EPRSA: interference resource scheduling algorithms for air-ground communication networks by Wenpeng Wu, Zhenhua Wei, Haiyang You, Xiaoqing Li, Jianwei Zhan, Zhaoguang Zhang

“…Based on this, this paper proposes the interference link margin in the mathematical model and normalizes and quantifies the optimization objectives. Strategies such as cycle and initial quantity selection, elastic initialization, double tabu power scheduling, and jammer conversion are designed to improve the scheduling ability of the Elastic Parallel Random Search Algorithm (EPRSA) in terms of system operation duration and interference cost. …”
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A study on the prediction of mountain slope displacement using a hybrid deep learning model by Yuyang Ma, Xiangxiang Hu, Yuhang Liu, Yaya Shi, Zhiyuan Yu, Xinmin Wang, Liangbai Hu, Shuailing Liu, Dongdong Pang

“…Abstract To address the challenges of large prediction errors and limited reliability in conventional modeling approaches, this study proposes a hybrid framework that integrates optimization and deep learning techniques. The method employs an Improved Whale Optimization Algorithm (IWOA) to fine-tune parameters for GNSS data fitting, ensuring accurate signal feature extraction. …”
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Medium and Long Term Wind Power Prediction Based on Graph Convolutional Network and Wind Velocity Differential Fitting by Zihan CHEN, Wei TENG, Xuefeng XU, Xian DING, Yibing LIU

“…In order to make full use of the prior relationships among data features and improve the prediction accuracy of medium and long term wind power at wind farms, a medium and long term wind power prediction model based on graph convolution neural network (GCN), wind velocity differential fitting (DF), and particle swarm optimization (PSO) is proposed. …”
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Inverse Kinematics Solution for Manipulators Based on the Artificial Evolved Hummingbird Algorithm by Wang Junru, Qin Pengfei, Sun Guangbin

“…Aiming at the current stage of inverse kinematics solving methods for multi-degree-of-freedom manipulators, most of which have the problems of low solving accuracy and poor generalization, an artificial evolved hummingbird algorithm (AEHA) was proposed for inverse kinematics solving of manipulators. …”
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The Application of Kalman Filter Algorithm in Rail Transit Signal Safety Detection by Zhinong Miao, Qilong Liao

“…Firstly, the improved Kalman filter algorithm is used to denoise the signal to ensure the accuracy of signal transmission. …”
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Supply Chains Problem During Crises: A Data-Driven Approach by Farima Salamian, Amirmohammad Paksaz, Behrooz Khalil Loo, Mobina Mousapour Mamoudan, Mohammad Aghsami, Amir Aghsami

“…Results demonstrate significant improvements in cost reduction, resource allocation, and service levels, highlighting the model’s practical applicability in real-world scenarios. …”
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A Novel SPGD Algorithm for Wavefront Sensorless Adaptive Optics System by Jiaxun Li, Lianghua Wen, Hankui Liu, Guiming Wei, Xiang Cheng, Qing Li, Bing Ran

“…Stochastic parallel gradient descent (SPGD) is the most frequently used optimization algorithm for correcting wavefront distortion in the wavefront sensorless adaptive optics(WFS-Less AO)system. …”
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A Clustering Approach Using Cooperative Artificial Bee Colony Algorithm by Wenping Zou, Yunlong Zhu, Hanning Chen, Xin Sui

“…This paper presents an extended ABC algorithm, namely, the Cooperative Article Bee Colony (CABC), which significantly improves the original ABC in solving complex optimization problems. …”
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Performance Analysis of Marine Predators Algorithm for Automatic Voltage Regulator System by Zeynep Garip, Murat Erhan Çimen, Ali Fuat Boz

“…With the proposed algorithm, this study aimed to minimize the maximum percent excess of the terminal voltage, settling time, rise time, and steady-state error and improve the transient response of the automatic voltage regulator system with an optimal proportional–integral– derivative controller. …”
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Adjacency List Algorithm for Traffic Light Control Systems in Urban Networks by Sergio Rojas-Blanco, Alberto Cerezo-Narváez, Manuel Otero-Mateo, Sol Sáez-Martínez

