An Effective Hybrid Strategy: Multi-Fuzzy Genetic Tracking Controller for an Autonomous Delivery Van by Mohammad Ghazali, Zaid Samadi, Mehmet Gol, Ali Demir, Kemal Rodoplu, Tarek Kabbani, Emrecan Hatipoğlu, Ahu E. Hartavi

“…Their output signals are optimally weighted by a genetic algorithm to determine the proper allocation of control signals for calculating the final steering angle. …”
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Hybrid Recurrent Neural Network and Decision Tree Scheduling for Energy-Efficient Resource Allocation in Cloud Computing by Sefati Seyed Salar, Vulpe Alexandru, Popovici Eduard, Fratu Octavian

“…The RNN model uses historical execution data to accurately predict task execution time, while the DT model classifies VMs based on performance characteristics, ensuring optimal task-to- VM assignments. …”
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Computational Construction of Sequential Efficient Designs for the Second-Order Model by Norah Alshammari, Stelios Georgiou, Stella Stylianou

“…By relaxing the restriction of non-replicated points within equally spaced intervals, our approach maintains space-filling properties while allowing greater flexibility for model-specific optimization. …”
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Network security situation assessment based on dual attention mechanism and HHO-ResNeXt by Dongmei Zhao, Guoqing Ji, Shuiguang Zeng

“…To solve these problems, this paper combines ResNeXt with the Efficient Channel Attention (ECA) module and the Contextual Transformer (COT) block to construct a model to assess network conditions. The optimal hyperparameters of the model are selected by the Harris Hawks Optimization (HHO) algorithm. …”
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An efficient hybrid framework with knowledge transfer for solving capacitated vehicle routing problems by Yanlin Wu, Yanguang Cai, Chuncheng Fang

“…This study proposes a hybrid framework (HF) that addresses these limitations through four key components: (1) An improved Clarke–Wright savings algorithm for rapid initialization of high-quality solutions, (2) an incremental auxiliary task formulation that optimizes knowledge transfer while minimizing computational overhead, (3) a similarity prediction strategy enabling efficient offspring selection without additional evaluations, and (4) the framework integrates enhanced search strategy and diversity maintenance strategy to prevent premature convergence. …”
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Decannulation ahead: a comprehensive diagnostic and therapeutic framework for tracheotomized neurological patients by Rainer Dziewas, Tobias Warnecke, Bendix Labeit, Volker Schulte, Inga Claus, Paul Muhle, Anna Brake, Lena Hollah, Anne Jung, Jonas von Itter, Sonja Suntrup-Krüger

“…This framework promotes flexibility, enabling clinicians to tailor interventions to individual patient needs while maintaining safety and optimizing outcomes.…”
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Sequential Inversion for Helicopter Time-Domain Electromagnetics Based on a Regularized Extended Kalman Filtering by Sirui Zhou, Jun Lin, Chuandong Jiang, Haigen Zhou, Yanzhang Wang

“…Based on the sequential processing strategy of measuring while inverting, the REKF algorithm yields the optimal solution of the inversion objective function in just a few iterations, or even a single iteration, enabling near real-time calculations. …”
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Machine learning frameworks to accurately predict coke reactivity index by Ayat Hussein Adhab, Morug Salih Mahdi, Krunal Vaghela, Anupam Yadav, Jayaprakash B, Mayank Kundlas, Ankur Srivastava, Jayant Jagtap, Aseel Salah Mansoor, Usama Kadem Radi, Nasr Saadoun Abd, Samim Sherzod

“…To minimize overfitting in each algorithm, K-fold cross-validation methodology is employed during the training phase. …”
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Hyperspectral Imaging for Non-Destructive Moisture Prediction in Oat Seeds by Peng Zhang, Jiangping Liu

“…Subsequently, a dual-optimized neural network model, termed Bayes-ASFSSA-BP, was developed by incorporating Bayesian optimization and the Adaptive Spiral Flight Sparrow Search Algorithm (ASFSSA). …”
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Reinforcement learning-based assimilation of the WOFOST crop model by Haochong Chen, Xiangning Yuan, Jian Kang, Danni Yang, Tianyi Yang, Xiang Ao, Sien Li

