Optimization Method for Network Awareness in Different Domains of LEO Communication Constellation by DI Hang, DONG Tao, LIU Zhihui, WEI Shuotong, ZHANG Qiwei, ZHANG Dingyun

Get full text

Conveyor X-Ray Tomosynthesis Imaging With Optimized Structured Sequential Illumination by Xu Ma, Dong Wang, Angela Cuadros, Tianyi Mao, Qile Zhao, Gonzalo R. Arce, Tingfa Xu

“…Subsequently, a genetic algorithm is developed to optimize the exposure sequence of X-ray sources, and mask patterns, and during the dynamic measurement process. …”
Get full text

Daily runoff forecasting using novel optimized machine learning methods by Peiman Parisouj, Changhyun Jun, Sayed M. Bateni, Essam Heggy, Shahab S. Band

“…In the Carson River, the GB model achieves the highest forecasting accuracy, which is significantly improved by ARO, resulting in a 24.8 % reduction in root mean square error (RMSE). …”
Get full text

Optimized YOLOv8 framework for intelligent rockfall detection on mountain roads by Peng Peng, Langchao Gao, Jiachun Li, Hongzhen Zhang

“…To enable efficient detection, this study proposes a rockfall detection system based on embedded technology and an improved Yolov8 algorithm, termed Yolov8-GCB. The algorithm enhances detection performance through the following optimizations: (1) integrating a lightweight DeepLabv3+ road segmentation module at the input stage to generate mask images, which effectively exclude non-road regions from interference; (2) replacing Conv convolution units in the backbone network with Ghost convolution units, significantly reducing model parameters and computational cost while improving inference speed; (3) introducing the CPCA (Channel Priori Convolution Attention) mechanism to strengthen the feature extraction capability for targets with diverse shapes; and (4) incorporating skip connections and weighted fusion in the Neck feature extraction network to enhance multi-scale object detection. …”
Get full text

Integrated deep learning for cardiovascular risk assessment and diagnosis: An evolutionary mating algorithm-enhanced CNN-LSTM by Ahmed Mohammed Ahmed Alsarori, Mohd Herwan Sulaiman

“…EMA was applied for hyperparameter optimization, demonstrating improved convergence and generalization over conventional methods. …”
Get full text

Environmental and Economic Dispatching of Fire-Wind Combined System Based on Improved MOPSO by Li Rongshuai, Du Ruiqi, Lu Yi, Jiang Shan

“…Then, an improved multi-objective particle swarm optimization algorithm, LRMOPSO, is proposed by combining multi-objective particle swarm optimization algorithm, Levy flight jamming strategy and reverse learning strategy. …”
Get full text

Optimization of Intelligent English Pronunciation Training System Based on Android Platform by Qianyu Cao, Hanmei Hao

Get full text

Bayesian Optimization of insect trap distribution for pest monitoring efficiency in agroecosystems by Eric Yanchenko, Thomas M. Chappell, Anders S. Huseth

“…In this study, a Bayesian optimization (BO) algorithm was used to learn more about the optimal distribution of a fine-scale trap network targeting Helicoverpa zea (Boddie), a significant agricultural pest across North America. …”
Get full text

Optimizing Feature Selection for IOT Intrusion Detection Using RFE and PSO by zahraa mehssen agheeb Alhamdawee

“…Two feature selection mechanisms, which are Particle Swarm Optimization Algorithm (PSO) and Correlation-based Feature Selection Recursive Feature Elimination (RFE) have been used to compare their performances. …”
Get full text

Bio inspired optimization techniques for disease detection in deep learning systems by A. Ashwini, Vanajaroselin Chirchi, S. Balasubramaniam, Mohd Asif Shah

“…This work assists researchers in selecting the most effective bio-inspired algorithm for disease categorization, prediction, and the analysis of high-dimensional biomedical data.…”
Get full text

Bi-Objective Optimization of Product Selection and Ranking Considering Sequential Search by Yuyang Tan, Hao Gong, Chunxiang Guo

“…Customer choices in online retailing are often influenced by sequential search behavior. However, most existing models ignore the dynamic property of this process. …”
Get full text

