Adaptive Trajectory Optimization for UAV-IRS Systems in 6G Thz Networks Using Multi Agent-DRL by Elmadina Nahla Nur, Saeed Rashid A., Saeid Elsadig, Awouda Ala Eldin, Mujlid Hana M., Elshafie Hashim

“…Given the non-convex and NP-hard nature of the problem, traditional optimization methods are insufficient. To tackle this, we propose a Multi-Agent Deep Reinforcement Learning (MADRL) algorithm, which provides an efficient, low-complexity solution for trajectory optimization. …”
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Balancing Human Mobility and Health Care Coverage in Sentinel Surveillance of Brazilian Indigenous Areas: Mathematical Optimization Approach by Juliane Fonseca Oliveira, Adriano O Vasconcelos, Andrêza L Alencar, Maria Célia S L Cunha, Izabel Marcilio, Manoel Barral-Netto, Pablo Ivan P Ramos

“…To optimize sentinel site selection, we implemented a linear optimization algorithm that maximizes (1) Indigenous region representation and (2) human mobility coverage. …”
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Dynamic Sensor-Based Data Management Optimization Strategy of Edge Artificial Intelligence Model for Intelligent Transportation System by Nu Wen, Ying Zhou, Yang Wang, Ye Zheng, Yong Fan, Yang Liu, Yankun Wang, Minmin Li

“…It aims to solve resource allocation optimization and improve operational efficiency in edge computing environments. …”
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System identification and robust PID controller tuning of quarter car suspension system using hybrid optimization techniques by S. Sakthiya Ram, C. Kumar, R. Saravanakumar, David Banjerdpongchai

“…Furthermore, two hybrid optimization strategies—Ant Colony Optimization with Genetic Algorithm (ACO-GA) and FminSearch with Simulated Annealing (Fmin-SA)—are applied to improve the control system’s robustness and response. …”
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Advanced Hybrid Brain Tumor Segmentation in MRI: Elephant Herding Optimization Combined with Entropy-Guided Fuzzy Clustering by Baiju Karun, Arunprasath Thiyagarajan, Pallikonda Rajasekaran Murugan, Natarajan Jeyaprakash, Kottaimalai Ramaraj, Rakhee Makreri

“…This method combines the nature-inspired Elephant Herding Optimization (EHO) algorithm with Entropy-Driven Fuzzy C-Means (EnFCM) clustering, offering significant improvements over conventional methods. …”
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A Path-Driven Fluid Routing and Scheduling Method for Continuous-Flow Microfluidic Biochips with Delay Time Optimization by Zhisheng Chen, Bowen Liu, Hongjin Su, Zhen Chen, Genggeng Liu, Xing Huang

“…This paper proposes an integrated path-driven methodology that jointly optimizes routing and application mapping. For routing, we develop a hybrid particle swarm optimization algorithm that incorporates conflict awareness and channel utilization strategies. …”
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Waveform design and signal processing for terahertz integrated sensing and communication by Xianbin YU, Zhidong LYU, Lianyi LI, Muhammad Idrees Nazar, Lu ZHANG

“…Integrated sensing and communication (ISaC) in the terahertz band can efficiently reduce the consumption of hardware and spectrum resources, while improving the transmission data rate and sensing resolution.Firstly, the development status of ISaC, terahertz communication and sensing were briefly introduced.Then, the strategy of waveform design and optimization for ISaC and the receiving signal processing algorithms were presented.As an example, an OFDM ISaC system operating at 97 GHz was experientially demonstrate, and the performance of ranging, speed and communication were all evaluated in the experiment.Finally, the key issues and research directions of future terahertz ISaC development were discussed.…”
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Optimizing Energy Efficiency in Vehicular Edge-Cloud Networks Through Deep Reinforcement Learning-Based Computation Offloading by Ibrahim A. Elgendy, Ammar Muthanna, Abdullah Alshahrani, Dina S. M. Hassan, Reem Alkanhel, Mohamed Elkawkagy