“…Our results demonstrate that the Time-Series Driven RL model achieved assimilation accuracy comparable to the SUBPLEX optimization algorithm, with an average MAE of 0.65 compared to 0.76 for SUBPLEX, and a slight decrease in RMSE, while significantly reducing the computational burden by 365 times. …”
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Adaptive sequential estimator for InSAR time series phase estimation by Guanya Wang, Zhiwei Li, Han Gao, Jun Hu, Mi Jiang, Peng Ren, Jie Zhang

“…First, an adaptive coherence-weighted matrix partitioning method is proposed. Utilizing Otsu’s algorithm and a local subset merging algorithm, it adaptively generates data subsets which are dynamically tailored to the coherence distribution. …”
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An Over-the-Air Multi-User Convolutional Code for URLLC by Rafael Santos, Daniel Castanheira, Adao Silva, Atilio Gameiro

“…A zero-terminated CC (ZTCC) enables efficient maximum likelihood (ML) decoding through the Viterbi algorithm, but suffers from a rate-loss particularly prominent in short blocks. …”
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Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario by Jingxuan Zhang, Xiaodong Xu, Kangjie Zhang, Bufang Zhang, Xiaofeng Tao, Ping Zhang

“…Moreover, we design the random forest-based ensemble TTI decision algorithm (RF-ETDA) to accomplish the TTI selection for each service. …”
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DynBlock: dynamic data encryption with Toffoli gate for IoT by Mubasher Haq, Ijaz Ali Shoukat, Alamgir Naushad, Mohsin Raza Jafri, Moid Sandhu, Abd Ullah Khan, Hyundong Shin

“…To address these challenges, this paper proposes a lightweight dynamic block cipher (DynBlock) algorithm. DynBlock is specifically suitable for resource-limited devices, and features a dynamic block size (64-128 bits), which is adaptable to symmetric encryption key sizes. …”
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IMA-FLADRC-Based Electric-Driven High-Speed Maize Precision Seeding Control Strategy and System by Song Wang, Shujuan Yi, Bin Zhao, Yifei Li, Dongming Zhang, Tao Chen, Wensheng Sun

“…This study develops an electric-driven high-speed maize precision seeding control system, establishing kinematic models for the seeding and guiding motors relative to operating speed. An Improve Mayfly Algorithm-Fuzzy Linear Active Disturbance Rejection Control (IMA-FLADRC)-based control strategy is proposed, integrating a fuzzy algorithm to adaptively adjust the proportional coefficient of the Linear State Error Feedback (LSEF) and optimizing key parameters using an IMA, enhancing system adaptability and robustness. …”
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Research on Rolling Bearing Fault Diagnosis Using Improved Majorization-Minimization-Based Total Variation and Empirical Wavelet Transform by Yangli Ou, Shuilong He, Chaofan Hu, Jiading Bao, Wenjie Li

“…Therefore, an improved particle swarm algorithm (IPSO) is used to find the optimal solution of λ. …”
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Association between admission Braden Skin Score and delirium in surgical intensive care patients: an analysis of the MIMIC-IV database by Meiling Shang, Meiling Shang, Ailing Shang, Yu Xu, Yu Xu

“…Feature importance of BSS was initially assessed using a machine learning algorithm, while restricted cubic spline (RCS) models and multivariable logistic analysis evaluated the relationship between BSS and delirium. …”
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Connected Transit Bus Dynamic Priority Weight Modeling and Conflicting Request Resolution Control at the Signalized Intersection by Shuxian He, Haihang Han, Huan Zhang, Shanzhi Sun, Tony Z. Qiu

“…What is more, it shows better delay optimization for social vehicles than the algorithm with delay as the objective while declining bus delay appreciable quantity with 43.4 s in average. …”
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Spectrum Sharing Design for Integrated Aeronautical Communication and Radar System by Lanchenhui Yu, Jingjing Zhao, Quan Zhou, Yanbo Zhu, Kaiquan Cai

“…An alternative optimization (AO) algorithm is proposed to solve the non-convex problem with highly coupled variables. …”
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Network capacity with probit-based stochastic user equilibrium problem. by Lili Lu, Jian Wang, Pengjun Zheng, Wei Wang

“…The network capacity is formulated as a bi-level programming where the up-level program is to maximize the network capacity through optimizing input parameters (O-D multiplies and signal splits) while the low-level program is the Logit-based or Probit-based SUE problem formulated to model the drivers' route choice. …”
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