. …”
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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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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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Optimal Fuzzy Deep Neural Networks-Based Plant Disease Detection and Classification on UAV-Based Remote Sensed Data by M. Pajany, S. Venkatraman, U. Sakthi, M. Sujatha, Mohamad Khairi Ishak

“…Moreover, this model’s scalability and efficiency improve its value for precision agriculture, optimizing resource usage and promoting sustainable farming practices. …”
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Blockchain enabled deep learning model with modified coati optimization for sustainable healthcare disease detection and classification by Heba G. Mohamed, Fadwa Alrowais, Fahd N. Al-Wesabi, Mesfer Al Duhayyim, Anwer Mustafa Hilal, Abdelwahed Motwakel

“…For the optimal subset of features, the spotted hyena optimization algorithm (SHOA) model is used. …”
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Improved FraSegNet-Based Rock Nodule Identification Method and Application by Yanbo Zhang, Guanghan Zhang, Qun Li, Xulong Yao, Hao Zhou

“…The algorithm was validated with the Barton–Bandis model and Hoek–Brown criterion. …”
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A Hybrid Approach Incorporating WSO-HO and the Newton-Raphson Method to Enhancing Photovoltaic Solar Model Parameters Optimisation by Jeridi Ahmed, Moulahi Mohamed Hedi, Khaterchi Hechmi, Zaafouri Abderrahmen

“…This study introduces a novel hybrid approach, WSO-HO, which integrates the strengths of the war strategy optimization (WSO) and Hippopotamus Optimization (HO) algorithms, enhanced by the Newton-Raphson (NR) method, to achieve precise parameter estimation for PV models. …”
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Enhanced detection of accounting fraud using a CNN-LSTM-Attention model optimized by Sparrow search by Peifeng Wu, Yaqiang Chen

“…This paper proposes an enhanced approach to fraud detection by integrating convolutional neural networks (CNN) and long short-term memory (LSTM) networks, complemented by an attention mechanism to prioritize relevant features. To further improve the model’s performance, the sparrow search algorithm (SSA) is employed for parameter optimization, ensuring the best configuration of the CNN-LSTM-Attention framework. …”
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Deep Reinforcement Learning Algorithm Based on Graph Weight Multi-Pointer Network for Solving Multiobjective Traveling Salesman Problem by Xiaoyu Fu, Shenshen Gu

“…To this end, this paper proposes a deep reinforcement learning algorithm based on graph weight multi-pointer network (GWMPN), which only needs to perform forward propagation on the GWMPN model to obtain the solution of MOTSP, thus significantly improving the solution efficiency. …”
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A Graphite Ore Grade Recognition Method Based on Improved Inception-ResNet-v2 Model by Xueyu Huang, Renjie Pan, Jionghui Wang

“…Key improvements include: 1) To enhance the extraction of global feature information from graphite mine data, a global average pooling branch is incorporated into the Inception-resnet architecture. 2) Incorporating a <inline-formula> <tex-math notation="LaTeX">$1\times 1$ </tex-math></inline-formula> convolutional layer at the tail of the model to control channel dimensions and employing the LeakyReLU activation function to address the limitations of the ReLU activation function. 3) Designing an LDP-Conv structure to replace certain <inline-formula> <tex-math notation="LaTeX">$3\times 3$ </tex-math></inline-formula> convolutions and incorporating a channel attention mechanism to improve feature capture. 4) Optimizing the Stem module to expand the early-stage receptive field and reconstructing the network architecture. …”
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