Designing a Stock Recommender System Using the Collaborative Filtering Algorithm for the Tehran Stock Exchange by Marziyeh Nourahmadi, Ali Rahimi, Hojjatollah Sadeqi

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Developing genetic algorithm-based neural networks and sensitivity analysis for thermal conductivity of natural gases by R. Beigzadeh, R. Ozairy

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Secondary System Fault Detection Method Based on Association Rules and Reconstruction Error by Yang WANG, Weidong MA, Jiming LIU, Boshi WANG, Kai YAO, Wei HAN, Juan YU

“…Therefore this paper proposes a secondary system fault detection method based on association rules and reconstruction errors. Firstly, the Apriori algorithm is used to derive the association rules between fault alarm information and fault devices in the logic circuit, achieving rapid diagnosis of logic circuit faults. …”
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Numerical Recognition Algorithm for Power Equipment Monitoring Based on Light-Resnet Convolutional Neural Network by Zhiheng KONG, Chong TAN, Peiyao TANG, Chengbo HU, Min ZHENG

“…This approach, leveraging the allocation of computational resources for task distribution, introduces a Light-Resnet-based numerical recognition algorithm, which enhances network training through the optimization of the D-Add loss function, enabling remote reading of electrical equipment monitoring data. …”
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Improving Cell Detection and Tracking in Microscopy Images Using YOLO and an Enhanced DeepSORT Algorithm by Mokhaled N. A. Al-Hamadani, Richard Poroszlay, Gabor Szeman-Nagy, Andras Hajdu, Stathis Hadjidemetriou, Luca Ferrarini, Balazs Harangi

“…To mitigate this, we incorporate the DeepSORT tracking algorithm, which enhances data association and reduces the cells’ identity (ID) switches by utilizing a pre-trained convolutional network for robust multi-object tracking. …”
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Comparison of Machine Learning Algorithms to Predict Down Syndrome During the Screening of the First Trimester of Pregnancy by Eduardo Alonso, Andoni Beristain, Jorge Burgos, Ibai Gurrutxaga

“…The trained classification algorithms achieved ROC-AUC values between 0.970 and 0.982, with sensitivity and specificity of 0.94. …”
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Moanna: Multi-Omics Autoencoder-Based Neural Network Algorithm for Predicting Breast Cancer Subtypes by Richard Lupat, Rashindrie Perera, Sherene Loi, Jason Li

“…Here, we propose a novel deep-learning-based algorithm, Moanna, that is trained to integrate multi-omics data for predicting breast cancer subtypes. …”
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Toward Hand Gesture Recognition Using a Channel-Wise Cumulative Spike Train Image-Driven Model by Yang Yu, Zeyu Zhou, Yang Xu, Chen Chen, Weichao Guo, Xinjun Sheng

“…However, establishing associations between the neural control signals of motor units and gestures remains an open question. …”
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Prediction model for psychological disorders in ankylosing spondylitis patients based on multi-label classification by Kun Yang, Yifan Gong, Xiaohan Xu, Tiantian Sun, Xinning Qu, Xiaxiu He, Hongxiao Liu

“…ObjectiveThis study aims to develop a predictive model to assess the likelihood of psychological disorders in patients with ankylosing spondylitis (AS) and to explore the relationships between different factors and psychological disorders.MethodsPatients were randomly divided into training and test sets in an 8:2 ratio. The Boruta algorithm was applied to select predictive factors, and a multi-label classification learning algorithm based on association rules (AR) was developed. …”
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Intelligent Energy-Efficient Train Trajectory Optimization Approach Based on Supervised Reinforcement Learning for Urban Rail Transits by Guannan Li, Siu Wing Or, Ka Wing Chan

