Collision-inducing method for UAV evasive maneuvers based on receding horizon optimization by Haonan Tang, Zhigong Tang, Gong Chen, Jifeng Guo

“…The obstacle potential field-based target selection algorithm was employed to identify the most appropriate target obstacle, while the induced trajectory was determined through a combination of receding horizon optimization and the hp-adaptive pseudo-spectral method. …”
Get full text

Comparative Analysis of a Quantum SVM With an Optimized Kernel Versus Classical SVMs by Matheus Cammarosano Hidalgo

“…Support Vector Machine (SVM) is a widely used algorithm for classification, valued for its flexibility with kernels that effectively handle non-linear problems and high-dimensional data. …”
Get full text

Optimal scheduling of BIES with multi-energy flow coupling based on deep RL by XIA Xuhua, YANG Jiandi, SHI Yongtao

“…Building integrated energy systems （BIESs） can enhance energy efficiency ratio （EER） and reduce carbon emissions while meeting diverse user-side load demands. To further improve the energy dispatch capability of BIES， this paper proposes a low-carbon economic and optimal dispatch method for BIES with multi-energy flow coupling based on deep reinforcement learning （deep RL）. …”
Get full text

LCDDN-YOLO: Lightweight Cotton Disease Detection in Natural Environment, Based on Improved YOLOv8 by Haoran Feng, Xiqu Chen, Zhaoyan Duan

“…Additionally, the CBAM attention mechanism is incorporated into the neck network to improve model performance. A Focal-EIoU loss function is also integrated to optimize the model’s training process. …”
Get full text

Two-Stage Integrated Optimization Design of Reversible Traction Power Supply System by Xiaodong Zhang, Wei Liu, Qian Xu, Zhuoxin Yang, Dingxin Xia, Haonan Liu

“…The parallel cheetah algorithm is employed to solve this complex optimization problem. …”
Get full text

Deep Reinforcement Learning-Based Motion Control Optimization for Defect Detection System by Yuhuan Cai, Liye Zhao, Xingyu Chen, Zhenjun Li

“…A composite reward mechanism is introduced to mitigate potential motor instability, while CP-MPA is utilized to optimize the performance of the proposed m-TD3 composite controller. …”
Get full text

A Computational Sketch-Based Approach Towards Optimal Product Design Solutions by Paschalis Charalampous

“…In order to further enhance the overall design process, topology optimization (TO) is also performed, iteratively refining the geometry to achieve optimal material distribution for improved structural performance. …”
Get full text

Hybrid optimization driven fake news detection using reinforced transformer models by Ganesh Karthik M, Khadri Syed Faizz Ahmad, Sai Geetha Pamidimukkala, Asha Prashant Sathe, Sirisha G.N.V.G, Sitha Ram M, Koteswararao Ch

“…The model is further optimized using PSODO, a hybrid Particle Swarm Optimization and Dandelion Optimization algorithm, addressing limitations such as slow convergence and local optima entrapment. …”
Get full text

Gene selection based on adaptive neighborhood-preserving multi-objective particle swarm optimization by Sumet Mehta, Fei Han, Muhammad Sohail, Bhekisipho Twala, Asad Ullah, Fasee Ullah, Arfat Ahmad Khan, Qinghua Ling

“…The analysis of high-dimensional microarray gene expression data presents critical challenges, including excessive dimensionality, increased computational burden, and sensitivity to random initialization. Traditional optimization algorithms often produce inconsistent and suboptimal results, while failing to preserve local data structures limiting both predictive accuracy and biological interpretability. …”
Get full text

A Computable Phenotype Algorithm for Postvaccination Myocarditis/Pericarditis Detection Using Real-World Data: Validation Study by Matthew Deady, Raymond Duncan, Matthew Sonesen, Renier Estiandan, Kelly Stimpert, Sylvia Cho, Jeffrey Beers, Brian Goodness, Lance Daniel Jones, Richard Forshee, Steven A Anderson, Hussein Ezzeldin

“…ResultsThe algorithm required 200-250 hours to implement and optimize. …”
Get full text

Detection and Optimization of Photovoltaic Arrays’ Tilt Angles Using Remote Sensing Data by Niko Lukač, Sebastijan Seme, Klemen Sredenšek, Gorazd Štumberger, Domen Mongus, Borut Žalik, Marko Bizjak