“…An adjacency list is more efficient than matrices in terms of space and computational cost, allowing for the identification of critical signals before applying advanced optimization techniques such as neural networks or hypergraphs. …”
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Assessing and Reducing Energy Consumption of Grain Cleaning and Drying Equipment by Yu. N. Sap’yan, V. A. Kolos, M. I. Suleymanov, E. N. Kabakova

“…(Conclusions) The paper provides the offered criteria and a developed algorithm for energy-saving optimization of grain drying equipment, which reduces the direct energy consumption of production lines and energy costs. …”
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A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

“…The experimental results showed that the proposed algorithm achieved 98.9% accuracy, with 2.1 million parameters and a computational cost of 7.0 GFLOPs. …”
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Metaheuristics in Logistics: Increasing the Efficiency of Algorithms by Defining Appropriate Parameter Settings by Tamara J. Bíró, Péter Németh

“…In many cases, when applying a metaheuristic, it works properly with the variables of a given task and there is no specific interval where a given algorithm can still be effective. To increase efficiency and reduce costs, the authors defined a general parameter definition by applying the Ant Colony Optimization algorithm applicable to the simple Traveling Salesman Problem with the number of cities n=50, where for values of 30 = n = 50, the defined parameter setting structure can be properly applied based on the results. …”
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A BIT* algorithm with dilated vertices-based path stretching strategy by Xuanle Wu, Pu Li, Zhicheng Hou

“…In addition, DS-BIT* performs bidirectional improvement of the final path at the end of the algorithm, further reducing the final path cost. …”
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An Approach to Trustworthy Article Ranking by NLP and Multi-Layered Analysis and Optimization by Chenhao Li, Jiyin Zhang, Weilin Chen, Xiaogang Ma

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A Tunnel Lining Line Identification Algorithm Based on Supervised Heatmap by Heng SONG, Yisheng ZHANG, Tianbao GENG, Dongjie WANG

“…Therefore, using 8~10 outer points to supervise model learning in the first 10 rounds yields the most significant improvements. When noise is introduced early in the curve fitting input, recognition accuracy improves, with optimal noise disturbance intensity at approximately 0.08. …”
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A Contribution of Shortest Paths Algorithms to the NetworkX Python Library by Miguel Cruz, Rui Carvalho, André Costa, Luis Pinto, Luis Dias, Paulino Cerqueira, Rodrigo Machado, Tiago Batista, Pedro Castro, Jorge Ribeiro

“…We have also done the benchmarking of the A*, comparing it with the new ones, and concluded the better efficiency of the A* extensions in tri-objective scenario parameters (length, cost and toll). Despite the extensive utilisation of A* and its notable efficacy in identifying optimal paths, its performance is suboptimal in specific scenarios, such as when confronted with memory constraints and dynamic environments. …”
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Optimal Management in the Operation of Complex Technical Systems by Dyadyura K., Oborskyi G., Prokopovych I., Khamitov V., Holubiev M.

“…Additionally, proof of the existence of an optimal verification strategy was given. An algorithm for determining the moments of verification was developed to ensure the minimum cost. …”
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Algorithm of reconstruction combined midface defects after resection malignant tumors by M. V. Bolotin, A. M. Mudunov, V. Yu. Sobolevsky, V. I. Sokorutov

“…The purpose of reconstruction is not only the elimination of cosmetic deformity, but also the restoration of such vital functions as breathing, swallowing, speech and binocular vision. Till that time, no algorithm has been developed for choosing a method for the reconstruction and there is no comparative analysis of the available methods.The study objective is to improve the functional and aesthetic results of treatment patients with malignant tumors of the upper jaw and midface.Materials and methods. …”
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Power inspection UAV task assignment matrix reversal genetic algorithm by Kai Liu, Meizhao Liu, Ming Tang, Chen Zhang

“…Specifically, TMGA reduces the average task time by 37% compared to the Cluster Grouping Consensus-base Bundle Algorithm and improves task unit utility by 56.91% compared to the Genetic Algorithm.…”
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