“…An optimization model is also proposed to minimize energy expenditure while ensuring that latency constraints are satisfied during computation offloading. …”
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A Novel Method for Traffic Parameter Extraction and Analysis Based on Vehicle Trajectory Data for Signal Control Optimization by Yizhe Wang, Yangdong Liu, Xiaoguang Yang

“…The method advances the state of the art through a novel polygon-based trajectory mapping algorithm and a systematic multi-source parameter extraction framework specifically designed for signal control optimization. …”
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Development of View Optimization Techniques for Structural Monitoring Systems Using Post-Processing of Structural Analysis and Image Processing by Yonghui Park

“…The optimization process applied image processing methods to detect deformation areas, while performance was evaluated at each iteration and saved when improvements were found. …”
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A Preemptive Scan Speed Control Strategy Based on Topographic Data for Optimized Atomic Force Microscopy Imaging by Thi Thu Nguyen, Oyoo Michael Juma, Luke Oduor Otieno, Thi Ngoc Nguyen, Yong Joong Lee

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Improving inverter efficiency for electric vehicles: Experimental validation of the neural network-based SHE technique using RT-LAB by Seyf Eddine Bechekir, Mokhtaria Jbilou, Mostefa Brahami, Fatima Zohra Boudjella, Imen Souhila Bousmaha, Mimouna Oukli, Said Nemmich

“…MATLAB/Simulink simulations and experimental results on the RT-LAB simulator confirm the algorithm’s capability to calculate optimal switching angles and produce high-performance PWM waveforms. …”
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Bayesian Network-Based Landslide Susceptibility Safe Route Assessment in the Face of Uncertain Knowledge and Various Information by Xinyu Gao, Bo Wang, Wen Dai, Yuanmin Liu

“…The BN model effectively integrates multi-source data and uncertainty knowledge to generate an accurate LSM, while the improved A* algorithm combines safety and efficiency considerations to optimize routes. …”
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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…To address this issue and guarantee more accurate ET predictions, this study attempts the following: i) to assess the performance of five machine learning (ML) models optimized by the RReliefF algorithm in estimating actual ET values for each month in four Chinese provinces under various agroclimatic conditions; and ii) to select the optimal model based on statistical metrics while minimizing discrepancies between the estimated and actual ET values. …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…For real-world limited samples (100 sets), adaptive optimization achieved 80% accuracy while boosting minority class (“spalling”) F1-score by 0.25 with 50% false alarm reduction. …”
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Personalized metronomic radiopharmaceutical therapy through injection profile optimization via physiologically based pharmacokinetic (PBPK) modeling by Aryan Golzaryan, M. Soltani, Farshad Moradi Kashkooli, Babak Saboury, Arman Rahmim

“…We designed a treatment algorithm to select optimal regimens with high AD, while investigating what we term radiopharmaceutical delivery payload (RDP). …”
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Utilizing Enhanced Particle Swarm Optimization for Feature Selection in Gender-Emotion Detection From English Speech Signals by Ammar Amjad, Li-Chia Tai, Hsien-Tsung Chang

“…This study introduces a novel approach, Dynamic Gender-Aware Enhanced Binary Particle Swarm Optimization (DGA-EBPSO), that leverages a gender-specific particle swarm optimization (PSO) technique for feature selection to enhance SER accuracy while promoting interpretability. …”
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Deep Learning Network Selection and Optimized Information Fusion for Enhanced COVID-19 Detection: A Literature Review by Olga Adriana Caliman Sturdza, Florin Filip, Monica Terteliu Baitan, Mihai Dimian

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Electricity Carbon Coupled Market Modeling Method and Market Optimization Mechanism Based on Dynamic Carbon Emission Intensity by Tong ZHAO, Xuesong LI, Hao ZHOU, Yu DING, Bin YANG, Wentao WANG, Peng WANG

“…A Markov decision iterative optimal coordination algorithm (MDIOCA) is proposed to solve the model. …”
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Performance Optimization of Synchronous Reluctance Motor using Adaptive MTPA Curve Fitting with Anti-Windup Current Control by Alex V, Rammohan A

“…Conventional scalar control methods typically rely on precomputed lookup tables or iterative optimization algorithms, which introduce computational overhead and require significant memory resources. …”
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