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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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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Driver identification in advanced transportation systems using osprey and salp swarm optimized random forest model by Akshat Gaurav, Brij B. Gupta, Razaz Waheeb Attar, Ahmed Alhomoud, Varsha Arya, Kwok Tai Chui

“…In this context, this work suggests a new method to find drivers by means of a Random Forest model optimized using the osprey optimization algorithm (OOA) for feature selection and the salp swarm optimization (SSO) for hyperparameter tuning based on driving behavior. …”
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Predicting Spacecraft Telemetry Data by Using Grey–Markov Model with Sliding Window and Particle Swarm Optimization by Liang Ren, Feng Yang, Yuanhe Gao, Yongcong He

“…To overcome this drawback, we improved the GMSW model by applying particle swarm optimization (PSO) algorithm a sliding window for better prediction of spacecraft telemetry data (denoted as PGMSW model). …”
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DEEP-SEA LANDING VEHICLE SHAPE DRAG ANALYSIS AND BOW MODELED LINE OPTIMIZATION DESIGN (MT) by ZHANG ZiYao, ZHOU Yue, SUN Yu, LAN YanJun, GUO Wei

“…The optimal latin Hypercube method is used to select sample points for the direct navigation resistance calculation, an approximate model of design variable-resistance was established based on the radial basis function neural network, and the optimal design of landing vehicle bow modeled line was carried out by using the adaptive simulated annealing algorithm. …”
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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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Optimized Controller Design Using Hybrid Real-Time Model Identification with LSTM-Based Adaptive Control by Yeon-Jeong Park, Joon-Ho Cho

“…Our approach integrates an optimally adaptive Proportional–Integral–Derivative (PID) controller design algorithm that estimates the coefficients of the SOPTD model in the Smith Predictor control structure and adjusts the PID controller parameters dynamically. …”
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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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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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RM-MOCO: A Fast-Solving Model for Neural Multi-Objective Combinatorial Optimization Based on Retention by Huiqing Wei, Fei Han, Qing Liu, Henry Han

“…However, most of these methods use attention mechanisms and their variants, which have room for further improvement in the speed of solving MOCO problems. In this paper, following the idea of decomposition strategy and neural combinatorial optimization, a novel fast-solving model for MOCO based on retention is proposed. …”
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A Learning-Enhanced Metaheuristic Algorithm for Multi-Zone Orienteering Problem with Time Windows by Hongwu Li, Yongqi Luo, Yanru Chen, Yangsheng Jiang

“…The HACO algorithm combines the global search capabilities of a population-based algorithm with the parallel decision-making abilities of the Pointer Network learning model. …”
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Structural Design and Experiment Analysis of a Morphing Wing Structure by Song Zhendong, Li Gang, Guo Bing

“…In order to obtain better aerodynamic characteristics， an improved artificial fish swarm optimization algorithm is proposed based on the traditional artificial fish swarm optimization algorithm. …”
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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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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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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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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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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

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Temporal dependent rate-distortion optimization based on distortion backward propagation by Hongwei GUO, Ce ZHU, Xu YANG, Lei LUO

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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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