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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Multi-objective Optimization Design of Component Cooling System in HPR1000 by ZHAO Weiguang1, 2, YU Pei1, 3, ZENG Xiaobo1, 2, FAN Guangming1, 2, YAN Changqi1, 2

“…Each variable possesses a specific range of values, which is critical for the optimization process. The theoretical model and the final optimization results demonstrate that the proposed evaluation model and optimization algorithm effectively assess the RRI’s performance in multi-objective optimization calculations, allowing for a substantial degree of RRI optimization. …”
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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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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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Optimizing Distribution Grid Performance through Electric Vehicle Integration and Stochastic Modeling in Extreme Weather Conditions by A. Niknami, M. Askari, M. Amirahmadi, M. Babaeinik

“…Monte Carlo simulation is employed to model uncertainties, while a multi-objective optimization algorithm is used to solve the problem. …”
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Improving the efficiency and security of passport control processes at airports by using the R-CNN object detection model by Elhoucine Ouassam, Yassine Dabachine, Nabil Hmina, Belaid Bouikhalene

“… The use of real-time machine learning to optimize passport control procedures at airports can greatly improve both the efficiency and security of the processes. …”
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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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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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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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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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An enhanced moth flame optimization extreme learning machines hybrid model for predicting CO2 emissions by Ahmed Ramdan Almaqtouf Algwil, Wagdi M. S. Khalifa

“…The model integrates the Gaussian mutation and shrink mechanism-based moth flame optimization (GMSMFO) algorithm with an extreme learning machine (ELM). …”
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Optimization of State Clustering and Safety Verification in Deep Reinforcement Learning Using KMeans++ and Probabilistic Model Checking by Ryeonggu Kwon, Gihwon Kwon

“…Counterexample analysis identifies critical failure paths, offering actionable insights for policy improvement. Experimental results demonstrate that the optimal number of clusters balances state space reduction with accurate failure analysis, enabling scalable verification. …”
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