Robust STAP with coprime sampling structure based on optimal singular value thresholding by Mingxin Liu, Mingfu Li, Hui Li, Yan Cheng

“…To address this issue, the STAP with the coprime sampling structure based on optimal singular value thresholding is proposed. The algorithm corrects errors by adding four calibrated auxiliary elements and auxiliary pulses to the original array and pulse sequence, while maintaining the coprime sampling structure. …”
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Efficient search, mapping, and optimization of multi‐protein genetic systems in diverse bacteria by Iman Farasat, Manish Kushwaha, Jason Collens, Michael Easterbrook, Matthew Guido, Howard M Salis

“…We developed a computational approach to build predictive models and identify optimal sequences and expression levels, while circumventing combinatorial explosion. …”
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Towards Optimizing the Downlink Transmit Power in UAV-Integrated IRS Wireless Systems by Ali Reda, Tamer Mekkawy, Ashraf Mahran

“…In interference scenarios and with different numbers of IRS meta-atoms, the proposed algorithm achieves a power reduction of approximately 8 and 13 dBm, while maintaining the same required signal-to-interference-plus-noise ratio. …”
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Optimal Dynamic Reserved Bandwidth Allocation for Cloud-Integrated Cyber-Physical Systems by Guanlin Wu, Weidong Bao, Xiaomin Zhu, Wenhua Xiao, Ji Wang

“…Then we develop an online algorithm based on the proposed strategy using the Lyapunov optimization theory. …”
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Research on the optimization method of inventory management of important spare parts of intercity railway. by Dongyan Wang, Ying Sun, Liang Yu, Kun Shen, Junbo Li, Xia Wu

“…To enhance the reliability of intercity railway operations and reduce spare parts management costs, this paper employs the Zebra Optimization Algorithm-Least Squares Support Vector Machine (ZOA-LSSVM) to analyze the reliability of the important Weibull distribution spare parts of the intercity railway and fit the parameters of the reliability function for spare parts. …”
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Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges by Akvile Giedraityte, Sigitas Rimkevicius, Mantas Marciukaitis, Virginijus Radziukynas, Rimantas Bakas

“…Using comprehensive methodologies, the review examines state-of-the-art algorithms such as Multi-Objective Particle Swarm Optimization (MOPSO) and Non-Dominated Sorting Genetic Algorithm II (NSGA-II), alongside Crow Search Algorithm (CSA), Grey Wolf Optimizer (GWO), Levy Flight-Salp Swarm Algorithm (LF-SSA), Mixed-Integer Linear Programming (MILP) and tools like HOMER Pro 3.12–3.16 and MATLAB 9.1–9.13, which have been instrumental in optimizing HRESs. …”
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An Improved Spider Wasp Optimizer for Green Vehicle Route Planning in Flower Collection by Mengxin Lu, Shujuan Wang

“…Moreover, a Genetic Neighborhood Comprehensive Spider Wasp Algorithm (GN_CSWA) is proposed to find the solution to this problem. …”
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Development of an Optimized Ensemble Least Squares Model for Identifying Potential Deposit Customers by Firman Aziz, Mutia Maulida, Jafar Jafar, Nurafni Shahnyb, Norma Nasir, Ampauleng Ampauleng

“…This study presents the development and optimization of an Ensemble Least Squares (ELS) algorithm to enhance the classification of potential deposit customers. …”
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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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