An integrated optimization model of network behavior victimization identification based on association rule feature extraction by Shengli ZHOU, Linqi RUAN, Rui XU, Xikang ZHANG, Quanzhe ZHAO, Yuanbo LIAN

“…The identification of the risk of network behavior victimization was of great significance for the prevention and warning of telecom network fraud.Insufficient mining of network behavior features and difficulty in determining relationships, an integrated optimization model for network behavior victimization identification based on association rule feature extraction was proposed.The interactive traffic data packets generated when users accessed websites were captured by the model, and the implicit and explicit behavior features in network traffic were extracted.Then, the association rules between features were mined, and the feature sequences were reconstructed using the FP-Growth algorithm.Finally, an analysis model of telecom network fraud victimization based on network traffic analysis was established, combined with the stochastic forest algorithm of particle swarm optimization.The experiments show that compared with general binary classification models, the proposed model has better precision and recall rates and can effectively improve the accuracy of network fraud victimization identification.…”
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Algorithm for Dynamic Reactive Power Optimization of Regional Power Grid Based on Interior Point Method and Neighborhood Search Decoupling Dynamic Programming Method by Jie ZHANG, Hengfeng WANG, Shengchun LIU, Huabiao WANG, Canghai WANG, Yao RAN, Xianmin WANG, Yongfei MA, Wei YAN

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An Efficient Optimal CapsNet Model-Based Computer-Aided Diagnosis for Gastrointestinal Cancer Classification by Fahdah A Almarshad, Prasanalakshmi Balaji, Liyakathunisa Syed, Eman Aljohani, Santhi Muttipoll Dharmarajlu, Thavavel Vaiyapuri, Nourah Ali AlAseem

“…With this inspiration, this study presents a new snake optimization algorithm with a DL-assisted GC classification (SOADL-GCC) approach. …”
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The Spatial Distribution and Driving Mechanism of Soil Organic Matter in Hilly Basin Areas Based on Genetic Algorithm Variable Combination Optimization and Shapley Additive Explana... by He Huang, Yaolin Liu, Yanfang Liu, Zhaomin Tong, Zhouqiao Ren, Yifan Xie

“…Based on the genetic algorithm, 47 environmental variables are combined and optimized to construct a random forest (RF) model and an improved version—a random forest model based on genetic algorithm variable combination optimization (RF-GA). …”
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Non-destructive detection of early wheat germination via deep learning-optimized terahertz imaging by Guangming Li, Hongyi Ge, Yuying Jiang, Yuan Zhang, Xi Jin

“…Subsequently, we introduce the EfficientViT-based YOLO V8 classification model, incorporating a Depthwise Separable Attention (C2F-DSA) module, and further optimize the model using the Gazelle Optimization Algorithm (GOA). …”
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Managing Risk Across Time: An Intertemporal Spectral Risk Measures Framework for Multi-Period Portfolio Optimization by Chengneng Jin, Jianjun Gao

“…This paper introduces a novel framework for multi-period portfolio optimization that incorporates intertemporal spectral risk measures (ISRMs). …”
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Algorithm of passive “Beidou”/INS closed-loop integrated using two level filter by GAO Fa-qin, TAN Zhan-zhong

“…One scheme of integrated navigation Kalman filter positioning algorithm was put forward to apply to “Beidou” and INS（intertial navigation system）.Using the pseudo-range’s velocity of changing as observations,on the basis of the high stable clock,a closed loop Kalman filtering model that can revise the attitude error of INS was put out,its biggest optimism was that it could change between the close-loop method and open-loop method steadily.Finally,by computer simulation,it explain that our scheme improve the positioning precision effectively when the satellites in sight are less then two ones,and it also show that our scheme can revise the attitude error of INS effectively and estimate the user’s velocity in high precision.…”
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Application of deep learning algorithm for judicious use of anti-VEGF in diabetic macular edema by Anwesa Mondal, Apurba Nandi, Subhasish Pramanik, Lakshmi Kanta Mondal

