PID Control and Input Shaping for Quadrotor UAV Stabilization and Payload Swing Reduction by Liyana Ramli, Izzuddin M. Lazim, Amalin Aisya Awi, Aina Syazwin Shukor

“…To enhance swing suppression, the input shaper parameters are optimized using the Particle Swarm Optimization (PSO) algorithm. …”
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Deep knowledge tracing and cognitive load estimation for personalized learning path generation using neural network architecture by Chunyan Tong, Changhong Ren

“…A dual-objective optimization algorithm balances knowledge acquisition with cognitive load management to generate paths that maintain optimal challenge levels. …”
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Energy-Efficient Secure Cell-Free Massive MIMO for Internet of Things: A Hybrid CNN–LSTM-Based Deep-Learning Approach by Ali Vaziri, Pardis Sadatian Moghaddam, Mehrdad Shoeibi, Masoud Kaveh

“…Additionally, a multi-objective improved biogeography-based optimization (MOIBBO) algorithm is utilized to optimize hyperparameters, ensuring an improved balance between convergence speed and model performance. …”
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A Sleep Scheduling Mechanism with PSO Collaborative Evolution for Wireless Sensor Networks by Luobing Dong, He Tao, William Doherty, Marten Young

“…To extend the lifetime of a wireless sensor network and improve the energy efficiency of its nodes, it is necessary to use node collaborative sleep algorithm to reduce the number of redundant nodes in the network. …”
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Economic sizing and placement of hydrogen fueling and electric vehicles charging stations powered by renewable and battery systems in smart distribution network by Mehdi Veisi

“…The solution is derived using Benders decomposition algorithm to achieve optimal results. The primary innovation highlighted in this paper includes integrating renewable resources and battery systems to power the refueling station, leveraging reactive power control for improved station performance, and addressing both operational and economic objectives in the distribution system. …”
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Reinforcement Learning-Driven Secrecy Energy Efficiency Maximization in RIS-Enabled Communication Systems by Akram Y. Sarhan, Osamah A. Abdullah, Hayder Al-Hraishawi, Faisal S. Alsubaei

“…We introduce an innovative framework that utilizes the deep deterministic policy gradient (DDPG) algorithm to address the challenges of the MDP. Our extensive simulations show that our method works much better than current techniques using deterministic policy gradients, like the proximal policy optimization (PPO) framework, in improving SEE. …”
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A UAV Image Stitching Method for Complex Urban Environments by W. Niu, D. Qiu, R. Wu, R. Wu, Z. Wang, Y. Shi

“…To address the issues of uneven feature point distribution, environmental interference, and insufficient real-time performance in UAV image stitching in complex urban environments, this paper proposes an improved ORB algorithm based on Gaussian scale-space optimization and dynamic grid division, combined with a global geometric consistency optimization strategy. …”
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Research on Dynamic Storage Location Assignment of Picker-to-Parts Picking Systems under Traversing Routing Method by Xiangbin Xu, Chenhao Ren

“…Finally, the computer program is developed to simulate the whole process. Simulation and data analysis results show that dynamic storage location assignment can effectively improve picking efficiency when the average order size is small and large demand correlation strength. …”
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Non-stereotypy (to species) in mysticete downsweeps by Paul Nguyen Hong Duc, Christine Erbe, Shyam Madhusudhana, Daniel Wilkes, Lachlan Gill, Cristina Tollefsen, Narissa de Bruin, Aiyana Erbeking, Curt Jenner, Micheline Jenner, Angela Recalde-Salas, Chandra P. Salgado Kent, Chandra P. Salgado Kent, Kautilya Srivastava, Kautilya Srivastava, Chong Wei, Robert McCauley

“…All of these species produce downsweeping calls, which may confound passive acoustic monitoring efforts. In an attempt to optimize a detector for Eastern Indian Ocean pygmy blue whale (EIOPBW) downsweeps, we tried a spectrogram correlator based on confirmed templates and a neural network trained on general blue whale D-calls followed by clustering algorithms. …”
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Privacy-Oriented Successive Approximation Image Position Follower Processing by Ying Miao, Danyang Shao, Zhimin Yan

