Magnetic Source Detection Using an Array of Planar Hall Effect Sensors and Machine Learning Algorithms by Miki Vizel, Roger Alimi, Daniel Lahav, Moty Schultz, Asaf Grosz, Lior Klein

“…To address this, we employed the Levenberg–Marquardt Algorithm (LMA) as a deterministic optimization method to estimate the magnetic source’s position and parameters, as well as machine earning (ML) algorithms, which consist of a Fully Connected Neural Network (FCNN). …”
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An Active RIS-Aided DFRC System for Improved Multi-User Communications by Ravi Patel, Aayush Singh, Keshav Singh, Shahid Mumtaz, Chih-Peng Li, Sudip Biswas

“…We develop a optimization algorithm that leverages weighted minimum mean square error (WMMSE) and fractional programming techniques to maximize the weighted sum rate (WSR) for communication users while ensuring robust radar detection performance. …”
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Estimation of the Ultimate Bearing Capacity of the Rocks via Utilization of the AI-Based Frameworks by Bianca Damico, Matteo Conti

“…The approach adopted here is new and solves the problem using KNN combined with two modern nature-inspired optimization frameworks, namely the Honey Badger Algorithm (HBA) and Equilibrium Slime Mould Algorithm (ESMA). …”
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CSCP-YOLO: A Lightweight and Efficient Algorithm for Real-Time Steel Surface Defect Detection by Chenglong Wang, Heng Wang, Yimin Jiang, Lei Yu, Xueting Wang

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Vehicular cache nodes selection algorithm under load constraint in C-V2X by Zhexin XU, Kaimeng GAO, Wenkang JIA, Yi WU

“…In order to solve the problem that the C-V2X vehicle topology in urban environment was highly dynamic and the load capacity of vehicle nodes was limited, and improve the utilization of vehicular cache resources and reduce the load of base station, a vehicle cache nodes selection algorithm under load constraints was proposed.Firstly, by defining the link stability metric, the predicted weight adjacency matrix was constructed to describe the vehicular micro-topology in essence.Next, the objective function was further constructed under the load constraints and non-overlapping coverage constraint, which maximized the average link weight of the clusters by using the least cache nodes.Finally, the greedy concept was then introduced and the node states were reasonably defined.As a result, the minimum dominating set of the vehicle topology was figured out under the load constraints.Besides, the serviced neighbor nodes were then determined preferentially.The simulation results show that the proposed algorithm is close to the global optimal results in terms of the number of cache nodes and the average weight of cluster links.Moreover, the repeated response ratio of the proposed algorithm is always zero while the request response ratio can achieve the theoretical upper bound.Furthermore, the response times of cache resources can be also effectively improved.…”
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Denoising of Inflow of Pingzhai Reservoir Based on Fusion Algorithm of Wavelet Transform and Savitzky-Golay Filter by GAO Lin, SONG Jinwei, LI Zuoxiao

“…According to the results, compared with the five point three order smoothing method, sliding average method, and wavelet threshold denoising method, the wavelet transform SG filtering fusion algorithm significantly improves the smoothness and denoising effect while ensuring the characteristics of the reverse flow peak information of the inflow. …”
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Denoising of Inflow of Pingzhai Reservoir Based on Fusion Algorithm of Wavelet Transform and Savitzky-Golay Filter by GAO Lin, SONG Jinwei, LI Zuoxiao

“…According to the results, compared with the five point three order smoothing method, sliding average method, and wavelet threshold denoising method, the wavelet transform SG filtering fusion algorithm significantly improves the smoothness and denoising effect while ensuring the characteristics of the reverse flow peak information of the inflow. …”
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Investigating the performance of random oversampling and genetic algorithm integration in meteorological drought forecasting with machine learning by Tahsin Baykal, Özlem Terzi, Gülsün Yıldırım, Emine Dilek Taylan

“…Therefore, this study aims to evaluate the effectiveness of machine learning methods for meteorological drought estimation and to integrate Random Oversampling (ROS) and Genetic Algorithm (GA) methods to improve estimation accuracy. …”
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Wood Panel Defect Detection Based on Improved YOLOv8n by Rui Li, Shilu Zhong, Xuemei Yang

