Gait and Trajectory Optimization by Self-Learning for Quadrupedal Robots with an Active Back Joint by Ariel Masuri, Oded Medina, Shlomi Hacohen, Nir Shvalb

“…The algorithm actively optimizes 12 of the robot’s dynamic walking parameters. …”
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Securing Communication Networks at the Physical Layer: A DRL and Phase Optimization Approach by Mian Muhammad Kamal, Syed Zain Ul Abideen, Amin Sharafian, Anwar Hassan Ibrahim, Muhammad Islam, Shabana Habib

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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

“…For resource allocation, the framework employs the Time-aware modified best fit decreasing (T-MBFD) algorithm, which adapts to fluctuating workloads. Key input parameters for T-MBFD include available resources, job size, and time constraints, while output parameters focus on optimized resource distribution and minimizing wastage. …”
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Optimizing Hybrid Renewable Energy Systems for Enhanced Sustainability and Efficiency in Rural Communities by Bartolomeo Cosenza, Gabriele Pannocchia, Marco Vaccari

“…The developed algorithm determines optimal operating setpoints for each generator, carefully balancing system constraints while ensuring uninterrupted power delivery to meet load demands. …”
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Modeling and Optimization of Beam Pumping System Based on Intelligent Computing for Energy Saving by Xiaohua Gu, Taifu Li, Zhiqiang Liao, Liping Yang, Ling Nie

“…It firstly employs the general regression neural network (GRNN) algorithm to obtain the best model of the beam pumping system, and secondly searches the optimal operation parameters with improved strength Pareto evolutionary algorithm (SPEA2). …”
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Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization by Usharani Bhimavarapu, Gopi Battineni, Nalini Chintalapudi

“…The improved whale optimization (IWOA) algorithm was used for feature selection, which optimized weight functions to improve prediction accuracy. …”
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Optimization of signal control at ramp adjacent intersections based on A2C by SONG Tailong, GUO Mingyang, CHEN Yifan, HE Yulong

“…This study utilizes deep reinforcement learning algorithms for traffic signal control optimization at exit ramps associated with intersection crossings. …”
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Optimization of Resonant Arrays for Dynamic Wireless Power Transfer Using Adaptive Termination by Joao Dinis, Jose Alberto, Antonio J. Marques Cardoso

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A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling by Pujie Han, Wentao Hu, Zhengjun Zhai, Min Huang

“…This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. …”
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An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). DAOA is based on the Archimedes Optimization Algorithm (AOA) and Dimensional Learning Strategy (DLS). …”
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Schur Complement Optimized Iterative EKF for Visual–Inertial Odometry in Autonomous Vehicles by Guo Ma, Cong Li, Hui Jing, Bing Kuang, Ming Li, Xiang Wang, Guangyu Jia

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Accuracy–Efficiency Trade-Off: Optimizing YOLOv8 for Structural Crack Detection by Jiahui Zhang, Zoia Vladimirovna Beliaeva, Yue Huang

“…To address the accuracy–efficiency trade-off faced by deep learning models in structural crack detection, this paper proposes an optimized version of the YOLOv8 model. YOLO (You Only Look Once) is a real-time object detection algorithm known for its high speed and decent accuracy. …”
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COD Optimization Prediction Model Based on CAWOA-ELM in Water Ecological Environment by Lili Jiang, Liu Yang, Yang Huang, Yi Wu, Huixian Li, XiYan Shen, Meng Bi, Lin Hong, Yiting Yang, Zuping Ding, Wenjie Chen

“…In order to detect high error rate and poor convergence of the water ecological chemical oxygen demand (COD) prediction model, combining the limit learning machine (ELM) model and whale optimization algorithm, CAWOA is improved by the sin chaos search strategy, while the ELM optimizes the parameters of the algorithm to improve convergence speed, thus improving the generalization performance of the ELM. …”
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Better care for children with appendicitis: implementation of antibiotic stewardship optimizes postoperative therapy by Beltz, Sebastian, Fischer, Stephanie, Huenger, Frank, Vahdad, Reza, Kalhoff, Hermann, Leutner, Andreas

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Networked Sensor-Based Adaptive Traffic Signal Control for Dynamic Flow Optimization by Xinhai Wang, Wenhua Shao

“…This method integrates the Webster algorithm with a proportional–integral–derivative (PID) controller, whose parameters are optimized using a genetic algorithm, thereby facilitating scientifically informed traffic signal timing strategies for enhanced traffic regulation. …”
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Optimizing Masks and Random Screening Test Usage within K-12 Schools by Yiwei Zhang, Maria E. Mayorga, Julie S. Ivy, Julie L. Swann

“…Many studies discussed the effectiveness of various interventions, while few focused on optimizing such interventions. …”
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Evolutionary Search with Multiple Utopian Reference Points in Decomposition-Based Multiobjective Optimization by Wu Lin, Qiuzhen Lin, Zexuan Zhu, Jianqiang Li, Jianyong Chen, Zhong Ming

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K-Means Based Bee Colony Optimization for Clustering in Heterogeneous Sensor Network by Prince Modey, Gaddafi Abdul-Salaam, Emmanuel Freeman, Patrick Acheampong, William Leslie Brown-Acquaye, Israel Edem Agbehadji, Richard C. Millham

“…While the traditional bee colony optimization technique has been widely used as a clustering technique in WSN, it mostly suffers from energy efficiency and network performance. …”
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Beamforming and resource optimization in UAV integrated sensing and communication network with edge computing by Bin LI, Sicong PENG, Zesong FEI

“…To address the dependence of traditional integrated sensing and communication network mode on ground infrastructure, the unmanned aerial vehicle (UAV) with edge computing server and radar transceiver was proposed to solve the problems of high-power consumption, signal blocking, and coverage blind spots in complex scenarios.Firstly, under the conditions of satisfying the user’s transmission power, radar estimation information rate and task offloading proportion limit, the system energy consumption was minimized by jointly optimizing UAV radar beamforming, computing resource allocation, task offloading, user transmission power, and UAV flight trajectory.Secondly, the non-convex optimization problem was reformulated as a Markov decision process, and the proximal policy optimization method based deep reinforcement learning was used to achieve the optimal solution.Simulation results show that the proposed algorithm has a faster training speed and can reduce the system energy consumption effectively while satisfying the sensing and computing delay requirements.…”
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Self-adaptive dragonfly based optimal thresholding for multilevel segmentation of digital images by Rakoth Kandan Sambandam, Sasikala Jayaraman

“…Dragonfly optimization (DFO) is a population based meta-heuristic optimization algorithm that simulates the static and dynamic swarming behaviors of dragonflies. …”
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