Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…By integrating wavelet-based feature extraction with machine learning-driven analysis, this approach enhances the ability to detect complex wave propagation patterns, leading to more precise subsurface modeling. This advancement supports the implementation of smart field technology in Kazakhstan’s oil and gas industry, ultimately improving decision-making speed, operational efficiency, and resource optimization. …”
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The Effect of Entropy on the Performance of Modified Genetic Algorithm Using Earthquake and Wind Time Series by Manuel Vargas, Guillermo Fuertes, Miguel Alfaro, Gustavo Gatica, Sebastian Gutierrez, María Peralta

“…The dynamic complexity of time series of natural phenomena allowed to improve the performance of the genetic algorithm to optimize the test mathematical functions. …”
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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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Improving MPCitH with Preprocessing: Mask Is All You Need by Guowei Liu, Guoxiao Liu, Kaijie Jiang, Qingyuan Yu, Keting Jia, Puwen Wei, Meiqin Wang

“…The optimal signature implementation costs about 78% of the previous implementation time. …”
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Mobile-YOLO: A Lightweight Object Detection Algorithm for Four Categories of Aquatic Organisms by Hanyu Jiang, Jing Zhao, Fuyu Ma, Yan Yang, Ruiwen Yi

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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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Estimation Algorithm for Vehicle Motion Parameters Based on Innovation Covariance in AC Chassis Dynamometer by Xiaorui Zhang, Xingyuan Xu, Hengliang Shi

“…The test results indicate that the testing error of the optimized algorithm for the loading model decreases from 6.4% to 1.8%. …”
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Design of performance evaluation method for higher education reform based on adaptive fuzzy algorithm by Dakun Yang, Muhammad Sheraz Arshad Malik

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CF-YOLO for small target detection in drone imagery based on YOLOv11 algorithm by Chengcheng Wang, Yuqi Han, Chenggui Yang, Mingjie Wu, Zaiqing Chen, Lijun Yun, Xuesong Jin

“…Experiments show that on the public VisDrone dataset, TinyPerson dataset, and HIT-UAV dataset, CF-YOLO improves the mAP50 by 12.7%, 10.1%, and 3.5%, respectively, compared to the baseline model. …”
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Development and Simulation of a Fast Delay Cancellation Algorithm for Digital Multimedia Network Communication by Jinxia Li, Liwei Lu

“…The aim of this paper is to enhance the communication quality of digital multimedia networks by developing an algorithmic model that rapidly mitigates communication delays. …”
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Stress management with HRV following AI, semantic ontology, genetic algorithm and tree explainer by Ayan Chatterjee, Michael A. Riegler, K. Ganesh, Pål Halvorsen

“…Additionally, a Tree-Explainer, specifically SHAP, is used to interpret and explain the models’ classifications. The combination of genetic algorithm-based feature selection and classification using a Random Forest Classifier yields effective results for both imbalanced and balanced datasets, especially in analyzing non-linear HRV features. …”
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Priority-Aware Spectrum Management for QoS Optimization in Vehicular IoT by Adeel Iqbal, Tahir Khurshaid, Yazdan Ahmad Qadri, Ali Nauman, Sung Won Kim

“…A Continuous-Time Markov Chain (CTMC) model is derived to analyze the proposed algorithm for various network loads. …”
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Robust Optimization for Integrated Construction Scheduling and Multiscale Resource Allocation by Qian Li, Sha Tao, Heap-Yih Chong, Zhijie Sasha Dong

“…The experimental results indicate that the MOPSO-interior point algorithm can reduce resource cost and improve the efficiency of resource utilization.…”
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Machine Learning Techniques for Heart Disease Prediction Using a Multi-Algorithm Approach by Muhammad Kunta Biddinika, Alya Masitha, Herman Herman, Vita Arfiana Nurul Fatimah

“…The novelty of this study lies in the comparative analysis of several algorithms to optimize the heart disease prediction model for clinical use. …”
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Dynamic Node Management for Energy Optimization in Cognitive Radio Systems by Tangsen Huang, Haibing Yin, Xiangdong Yin, Huijun Xiao

“…Compared to traditional algorithms, the dynamic grouping algorithm significantly enhances spectrum sensing performance and improves energy efficiency. …”
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Data Enabled Predictive Control for Water Distribution Systems Optimization by Gal Perelman, Avi Ostfeld

“…Abstract Recent developments in control theory, coupled with the growing availability of real‐time data, have paved the way for improved data‐driven control methodologies. This study explores the application of the Data‐Enabled Predictive Control (DeePC) algorithm to optimize the operation of water distribution systems (WDS). …”
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Classification Algorithm for Heterogeneous Network Data Streams Based on Big Data Active Learning by Lili Zhan

“…The simulation experimental results show that the SNN-RODE-LapRLS algorithm improves the performance by 14%-51% over the mainstream classification algorithms, and the consumption time meets the demand of real-time classification.…”
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Indoor fire and smoke detection based on optimized YOLOv5. by Md Shafak Shahriar Sozol, M Rubaiyat Hossain Mondal, Achmad Husni Thamrin

“…It presents a hyperparameter-optimized YOLOv5 (HPO-YOLOv5) model optimized by a genetic algorithm. …”
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Optimization of a high gain observer for feedback linearization control by Nadia Bounouara, Mouna Ghanai, Kheireddine Chafaa

“…The main contribution of this approach is to improve the value of the high gain that corresponds to the minimum value of the cost function by using some metaheuristic algorithms. …”
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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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