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MSKT: multimodal data fusion for improved nursing management in hemorrhagic stroke by Ting Zhou, Dandan Li, Jingfang Zuo, Aihua Gu, Li Zhao

“…Results The proposed MSKT-NSGP model outperformed traditional algorithms in prediction accuracy, computational efficiency, and uncertainty handling. …”
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Multitask allocation model of the coal foreign object sorting robot based on optimal capacity and benefit by Wu Xudong, Cao Xiangang, Ding Wentao, Wang Peng, Zhang Ye, Liu Jiahui

“…Firstly, this paper constructs a multi-task allocation model of coal foreign object sorting robot (CFoSR) based on optimal capacity and benefit. …”
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Enhancing Education with Machine Learning: Predicting Student Readability Scores by Claire Bell

“…This study explores the use of machine learning techniques to predict students' reading scores, with a particular focus on Random Forest Classification (RFC) as a reliable baseline model. The research leverages a dataset of 1,000 English texts to evaluate and compare the performance of RFC, the Sooty Tern Optimization Algorithm (STOA), and the Gold Rush Optimizer (GRO) in predicting readability ratings. …”
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Quantum-enhanced beetle swarm optimized ELM for high-dimensional smart grid intrusion detection by Na Cheng, Shuqing Wang, Lihong Zhao, Yan Hu

“…Abstract This study proposes a novel smart grid intrusion detection model, combining a quantum-enhanced beetle swarm optimization algorithm with extreme learning machine (QBOA-ELM), with the aim of improving detection accuracy, efficiency, and robustness. …”
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A Hybrid Fault Diagnosis Model for Rolling Bearing With Optimized VMD and Fuzzy Dispersion Entropy by Xin Xia, Xiaolu Wang, Weilin Chen

“…Firstly, a parameter optimization method using the sparrow search algorithm (SSA) was applied to VMD to improve the decomposition ability. …”
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Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang, He Fan

“…This algorithm is subsequently deployed to optimize hyperparameters within the redesigned predictive architecture. …”
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An Operation Plan Optimization Model for Integrated Customized and Conventional Bus Services Based on Cost Analysis by Xi Lu, Junru Han, Peng Xu, Haode Liu, Xumei Chen

“…A mixed-integer planning model and a hybrid genetic algorithm are used to optimize the operation plan for specific travel demands and supply capacities. …”
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YOLO-LSM: A Lightweight UAV Target Detection Algorithm Based on Shallow and Multiscale Information Learning by Chenxing Wu, Changlong Cai, Feng Xiao, Jiahao Wang, Yulin Guo, Longhui Ma

“…Focaler inner IoU is incorporated to improve bounding box matching and localization, thereby accelerating model convergence. …”
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Autonomous UAV Path Optimization Using Genetic and Multiobjective Evolutionary Algorithms for Effective Data Retrieval in Cache-Enabled Mobile Ad-Hoc WSNs by Umair B. Chaudhry, Chris Ian Phillips

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Hierarchical optimal control of virtual power plants for source-network-load-storage by Zhaoze LI, Jihong ZHANG, Zhenkui WU, Zilei ZHANG, Qingsong HE

“…This shall be combined with generalized energy storage to achieve balance between power supply and power demand, especially the Sinh Cosh optimization algorithm, to enhance the source storage and ensure that the virtual power plant operates under low carbon conditions. …”
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Artificial neural network-driven approaches to improved forecasting of disability care expenditures in an aging Kingdom of Saudi Arabia population by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Furthermore, the bidirectional variational autoencoder with the self-attention module (BiVAE‐SAM) model forecasts disability care expenses. Finally, the enriched coati osprey algorithm (ECOA)-based hyperparameter selection process is performed to optimize the prediction results of the BiVAE‐SAM method. …”
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Optimization Model of Express–Local Train Schedules Under Cross-Line Operation of Suburban Railway by Jingyi Zhu, Xin Guo, Jianju Pan

“…This study addresses the joint optimization of cross-line operation and express–local scheduling by proposing a novel train timetable model. …”
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