Reliability-Based Optimization of Impeller Structure Using Exponential Function Approximation by Haiwei Lin, Yiqun Ren, Hong Bao, Feng Zhang, Feifei Zhao, Xiya Bao

“…Then, the obtained explicit exponential function approximation is used to decouple the reliability-based optimization problem and transform it into an equivalent deterministic optimization problem, where a general optimization algorithm can be adopted to solve steadily with a neglectable computational cost. …”
Get full text

Research on pose estimation algorithm of non-cooperative target tracked vehicles based on PnP model by Zhigang Ren, Xinagjun Tang, Guoquan Ren, Dinghai Wu

“…Finally, the pose equation is solved by finding the local minimum of the cost function through algebraic optimization, thus avoiding convergence issues in iterative optimization. …”
Get full text

A New Image Encryption Method Using an Optimized Smart Codebook by Rami Sihwail, Dyala Ibrahim

Get full text

Optimization of external container delivery and pickup scheduling based on appointment mechanism. by Pengfei Huang, Hao Wang, Fangjiao Tan, Yuyue Jiang, Jinfen Cai

“…Through case studies, we have demonstrated the superior performance of this algorithm in addressing relevant problems. The results show that, in terms of truck operational costs, the improved algorithm reduces costs by 10.96% and 3.02% compared to traditional Ant Colony Optimization and Variable Neighborhood Search algorithms, respectively, and by 4.89% compared to manual scheduling. …”
Get full text

Optimization Techniques on Quantum and Classical Systems: A Comprehensive Comparative Study by Shaik Hussain, Rajitha Morampudi, Priyamvada K., Bhargavi R. Naveena

“…This study compares Particle Swarm Optimization (PSO), Moth Flame Optimization (MFO), and Genetic Algorithm (GA) on three platforms : a local computer, a local computer with quantum integration, and an IBM quantum machine. …”
Get full text

Greedy gradient-free adaptive variational quantum algorithms on a noisy intermediate scale quantum computer by César Feniou, Muhammad Hassan, Baptiste Claudon, Axel Courtat, Olivier Adjoua, Yvon Maday, Jean-Philip Piquemal

“…However, practical implementations on current quantum processing units (QPUs) are challenging due to the noisy evaluation of a polynomially scaling number of observables, undertaken for operator selection and high-dimensional cost function optimization. We introduce an adaptive algorithm using analytic, gradient-free optimization, called Greedy Gradient-free Adaptive VQE (GGA-VQE). …”
Get full text

Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…Bayesian Optimization was applied to fine-tune hyperparameters to improve model accuracy. …”
Get full text

Optimization of Toolpath Planning and CNC Machine Performance in Time-Efficient Machining by Arbnor Pajaziti, Orlat Tafilaj, Afrim Gjelaj, Besart Berisha

“…We propose a method that integrates advanced algorithms to identify and eliminate redundant movements, optimize the toolpaths, and improve the machining strategies. …”
Get full text

Resource allocation strategy based on optimal matching auction in the enterprise network by Xin CONG, Lingling ZI, Xueli SHEN

“…To address the issue that the owners of computer are selfish in the enterprise networks,which caused the low available number of resource nodes and low efficiency of resource allocation,an optimized matching resource allocation strategy OMRA was proposed and its core was the auction mechanism.Selfishness was restrained and the number of available resources was increased by OMRA,so as the operating efficiency of the whole auction market was improved.First,the initial prices were determined by normalizing the costs of different type of resources on the beginning of auction.Secondly,an optimal matching auction algorithm was designed to maximize the interests of the auction markets.Then,service perfecting algorithm was performed such that the sellers could get more services at the current transaction value,thus ensuring the benefits of resource providers.At last,a request price updating algorithm was adopted to assurance that both sellers and buyers could get priorities in the next auction processing.Compared with the cloud resource allocating algorithm via fitness-enabled auction (CRAA/FA),the experiment results indicate that the efficiency of resource allocation improves by 10% and the benefits of market increase by 11.4%.…”
Get full text