“…However, the accuracy and convergence speed of existing defect detection techniques still require improvement. In this paper, an improved algorithm based on YOLOv8n was designed for accurate detection of wood panel defects. …”
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BED-YOLO: An Enhanced YOLOv10n-Based Tomato Leaf Disease Detection Algorithm by Qing Wang, Ning Yan, Yasen Qin, Xuedong Zhang, Xu Li

“…In this paper, we propose an improved tomato leaf disease detection method based on the YOLOv10n algorithm, named BED-YOLO. …”
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Optimal Modeling of Wireless LANs: A Decision-Making Multiobjective Approach by Tomás de Jesús Mateo Sanguino, Jhon Carlos Mendoza Betancourt

“…To this end, we implemented a multiobjective genetic algorithm (MOGA) with the purpose of meeting two simultaneous design objectives, namely, to minimize the number of APs while maximizing the coverage signal over a whole planning area. …”
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Evaluation of genomic mating approach based on genetic algorithms for long-term selection in Huaxi cattle by Yuanqing Wang, Bo Zhu, Jing Wang, Lupei Zhang, Lingyang Xu, Yan Chen, Zezhao Wang, Huijiang Gao, Junya Li, Xue Gao

“…Our results showed that the GM method could significantly improve the genetic gain while effectively controlling the inbreeding accumulation within the population. …”
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Optimization Research of the Hinge Position and Output Speed of Electromechanical Erection Device by Wei Cai, Shangjun Ma, Jianxin Zhang, Yong Zhou, Xiang Chen, Geng Liu

“…The optimum match relation between the output speed and the hinge position is got. It can improve work efficiency， make space layout of the whole device optimal and make the installation space the best compact.…”
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Flood-prone area mapping using a synergistic approach with swarm intelligence and gradient boosting algorithms by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Sani I. Abba, Jamil Hussain, Soo-Mi Choi

“…This research introduces a novel approach to increase the accuracy of FSM by optimizing the CatBoost algorithm with two swarm-based metaheuristic algorithms: the Zebra optimization algorithm (ZOA) and the Whale optimization algorithm (WOA). …”
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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%.…”
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MPDCGA: a real-coded multi-population dynamic competitive genetic algorithm for feature selection by Chuantao Li, Chen Huang, Ruihan Chen, Zhuohong Yu, Sheng Li

“…To mitigate these limitations, this study proposes a real-coded multi-population dynamic competitive genetic algorithm (MPDCGA) for feature selection. In this innovative framework, the population initialization mechanism based on mRMR and cosine similarity furnishes a diverse initial solution, the dynamic competition operator explores the optimal feature subset through coevolutionary processes, and the adaptive similarity crossover operator improves the global search efficiency while augmenting the capability to extract potentially salient features. …”
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Explorative Binary Gray Wolf Optimizer with Quadratic Interpolation for Feature Selection by Yijie Zhang, Yuhang Cai

“…Therefore, feature selection becomes an essential preprocessing stage, aimed at reducing the dimensionality of the dataset by selecting the most informative features while improving classification accuracy. This paper proposes a novel binary Gray Wolf Optimization algorithm to address the feature selection problem in classification tasks. …”
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Simulation of a scalable corridor waning radiance system using fuzzy PID and genetic algorithm by Abdallah Awamu, Jimmy Nabende Wanzala, Michael Robson Atim, Cosmos Dumba

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VRU-YOLO: A Small Object Detection Algorithm for Vulnerable Road Users in Complex Scenes by Yunxiang Liu, Yuqing Shi

“…Additionally, a lightweight Optimized Shared Detection Head (OSDH-Head) is introduced, reducing computational complexity while improving detection efficiency. …”
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Significance of Machine Learning-Driven Algorithms for Effective Discrimination of DDoS Traffic Within IoT Systems by Mohammed N. Alenezi

“…Findings revealed that the RF model outperformed other models by delivering optimal detection speed and remarkable performance across all evaluation metrics, while KNN (K = 7) emerged as the most efficient model in terms of training time.…”
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