“…The algorithm solves the problems of lack of scale estimation of KCF algorithm and low real-time rate of DSST algorithm and improves the tracking accuracy while ensuring the real-time performance of the algorithm.…”
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Edge Cloud Resource Scheduling with Deep Reinforcement Learning by Y. Feng, M. Li, J. Li, Y. Yu

“…Furthermore, we enhance the Proximal Policy Optimization (PPO) algorithm to improve adaptability, increase the accuracy of likelihood ratio estimation, identify a more suitable activation function, and impose constraints on gradient updates. …”
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Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…Additionally, the use of the Single-Step Proximal Policy Optimization (SSPPO) algorithm enhances the exploration of nozzle geometries by maximizing aerodynamic performance while balancing computational efficiency. …”
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A Distributed Resilience Enhancement Strategy for Multi-microgrids Based on System of Systems Architecture by Linxinyan LIN, Junpeng ZHU, Yue YUAN

“…Firstly, the energy exchange process of the multi-microgrid systems is modeled based on the SoS architecture, and the distributed optimization algorithm is used to solve the model, which ensures the privacy of user information. …”
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Modify a dual ridge horn antenna for drone jamming applications by Alaa Hussein Hilal, Ahmed Hameed Reja, Mohammed J. Mohammed

“…This work presents a DRHA developed utilizing CST Studio and optimized by using genetic algorithm optimization (GA) that has been employed to improve parameters that enhance selected frequencies. …”
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Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions by Xiaoshuang Guo, Ruiliang Xu, Junjiang Zhang, Xianghai Yan, Mengnan Liu, Mingyue Shi

“…Finally, a nonlinear model predictive control cooling optimization strategy is proposed, with the optimization objectives of quickly achieving battery temperature regulation and reducing compressor energy consumption. …”
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Convolutional transform learning based fusion framework for scale invariant long term target detection and tracking in unmanned aerial vehicles by Fatma S. Alrayes, Nazir Ahmad, Asma Alshuhail, Menwa Alshammeri, Ali Alqazzaz, Hassan Alkhiri, Jehad Saad Alqurni, Yahia Said

“…Finally, the hybrid nonlinear whale optimization algorithm with sine cosine (SCWOA) is implemented for the optimum choice of the hyperparameters involved in the GCN technique. …”
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Unsupervised fake news detection on social media using hybrid Gaussian Mixture Model. by Sajida Perveen, Muhammad Shahbaz, Sami S Albouq, Khlood Shinan, Hanan E Alhazmi, Fatmah Alanazi, M Usman Ashraf, Rehan Ashraf

“…In particular, it also proposes a novel hybrid method that leverages the Gaussian Mixture Model (GMM) in conjunction with the Group Counseling Optimizer (GCO), a metaheuristic optimization algorithm, to identify the optimal number of clusters for the detection of fake news. …”
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Green and Reliable Freight Routing Problem in the Road-Rail Intermodal Transportation Network with Uncertain Parameters: A Fuzzy Goal Programming Approach by Yan Sun

“…The operations of road transportation are time flexible, while rail transportation has fixed departure times. …”
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A Knowledge-Driven Smart System Based on Reinforcement Learning for Pork Supply-Demand Regulation by Haohao Song, Jiquan Wang

“…By harnessing dynamic decision-making capabilities of reinforcement learning (RL), we design an optimization architecture centered on the Q-learning mechanism and dual-strategy pools, which is integrated into the honey badger algorithm to form the RL-enhanced honey badger algorithm (RLEHBA). …”
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Blind source separation and unmanned aerial vehicle classification using CNN with hybrid cross-channel and spatial attention module by Jiangong Ni, Zhigang Zhou

“…The experimental results indicate that the mean absolute error (MAE) of the original algorithm was 14.58%, while the MAE of the improved FastICA decreased by 10.31%, dropping to 4.27%. …”
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