Prediction and Optimization of Civil Aviation Flight Delays Based on Machine Learning Algorithms by Qingwei Zhong, Yingxue Yu, Yiru Huang, Tianhang Zhang

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A Comparative Study Evaluated the Performance of Two-class Classification Algorithms in Machine Learning by Shilan Abdullah Hassan, Maha Sabah Saeed

“…By leveraging Azure Machine Learning's capabilities, researchers and healthcare professionals can analyze large datasets containing patient information and medical records to identify patterns and risk factors associated with heart attacks. …”
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Progress in plant genome sequencing: research directions by M. K. Bragina, D. A. Afonnikov, E. A. Salina

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Image Reconstruction Algorithm Based on Spectral Projected Gradient Pursuit for Electrical Capacitance Tomography by WANG Li-li, LIU Hong-bo, CHEN De-yun, CHEN Feng

“…Simulation experiment of typical flow pattern is carried out by the algorithm，and compared with the traditional LBP algorithm. …”
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Artificial Intelligence With Neural Network Algorithms in Pediatric Astrocytoma Diagnosis: A Systematic Review by Floresya K. Farmawati, Della W.A. Nurwakhid, Tifani A. Pradhea, Rayyan Fitriasa, Hutami H. Arrahmi, Muhana F. Ilyas, Fadhilah T. Nur

“…Recent advancements in artificial intelligence (AI), particularly neural network algorithms, have been studied for their precision and efficiency in medical diagnostics via effectively analyzing imaging data to identify patterns and anomalies.Objective: To systematically review AI-based diagnostic tools with neural network algorithms’ methodologies, sensitivities, specificities, and potential clinical integration for pediatric astrocytoma, providing a consolidated perspective on their overall performance and impact on clinical decision-making.Methods: As per PRISMA 2020 guidelines, we conducted a comprehensive search in PubMed, Scopus, and ScienceDirect on February 5, 2024. …”
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CRYPTOCURRENCY TIME SERIES FORECASTING MODEL USING GRU ALGORITHM BASED ON MACHINE LEARNING by Melina Melina, Sukono Sukono, Herlina Napitupulu, Norizan Mohamed, Yulison Herry Chrisnanto, Asep ID Hadiana, Valentina Adimurti Kusumaningtyas

“…The high fluctuation and volatility of cryptocurrency prices and the complexity of non-linear relationships in data patterns attract investors and researchers who want to develop accurate cryptocurrency price forecasting models. …”
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Automatic detection of human gait events: a simple but versatile 3D algorithm by Théo Vancanneyt, Camille Le Moal, Maxence Blard, Juliette Lenoir, Nicolas Roche, Céline Bonnyaud, Fabien Dubois

“…However, those methods do not fully account for intra-individual variability, particularly in the case of multiple and simultaneous gait patterns. Method We developed a deterministic algorithm called the Multi-Condition algorithm. …”
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An Enhanced Human Evolutionary Optimization Algorithm for Global Optimization and Multi-Threshold Image Segmentation by Liang Xiang, Xiajie Zhao, Jianfeng Wang, Bin Wang

“…Experiments demonstrated that the CLNBHEOA outperformed the comparison algorithms by over 90%, exhibiting higher optimization performance and search efficiency. …”
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Pedestrian Re-Recognition Algorithm Based on Optimization Deep Learning-Sequence Memory Model by Feng-Ping An

“…In view of this, this paper introduces a revertive connection into the pedestrian re-recognition detector, making it more similar to the human cognitive process by converting a single image into an image sequence; then, the memory image sequence pattern reidentifies the pedestrian image. This approach endows deep learning-based pedestrian re-recognition algorithms with the ability to memorize image sequence patterns and allows them to reidentify pedestrians in images. …”
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How does artificial intelligence shape the productivity and quality of research in business studies? A systematic literature review and future research framework by Sugandha Agarwal, Qian Long Kweh, Dima Jamali, Walton Wider, Syed Far Abid Hossain, Muhammad Ashraf Fauzi