“…First, multiple objectives are formulated based on real-time train operation and systematically integrated into the RL algorithm by a binary function-based goal-directed reward design method. …”
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Prediction of stunting and its socioeconomic determinants among adolescent girls in Ethiopia using machine learning algorithms. by Alemu Birara Zemariam, Biruk Beletew Abate, Addis Wondmagegn Alamaw, Eyob Shitie Lake, Gizachew Yilak, Mulat Ayele, Befkad Derese Tilahun, Habtamu Setegn Ngusie

“…The synthetic minority oversampling technique was used for data balancing and Boruta algorithm was used to identify best features. Association rule mining using an Apriori algorithm was employed to generate the best rule for the association between the independent feature and the targeted feature using R software.…”
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Cooperative Control of Power Grid Frequency Based on Expert-Guided Deep Deterministic Policy Gradient Algorithm by Tao Shen, Jing Zhang, Yu He, Shengsun Yang, Demu Zhang, Zhaorui Yang

“…This approach avoids the overfitting issues associated with fixed disturbance training, enhancing the adaptability and robustness of the algorithm. …”
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An Analysis of Semi-Supervised Machine Learning in Electrical Machines by V. Raju Arvind, S. Shyamsharan, Poorvajaa Gurunathan, Krishna Kumba, Nawin Ra

“…The research investigates important SSML algorithms such as self-training, co-training, generative models, and graph-based methods, highlighting their particular uses in fault diagnosis, condition monitoring, and predictive maintenance of electrical machines. …”
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Research on Asphalt Pavement Surface Distress Detection Technology Coupling Deep Learning and Object Detection Algorithms by Hong Zhang, Yuanshuai Dong, Yun Hou, Xiangjun Cheng, Peiwen Xie, Keming Di

“…A monocular camera was used to capture pavement surface images, resulting in a dataset of 85,511 training samples. Additionally, the YOLOv5 object detection algorithm, combined with convolutional deep learning techniques, was employed to classify and identify pavement surface distresses in the collected images. …”
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Dark Ship Detection via Optical and SAR Collaboration: An Improved Multi-Feature Association Method Between Remote Sensing Images and AIS Data by Fan Li, Kun Yu, Chao Yuan, Yichen Tian, Guang Yang, Kai Yin, Youguang Li

“…Subsequently, an advanced JVC global optimization algorithm is employed to ensure high-precision association in dense scenes. …”
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Identifying liver cirrhosis in patients with chronic hepatitis B: an interpretable machine learning algorithm based on LSM by Xueting Bai, Chunwen Pu, Wenchong Zhen, Yushuang Huang, Qian Zhang, Zihan Li, Yixin Zhang, Rongxuan Xu, Zhihan Yao, Wei Wu, Mei Sun, Xiaofeng Li

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Accuracy of Smartphone-Mediated Snore Detection in a Simulated Real-World Setting: Algorithm Development and Validation by Jeffrey Brown, Zachary Mitchell, Yu Albert Jiang, Ryan Archdeacon

“…ObjectiveThe SleepWatch smartphone app (Bodymatter, Inc) aims to monitor and improve sleep quality and has snore detection capabilities that were built through a machine-learning process trained on over 60,000 acoustic events. This study evaluated the accuracy of the SleepWatch snore detection algorithm in a simulated real-world setting. …”
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Predicting Financial Distress through Ranking Working Capital Management Components Using Random Forest Algorithm by Pouya Sadeghi, Daryush Farid, Hamid Reza Mirzaei, Abolfazl Dehghani

“…Subsequently, the predictive power of 7 key working capital management components in forecasting financial distress was tested using Python software and the random forest algorithm.The random forest method is based on ensemble learning, wherein the data are split into training and testing sets. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…This segmentation is significantly enhanced by runtime data augmentation and trained on a robust train/validation/test dataset split. …”
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Construction and validation of a prognostic model for NK/T-cell lymphoma based on random survival forest algorithm by HUANG Zhen, HUANG Zhen, WU Yazhou

“…The patients were divided into a training cohort (n=471) and a validation cohort (n=203) in a 7∶3 ratio. …”
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