Comprehensive Performance-Oriented Multi-Objective Optimization of Hemispherical Resonator Structural Parameters by Xiaohao Liu, Xin Jin, Chaojiang Li, Yumeng Ma, Deshan Xu, Simin Guo

“…Subsequently, the NSGA-II algorithm is applied to perform multi-objective mapping of these parameters, achieving an optimized resonator with a 4.61% increase in the minimum frequency difference from interference modes and a substantial improvement in thermoelastic damping of approximately 70.41%. …”
Get full text

Cancer Diagnosis Optimization With a Combination of Flexible THz Antennas and Machine Learning by M. Senthil Pandian, S. Deepa Nivethika, J. Idhikash, Vamsee N. Yashwanth, Aishwarya Shaji, Prabhakaran Paulraj

“…Whereas, the same antenna was designed and simulated with a model replicating human tissue with tumor, radiating at 0.88 THz with a return loss of −38 dB and gain of 9.6 dB. The optimization of the decision was done using the combination of K‐means and logistic regression algorithm to determine 95.06% efficiency.…”
Get full text

An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization by Warda M. Shaban

“…We feed these extracted features to FSS, which uses a proposed method to select the most important and effective features. The proposed method is called the Dimensional Archimedes Optimization Algorithm (DAOA). …”
Get full text

Applications of Recent Metaheuristic Algorithms for Loss Reduction in Distribution Power Systems considering Maximum Penetration of Photovoltaic Units by Le Duy Luan Nguyen, Phuc Khai Nguyen, Viet Cuong Vo, Ngoc Dieu Vo, Thang Trung Nguyen, Tan Minh Phan

“…Photovoltaic units (PVUs) are placed optimally by implementing the Coot optimization algorithm (COOA), the archimedes optimization algorithm (AOA), the transient search optimization algorithm (TSOA), the crystal structure algorithm (CrSA), the war strategy optimization algorithm (WSA), and the average and subtraction-based optimizer (ASBO). …”
Get full text

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

“…Results demonstrate that， compared to similar methods， the proposed method achieves faster convergence， more stable optimization effects， and effectively reduces both daily energy costs and carbon emission costs in IES operations.…”
Get full text

Location Optimization Model of a Greenhouse Sensor Based on Multisource Data Fusion by DianJu Qiao, ZhenWei Zhang, FangHao Liu, Bo Sun

“…In this paper, a model based on the moving least square method in the fusion algorithm is proposed to study the optimal monitoring point of the sensor in the greenhouse and determine the most suitable installation position of the sensor in the greenhouse to improve the control effect of the temperature control device of the system. …”
Get full text

Color Dominance-Based Polynomial Optimization Segmentation for Identifying Tomato Leaves and Fruits by Juan Pablo Guerra Ibarra, Francisco Javier Cuevas de la Rosa, Alicia Linares Ramirez

“…Similarly, a UNetmodel is used for semantic segmentation, the results of which are inferior to those obtained by the proposed interpolation optimization method. The most significant contribution of the interpolation method is that it requires only a single iteration to generate the initial data, in contrast to the iterative search required by the greedy algorithm and the lengthy training process and video card dependency of the UNet model. …”
Get full text

Research on Optimization of Large-Scale Heterogeneous Combat Network Based on Graph Embedding by Xianzheng Meng, Changrong Xie, Hui Li, Guangjun Zeng, Kebin Chen

“…It has shown a 17.23% improvement in this aspect compared to HCNOF0 and a 6.89% enhancement when compared to the GE-SU-EANet algorithm, underscoring its advantages in both optimization performance and cost reduction. …”
Get full text

Contextual Regularization-Based Energy Optimization for Segmenting Breast Tumor in DCE-MRI by Priyadharshini Babu, Mythili Asaithambi, Sudhakar Mogappair Suriyakumar

“…An iterative gradient descent algorithm is engaged to minimize the energy-based cost function, obtaining stable convergence towards the optimal solution. …”
Get full text

Optimization of Railway Equipment Maintenance Plan Based on Intelligent Patrol Inspection System by MA Yunlong

Get full text

Spatial modeling of brine level and salinity in the Qarhan Salt Lake using GIS and automated machine learning algorithms by Dongmei Yu, Zitao Wang, Chao Yue, Jianping Wang

Get full text

SIMULATION AND OPTIMIZATION AS A TOOL FOR THE DEVELOPMENT OF HIGH EFFECTIVE TECHNOLOGICAL SCHEMES OF DISTILLATION by A. V. Timoshenko, E. A. Anokhina

“…The data are presented for the optimization algorithms of the PTCDS. A comparison is made of conventional and developed distillation schemes using the energy consumption criterion. …”
Get full text

A Lyapunov Optimization-Based Approach to Autonomous Vehicle Local Path Planning by Ziba Arjmandzadeh, Mohammad Hossein Abbasi, Hanchen Wang, Jiangfeng Zhang, Bin Xu

“…Each control algorithm, i.e., Lyapunov Optimization (LO) and the two baseline methods, were independently used to generate safe and smooth paths for the AV based on the collected data. …”
Get full text

Towards few-shot learning with triplet metric learning and Kullback-Leibler optimization by Yukun Liu, Xiaojing Wei, Daming Shi, Dan Xiang, Junliu Zhong, Hai Su

“…In training, the deep learning and expectation-maximization algorithm are used to optimize models. Intensive experiments have been conducted on three popular benchmark datasets, and the experimental results show that this method significantly improves the classification ability of few-shot learning tasks and obtains the most advanced performance.…”
Get full text

Technique on Vehicle Damage Assessment After Collisions Using Optical Radar Technology and Iterative Closest Point Algorithm by Shih-Lin Lin, Yi-Hsuan Chen

“…The contributions of this study lie in integrating LiDAR technology with advanced point cloud processing algorithms and a deep learning optimization model for vehicle damage assessment, demonstrating high precision and cost-effectiveness. …”
Get full text

Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
Get full text

Adaptive component crossover for differential evolution in solving single-objective optimization problems by Sopov Anton, Sopov Evgenii

“…One of the most popular and promising evolutionary methods is the Differential Evolution algorithms. …”
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

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

Distribution Network Differential Protection Technology Based on 5G Communication and Improved DTW by YU Yang, TANG Wei, YE Yuanbo, SHAO Qingzhu, YANG Ruijin, HUANG Yuhui

“…Aiming at the shortcomings of traditional DTW algorithms, such as large overhead, algorithm accuracy and efficiency limited by sequence amplitude difference, and empirical selection of parameters, the global path constraint strategy, data standardization strategy and particle swarm optimization strategy are proposed to be improved. …”
Get full text