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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Research on Sparse Code Multiple Access Detection Technology in Satellite Communication Systems by Yiting JIANG, Lidong ZHU

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Research on intelligent control of coal slime flotation based on the WOA-GRU model by DOU Zhiheng, WANG Ranfeng, QIN Xinkai, CHAI Yuqing, LI Pinyu, LIU Shutong

“…To address the low fitting accuracy of traditional identification methods, a Whale Optimization Algorithm (WOA)-based Gated Recurrent Unit (GRU) system identification model (WOA-GRU) was proposed. …”
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Multi-objective quantum hybrid evolutionary algorithms for enhancing quality-of-service in internet of things by Shailendra Pratap Singh, Gyanendra Kumar, Umakant Ahirwar, Shitharth Selvarajan, Firoz Khan

“…The hybrid algorithm enhances QoS in IoT applications by achieving superior optimization in terms of energy efficiency, latency reduction, convergence, and coverage cost. …”
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A thermodynamic inspired AI based search algorithm for solving ordinary differential equations by V. Murugesh, M. Priyadharshini, T. R. Mahesh, Esmael Adem Esleman

“…In return, metaheuristic algorithms have become promising alternatives that strongly transform the solution process into an optimization task. …”
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Visual SLAM algorithm for underground robots in coal mines based on point-line features by Li WANG, Tianxiang ZANG, Bo SU

“…Therefore, a binocular vision localization algorithm SL-SLAM for underground mobile robots in coal mines based on the improved ORB (Oriented Fast and Rotated Brief)-SLAM3 algorithm is proposed. …”
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Biomechanical Modeling of Selected Methods of Load Carriage to Improve Military Capabilities of Troops by Mostafa Hajlotfalian, Alireza Redaei, Heydar Sadeghi

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Nonlinear waveform optimization for wireless power transfer systems by Lina Yuan, Huajun Chen, Maoxue Hu, Jing Gong

“…We develop single-user and multi-user algorithms that maximize the output DC voltage of the weighted and/or minimum moment antennas by optimizing waveform design. …”
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A multi strategy bidirectional RRT* algorithm for efficient mobile robot path planning by Yourui Huang, Wenxin Jiang, Shanyong Xu

“…During the parent node rewiring phase, a multi-factor path cost function is constructed to optimize parent node selection, thereby improving path quality. …”
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A parallel multi-objective genetic algorithm for scheduling scientific workflows in cloud computing by Muhammad Sardaraz, Muhammad Tahir

“…The results show that the proposed algorithm achieves an improvement in makespan and reduces the cost with a well load balanced system.…”
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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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A Novel Proposed Algorithm to Enhance the Overcurrent Relays’ Performance in Active Distribution Networks by Sally El-Tawab, Hassan S. Mohamed, A. M. Abdel-Aziz

“…In this study, the improved wild horse optimization (IWHO) algorithm is used as a novel metaheuristic method for solving optimization issues in coordination of OCRs in a distribution network, for the first time. …”
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Development of Spectral Clustering Algorithm in Cognitive Diagnosis Model: Approach for Student’s Psychological Growth by Xiao Chang

“…The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…Additionally, a neural network-based forecasting algorithm utilizing the Daubechies wavelet transform is introduced to improve the predictive accuracy of subsurface characteristics. …”
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Performance assessment of basalt fibre concrete under freeze-thaw cycles using hybrid long short-term memory models by Qingguo Yang, Honghu Wang, Qigui Yi, Liuyuan Zeng, Rui Xiang, Longfei Guan, Jiawei Cheng, Keling Chen, Yunhao Li

“…The synergistic use of different admixtures is an effective anti-freezing method, but traditional testing methods are costly and time-consuming. To optimize current technical approaches, this study proposes a Ensemble Model combining Long Short-Term Memory (LSTM) networks with swarm intelligence optimization algorithms to address the adaptability of multi-parameter materials in basalt fiber concrete (BFC) under FTCs. …”
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A comprehensive review of fiber-reinforced topology optimization for advanced polymer composites produced by automated manufacturing by Bence Szederkenyi, Norbert Krisztian Kovacs, Tibor Czigany

“…Accordingly, the review introduces the main TO techniques and the common reinforcement path design strategies using concurrent and sequential optimization approaches. Furthermore, this paper examines the potential transformation of the conventional role of TO algorithms in structural optimization by integrating Artificial Intelligence (AI) into the optimization process [1]. …”
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Finite-Time Control for Satellite Formation Reconfiguration and Maintenance in LEO: A Nonlinear Lyapunov-Based SDDRE Approach by Majid Bakhtiari, Amirhossein Panahyazdan, Ehsan Abbasali

“…This optimization process minimizes energy usage through a hybrid genetic algorithm and simulated annealing (HGASA), resulting in improved performance. …”
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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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Design and Experiment of a Greenhouse Autonomous Following Robot Based on LQR–Pure Pursuit by Yibin Hu, Jieyu Xian, Maohua Xiao, Qianzhe Cheng, Tai Chen, Yejun Zhu, Guosheng Geng

“…These findings confirm that the designed robot can sustain its payload under most operating scenarios and that the proposed tracking strategy effectively suppresses deviations and improves path-following accuracy.…”
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An Experimental Comparison of Self-Adaptive Differential Evolution Algorithms to Induce Oblique Decision Trees by Rafael Rivera-López, Efrén Mezura-Montes, Juana Canul-Reich, Marco-Antonio Cruz-Chávez

“…This study addresses the challenge of generating accurate and compact oblique decision trees using self-adaptive differential evolution algorithms. Although traditional decision tree induction methods create explainable models, they often fail to achieve optimal classification accuracy. …”
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