Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…This study introduces a novel method to optimize Post-Training Quantization (PTQ), a widely used technique for reducing model size, by integrating Vector Quantization (VQ) with incremental clustering. …”
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Lightweight visible damage detection algorithm for embedded systems applied to pipeline automation equipment by Jiale Xiao, Lei Xu, Changyun Li, Ling Tang, Guogang Gao

“…In addition, the performance of the model is optimized by knowledge refinement. When tested on a customized pipeline defect dataset, CGYOLO used 25 % less memory, ran 39.5 % fewer gigaprocessors per second, had 28.5 % fewer parameters, and improved average accuracy by 4 % to 94.3 % compared to the smallest known state-of-the-art model. …”
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Graph neural processes for molecules: an evaluation on docking scores and strategies to improve generalization by Miguel García-Ortegón, Srijit Seal, Carl Rasmussen, Andreas Bender, Sergio Bacallado

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Efficient Pathfinding on Grid Maps: Comparative Analysis of Classical Algorithms and Incremental Line Search by Amr Elshahed, Majid Khan Bin Majahar Ali, Ahmad Sufril Azlan Mohamed, Farah Aini Binti Abdullah, Ts. Lee Jian Aun

“…Pathfinding on grid maps is a cornerstone problem in robotics, autonomous navigation, and game development. Classical algorithms such as A*, Dijkstra’s, and Breadth-First Search (BFS) are known for their ability to guarantee optimal solutions, while others like Depth-First Search (DFS) and Greedy Best-First Search prioritize speed over optimality. …”
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An approach based on genetic algorithms and neural networks for QoS-aware IoT services composition by Rabah Boucetti, Ouassila Hioual, Sofiane Mounine Hemam

“…Finally, we apply the second GA on the concrete services of the retained categories, in order to obtain the IoT service concrete composition with an overall QoS optimization. The simulation results show that the proposed approach has the best composition time, the best Hypervolume indicator and the best compositional optimality compared to SC-FLA, Improved GA and MGA approaches. …”
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PM2.5 Concentration Prediction Based on Markov Blanke Feature Selection and Hybrid Kernel Support Vector Regression Optimized by Particle Swarm Optimization by Lian-Hua Zhang, Ze-Hong Deng, Wen-Bo Wang

“…Abstract This study employed air quality and meteorological data as research materials and extracted the optimal feature subset by using the approximate Markov blanket-based normal maximum relevance minimum redundancy (nMRMR) algorithm to serve as the input data of the prediction model. …”
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Offshore Optical-wireless Integrated Access Network Deployment Algorithm based on MHA-MAD by LI Xuehua, XI Tong, WANG Xin, HUANG Xiang

“…Furthermore, compared to multi-agent Deep Q-Network (DQN) method without the multi-head attention, MHA-MAD algorithm improves the performance by nearly 8% in the joint optimization objective of minimizing overall network deployment costs, node power consumption, link attenuation, and network deployment risk probabilities.…”
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Dynamic scheduling for flexible job shop based on MachineRank algorithm and reinforcement learning by Fujie Ren, Haibin Liu

“…To improve the quality of the model solutions, a MachineRank algorithm (MR) is proposed, and based on the MR algorithm, seven composite scheduling rules are introduced. …”
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Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…Hence, an improved K-means clustering algorithm is proposed by introducing fast search and discovering density peak methods. …”
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Automated diabetes detection prediction system based on patients’ medical data by S.V. Pidopryhora, Yu.V. Bogoyavlenska

“…Furthermore, these systems create new opportunities for developers to monetize solutions, improving the economic efficiency of medical institutions by optimizing treatment costs. …”
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Predictive modelling of aquaculture water quality using IoT and advanced machine learning algorithms by Md. Abdullah Al Mamun Hridoy, Chiara Bordin, Andleeb Masood, Khalid Masood

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Third or fourth branchial pouch sinus lesions: a case series and management algorithm by Yun Li, Kexing Lyu, Yihui Wen, Yang Xu, Fanqin Wei, Haocheng Tang, Siyu Chen, Zhangfeng Wang, Xiaolin Zhu, Weiping Wen, Wenbin Lei

“…Conclusion Refining fistula subtypes and adopting corresponding treatment measures can reduce the recurrence rate and improve curative effects. We propose and advocate this treatment algorithm for all third and fourth branchial pouch lesions.…”
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Predicting the Likelihood of Operational Risk Occurrence in the Banking Industry Using Machine Learning Algorithms by Hamed Naderi, Mohammad Ali Rastegar Sorkhe, Bakhtiar Ostadi, Mehrdad Kargari

“…Specifically, the RF algorithm achieved an accuracy of 0.9690, while the SVM algorithm attained an accuracy of 0.9587 in State 1, making them the most effective models in this setting. …”
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Research on short-term traffic flow prediction based on the PCC-IGA-LSTM model by Junxi Zhang, Shiru Qu, Yang Bi, Lijing Ma

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Cable Force Optimization of Circular Ring Pylon Cable-Stayed Bridges Based on Response Surface Methodology and Multi-Objective Particle Swarm Optimization by Shengdong Liu, Fei Chen, Qingfu Li, Xiyu Ma

“…By synergizing explicit modeling with intelligent algorithms, this methodology effectively resolves the longstanding efficiency–accuracy trade-off in cable force optimization for cable-stayed bridges. …”
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Evaluation of Traditional and Data-Driven Algorithms for Energy Disaggregation Under Sampling and Filtering Conditions by Carlos Rodriguez-Navarro, Francisco Portillo, Isabel Robalo, Alfredo Alcayde

“…The selection of the optimal NILM algorithm for real-world applications must consider a balance between desired accuracy, load types, electrical signal characteristics, and crucially, the limitations of available computational resources.…”
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Modelling and optimization for cognitive radio networks with preemption backoff mechanism by Yuan Zhao, Zhiyu Xiang, Kang Chen, Zhisheng Ye, Qi Lu

“…To assess the comprehensive performance of our proposed mechanism, we deduce various important expressions of performance indices and get the corresponding performance figures. At last, we design a cost function by compromising various performance indices and find the optimum parameter combination under the lowest system cost through the Transient Search Optimization (TSO) algorithm. …”
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DP-YOLO: A Lightweight Real-Time Detection Algorithm for Rail Fastener Defects by Lihua Chen, Qi Sun, Ziyang Han, Fengwen Zhai

“…To enable accurate and efficient real-time detection of rail fastener defects under resource-constrained environments, we propose DP-YOLO, an advanced lightweight algorithm based on YOLOv5s with four key optimizations. …”
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Private Stochastic Optimization with Large Worst-Case Lipschitz Parameter by Andrew Lowy, Meisam Razaviyayn

“…To do so, we develop novel algorithmic and stability-based proof techniques, which we believe will be useful for future work in obtaining optimal excess risk. …”
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An improved lightweight method based on EfficientNet for birdsong recognition by Haolun He, Hui Luo

“…Finally, we employ the Adam optimization algorithm to improve network convergence speed. …”
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