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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A multi strategy bidirectional RRT* algorithm for efficient mobile robot path planning by Yourui Huang, Wenxin Jiang, Shanyong Xu

“…Abstract To address the issues of slow convergence speed and poor path quality of the traditional Rapidly-exploring Random Tree Star (RRT*) algorithm in complex environments, this paper proposes a Multi Strategy Bidirectional RRT* (MS-BI-RRT*) algorithm for efficient mobile robot path planning. …”
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The Local Path Planning Algorithm for Amphibious Robots Based on an Improved Dynamic Window Approach by Xiaoqiang Dai, Chengye Liu, Qiang Lai, Xin Huang, Qingjun Zeng, Ming Liu

“…The speed resolution adaptive adjustment algorithm improves the ability to pass through a complex multiple-obstacle area, and the dynamic obstacle prediction algorithm optimizes obstacle avoidance paths. …”
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Comparative Analysis of Time Series Prediction Algorithms on Multiple Network Function Data of NWDAF by Dasheng Chen, Qi Song, Yinbin Zhang, Ling Li, Zhiming Yang

“…The dataset is carefully anonymized to ensure maximum realism and comprehensiveness, while safeguarding sensitive information. It encompasses eight categories of network functions, with data collected at five-minute intervals. …”
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DLE-YOLO: An efficient object detection algorithm with dual-branch lightweight excitation network by Peitao Cheng, Xuanjiao Lei, Haoran Chen, Xiumei Wang

“…Thirdly, the localization loss utilizes SIoU loss to further optimize the accuracy of the bounding box. Our method achieves a mAP value of 46.0% on the MS-COCO dataset, which is a 2% mAP improvement compared to the baseline YOLOv5-m, while bringing a 19.3% reduction in parameter count and a 12.9% decrease in GFLOPs. …”
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A hybrid evolution strategies algorithm for non-permutation flow shop scheduling problems by Bilal Khurshid, Shahid Maqsood, Muhammad Salman Habib, Muhammad Omair, Seung-June Hwang

“…The Quad swap mutation operator is employed in the IES to optimize the utilization of the solution space while minimizing computational time. …”
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Hybrid algorithms for geospatial analysis of dam location points in protective tasks for protected areas by S. Rodriguez Vasquez, N. V. Mokrova

“…This paper presents the way of optimizing the process of locating key terrain points by developing a hybrid algorithm for geospatial analysis in QGIS. …”
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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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Retrieval Augmented Therapy Suggestion for Molecular Tumor Boards: Algorithmic Development and Validation Study by Eliza Berman, Holly Sundberg Malek, Michael Bitzer, Nisar Malek, Carsten Eickhoff

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USD-YOLO: An Enhanced YOLO Algorithm for Small Object Detection in Unmanned Systems Perception by Hongqiang Deng, Shuzhe Zhang, Xiaodong Wang, Tianxin Han, Yun Ye

“…Second, we introduced the Spatial and Channel Reconstruction Convolution module to reduce redundancy in spatial and channel features while extracting key features of small objects. Additionally, we designed a novel C2f-Global Attention Mechanism module to expand the receptive field and capture more contextual information, optimizing the detection head’s ability to handle small and low-resolution objects. …”
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Modelling and Simulation of Perturb and Observe MPPT Algorithm Based on The PI Controller for Photovoltaic System by Ahlam Mohamad Shakoor, Hersh Hasan Taha

“…The proposed PV system is composed of a Photovoltaic array, DC to DC boost type converter and an MPPT algorithm using perturb and observe method. 1Soltech 1STH-220-P module type was chosen in this study for the simulation and proposed PV The array consists of 40 rows of PV modules connected in parallel, while each row consists of 10 modules connected in a series. …”
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

“… This research aimed to automate the fitting of kinetic models using genetic algorithms (GAs) to optimize the estimation of kinetic parameters—the reaction rate constant (k) and the initial value of total titratable acidity (TTA, C₀)—and enhance predictive accuracy. …”
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EMB-YOLO: A Lightweight Object Detection Algorithm for Isolation Switch State Detection by Haojie Chen, Lumei Su, Riben Shu, Tianyou Li, Fan Yin

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Design of netted muskmelon digital twin growth model based on HMM+LSTM algorithm by LU Peng, LIU Mingtang, WU Shanshan, LI Bin, LI Shihao, WANG Changchun, YANG Yangrui, JIANG Enhui

“…The digital twin model was developed using 3ds Max for 3D modeling and Unity 3D for visualization, while the growth prediction model was built by integrating Hidden Markov Model (HMM) and Long Short-Term Memory (LSTM) algorithms. …”
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Exploring the achievements and forecasting of SDG 3 using machine learning algorithms: Bangladesh perspective. by Md Maeen Molla, Md Sifat Hossain, Md Ayub Ali, Md Raqibul Islam, Mst Papia Sultana, Dulal Chandra Roy

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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

“…Furthermore, machine learning models, including standard regression algorithms and neural networks, are leveraged to enhance signal interpretation and predictive capabilities. …”
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Machine learning algorithms to predict epidural-related maternal fever: a retrospective study by Xiaohui Guo, Xiaohui Guo, Xiaohui Guo, Haixia Zhang, Haixia Zhang, Haixia Zhang, Hongliang Mei, Hongliang Mei, Hongliang Mei

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Optimizing the learning rate for adaptive estimation of neural encoding models. by Han-Lin Hsieh, Maryam M Shanechi

“…Here, we develop a novel analytical calibration algorithm for optimal selection of the learning rate in adaptive Bayesian filters. …”
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Maize Leaf Area Index Estimation Based on Machine Learning Algorithm and Computer Vision by Wanna Fu, Zhen Chen, Qian Cheng, Yafeng Li, Weiguang Zhai, Fan Ding, Xiaohui Kuang, Deshan Chen, Fuyi Duan

“…Traditional LAI measurement methods are often destructive and labor-intensive, while techniques relying solely on spectral data suffer from limitations such as spectral saturation. …”
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Pregnancy probability prediction models based on 5 machine learning algorithms and comparison of their performance by REN Chao, REN Chao, YANG Huan, ZHOU Niya, ZHOU Niya

“…In consideration of difficulty to carry out semen parameters analysis in primary healthcare institutions, feature Set 1 including sperm parameters and feature Set 2 excluding semen parameters were constructed by including or excluding sperm quality simultaneously in the training set and the validation set. Five algorithms, that is, Logistic Regression, Naive Bayes, Random Forest, Gradient Boosting Machine, and Support Vector Machine, were used to construct preconception outcome prediction models, and the parameters of each model were optimized using random search combined with grid search. …”
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