“…We show that AI helps reduce research time and improve data management. Methods like machine learning and natural language processing can effectively uncover patterns and trends that conventional research methods may overlook. …”
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Machine heuristic in algorithm aversion: Perceived creativity and effort of output created by or with artificial intelligence by Sigurd Birk Heimstad, Anders Hauge Wien, Tarje Gaustad

“…Through two pre-registered experiments, we investigate how individuals evaluate creative content when it is labeled as created by AI, humans, or human-AI collaboration. While previous research has established algorithm aversion across various domains, our findings reveal nuanced patterns in creative contexts. …”
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Balancing comfort and conservation: dynamic programming algorithm for appliance scheduling in residential demand-side management by Maria Ashraf, Maryam Arshad, Sajjad Haider Zaidi, Kiran Shaukat

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Research Progress on Information Model of Urban Green Space by Wei ZHANG, Yahan YAN

“…Current urban green space information models require further development and refinement in research practices, which could focus on three approaches: The standardization of modeling process, the development of sharing platforms, and the application of generative algorithms. …”
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Evaluation and Analysis of Animation Multimedia 3D Lip Synchronization considering the Comprehensive Weighted Algorithm by Zhe Xu

“…How to carry out 3D lip synchronization effectively and accurately is an important research direction in the field of multimedia. On this basis, a comprehensive weighted algorithm is introduced in this paper to sort out the related laws and the time of lip pronunciation in animation multimedia, carry out the vector weight analysis on the texts in the animation multimedia, and synthesize a matching evaluation model for 3D lip synchronization. …”
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Optimized machine learning algorithms with SHAP analysis for predicting compressive strength in high-performance concrete by Samuel Olaoluwa Abioye, Yusuf Olawale Babatunde, Oluwafikejimi Abigail Abikoye, Aisha Nene Shaibu, Bailey Jonathan Bankole

“…Abstract This research examines the application of eight different machine learning (ML) algorithms for predicting the compressive strength of high-performance concrete (HPC). …”
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Nursing Value Analysis and Risk Assessment of Acute Gastrointestinal Bleeding Using Multiagent Reinforcement Learning Algorithm by Fang Liu, Xiaoli Liu, Changyou Yin, Hongrong Wang

“…Feature extraction is done using local binary patterns (LBP). Classification is performed using a fuzzy support vector machine (FSVM) classifier. …”
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APPA: An adaptation path planning algorithm for real-time obstacle avoidance in multi-robot systems by Jianzhi Jin, Mou Wu, Ping Fan, Guonian Jin

“…The APPA employs a hierarchical two-level planning architecture: in the first stage, an incremental search algorithm is used to generate a potential path framework; in the second stage, an adaptive exploration mechanism refines the path dynamically to adapt to environmental changes and moving obstacles. …”
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Advanced predictive disease modeling in biomedical IoT using the temporal adaptive neural evolutionary algorithm by Chandragandhi S, Arvind C, Srihari K

“…Experimental evaluations demonstrate TANEA’s superior performance over traditional methods, achieving improved accuracy, reduced computational overhead, and faster convergence rates. The algorithm’s adaptability to various biomedical data patterns enables more effective real-time monitoring and decision-making in IoT-based healthcare environments. …”
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PyBodyTrack: A python library for multi-algorithm motion quantification and tracking in videos by Angel Ruiz-Zafra, Janet Pigueiras-del-Real, Jose Heredia-Jimenez, Syed Taimoor Hussain Shah, Syed Adil Hussain Shah, Lionel C. Gontard

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Enhanced Network Traffic Classification Using Bayesian-Optimized Logistic Regression and Random Forest Algorithm by Manisankar Sannigrahi, R. Thandeeswaran

“…It examines the performance of a logistic regression model enhanced by Bayesian optimization for detecting TOR traffic using the UNB-CIC TOR-NonTOR datasets and a Bayesian-optimized random forest model for the CIC-Darknet2020 dataset. The research evaluates four key machine learning algorithms: Random forest, logistic regression, support vector machine (SVM), and K-nearest neighbors (K-NN). …”
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