“…The modules are grouped into arrays, and tilt angles are optimized using a Simulated Annealing (SA) algorithm, which maximizes simulated solar irradiance while accounting for shadowing, direct, and anisotropic diffuse irradiances. …”
Get full text

Integrated Approach to Optimizing Selection and Placement of Water Pipeline Condition Monitoring Technologies by Diego Calderon, Mohammad Najafi

“…This article introduces a unified framework and methods for optimally selecting condition monitoring technologies while locating their deployment at the most vulnerable pipe segments. …”
Get full text

A population spatialization method based on the integration of feature selection and an improved random forest model. by Zhen Zhao, Hongmei Guo, Xueli Jiang, Ying Zhang, Changjiang Lu, Can Zhang, Zonghang He

“…Therefore, feature factors selection using the MDA method was considered the optimal feature subset. Compared with MDA-RF, the prediction accuracy of the improved RF built on the same subset increased by 1.7%, indicating that improving the bootstrap sampling of random forest by using the K-means++ clustering algorithm can enhance model accuracy to some extent. …”
Get full text

Optimizing Rural Connectivity Through Hybrid Wireless-Wireline and Satellite Network Integration by Fareha Nizam, Teong Chee Chuah, Ying Loong Lee

“…In the user association scheme, the user association problem is formulated as a combinatorial optimization problem and solved using a greedy algorithm with a fairness-throughput trade-off that efficiently allocates resources based on network conditions and service priorities. …”
Get full text

Predicting compressive strength of concrete at elevated temperatures and optimizing its mixture proportions by Jinjun Xu, Han Wang, Wenjun Wu, Lang Lin, Yong Yu

“…The Cuckoo search algorithm was then employed to optimize mix designs, balancing high-temperature strength, cost and sustainability. …”
Get full text

A comprehensive review of artificial intelligence approaches for smart grid integration and optimization by Malik Ali Judge, Vincenzo Franzitta, Domenico Curto, Andrea Guercio, Giansalvo Cirrincione, Hasan Ali Khattak

“…The advanced metaheuristic algorithms are a good addition to the literature, they are still in emerging stages and their performance can further be improved. …”
Get full text

Cloud-edge hybrid deep learning framework for scalable IoT resource optimization by Umesh Kumar Lilhore, Sarita Simaiya, Yogesh Kumar Sharma, Anjani Kumar Rai, S. M. Padmaja, Khan Vajid Nabilal, Vimal Kumar, Roobaea Alroobaea, Hamed Alsufyani

“…The use of Graph Neural Networks (GNNs) improves the accuracy of resource representation, while reinforcement learning-based scheduling allows for seamless adaptation to changing workloads. …”
Get full text

Electrical discharge machining: Recent advances and future trends in modeling, optimization, and sustainability by Muhamad Taufik Ulhakim, Sukarman, Khoirudin, Dodi Mulyadi, Hendri Susilo, Rohman, Muji Setiyo

“…Optimization approaches, including machine learning-based algorithms, multi-objective optimization, and hybrid methods, have enhanced key performance indicators, such as material removal rate (MRR), surface quality, and tool wear, thereby increasing process efficiency and reducing machining time. …”
Get full text

A lightweight weed detection model for cotton fields based on an improved YOLOv8n by Jun Wang, Zhengyuan Qi, Yanlong Wang, Yanyang Liu

“…This study proposes the YOLO-Weed Nano algorithm based on the improved YOLOv8n model. First, the Depthwise Separable Convolution (DSC) structure is used to improve the HGNetV2 network, creating the DS_HGNetV2 network to replace the backbone of the YOLOv8n model. …”
Get full text

Interpretable prediction model for hand-foot-and-mouth disease incidence based on improved LSTM and XGBoost by Xiao LI, Shuyu HE, Yan PENG, Rongxin YANG, Lu TAO, Tingqi LOU, Wenqi HE

“…To further enhance the LSTM performance, the GWO is employed to adaptively optimize the key parameters of the LSTM. Thirdly, to fully leverage the advantages of XGBoost in handling nonlinear relationships and high-dimensional data while overcoming its complexities in parameter tuning and slower convergence, the GA is used to optimize the parameters of XGBoost. …”
Get full text