Prediction and optimization of acoustic absorption performance of quasi-Helmholtz acoustic metamaterials based on LightGBM algorithm by Jianxin Xu, Weikang Mao, Xiaoqian Yu, Bingfei Liu

“…This thesis aims to optimize and predict the acoustic absorption performance of quasi-Helmholtz acoustic metamaterials by using LightGBM algorithm in machine learning. …”
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355 Validation of an artificial intelligence Algorithm for predicting diagnosis-related groups in a community health system by Angela Muhanga, King Jason, Xsolis Mueller, Jennifer L. Sanger, Julie M. Bartlett, Brian N. Manz, James W. Spiten, Matthew J. Overgaard, Shauna M. Wang Hanyin

“…This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. …”
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Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

“…The optimal amount of data was determined to be between three and seven days, with an average model r² of 0.8811 and an RMSE of 2.056 for the gated recurrent unit algorithm. This study verified the possibility of developing a predictive model for the internal environment of a greenhouse based on weather data from outside. …”
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An enhanced adaptive dynamic metaheuristic optimization algorithm for rainfall prediction depends on long short-term memory by Ahmed M. Elshewey, Amel Ali Alhussan, Doaa Sami Khafaga, Marwa Radwan, El-Sayed M. El-kenawy, Nima Khodadadi

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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

“…In the first step, a random forest algorithm was employed to assess the predictive power of the seven working capital management indicators in classifying companies as distressed or healthy. …”
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Novel deep learning algorithm based MRI radiomics for predicting lymph node metastases in rectal cancer by Weiqun Ao, Sikai Wu, Neng Wang, Guoqun Mao, Jian Wang, Jinwen Hu, Xiaoyu Han, Shuitang Deng

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Remaining useful life prediction of Lithium-ion batteries based on data preprocessing and CNN-LSSVR algorithm by Ti Dong, Yiming Sun, Jia Liu, Qiang Gao, Chunrong Zhao, Wenjiong Cao

“…Eventually, the CNN-LSSVR algorithm and mutant particle swarm optimisation algorithm are utilised to solve the mapping regression and hyper-parameter optimisation problems, respectively, to achieve a complete prediction of RUL. …”
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A preference random walk algorithm for link prediction through mutual influence nodes in complex networks by Kamal Berahmand, Elahe Nasiri, Saman Forouzandeh, Yuefeng Li

“…Predicting links in complex networks has been one of the essential topics within the realm of data mining and science discovery over the past few years. …”
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Feature selection using a multi-strategy improved parrot optimization algorithm in software defect prediction by Qi Fei, Guisheng Yin, Zhian Sun

“…This study proposes a novel feature selection and defect prediction classification algorithm based on a multi-strategy enhanced Parrot Optimization (PO) algorithm. …”
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Development of a LASSO machine learning algorithm-based model for postoperative delirium prediction in hepatectomy patients by Yu Zhu, Renrui Liang, Ying Wang, Jian-Jun Yang, Ning Zhou, Cheng-Mao Zhou

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HPRNA: Predicting synergistic drug combinations for angina pectoris based on human pathway relationship network algorithm. by Mengyao Zhou, Mengfan Xu, Xiangling Zhang, Xiaochun Xing, Yang Li, Guanghui Wang, Guiying Yan

“…In this paper, we introduce a novel mathematical algorithm, the Human Pathway Relationship Network Algorithm (HPRNA), which is designed to predict synergistic drug combinations for angina pectoris. …”
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Prediction of Soil Liquefaction Using a Multi-Algorithm Technique: Stacking Ensemble Techniques and Bayesian Optimization by Long Tsang, Mahdi Akbari, Pouyan Fakharian

“…A Bayesian optimization method is also used to improve the accuracy of the predictions of soil liquefaction by adjusting the hyperparameters of these four classification algorithms. …”
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Comparative Analysis of the Proportional Distribution Method and the Random Forest Algorithm for Predicting Pedestrian Traffic Accident Risk by Hristo V. Uzunov, Plamen G. Matzinski, Vasil H. Uzunov, Silvia V. Dechkova

“…This study presents a comparative analysis of two methodologies for predicting the risk of pedestrian traffic accidents: a methodology based on proportional risk distribution and the Random Forest algorithm. …”
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Rainfall Prediction in Khorasan Razavi Stations Using a Hybrid Neural Network and Genetic Algorithm Approach by Mahdi Naseri, Mahsa Mardani

Subjects: “…genetic algorithm…”
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Predicting Metabolite-Disease Associations Based on Linear Neighborhood Similarity with Improved Bipartite Network Projection Algorithm by Xiujuan Lei, Cheng Zhang

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Utilizing an Innovative Gaussian Process Regression Machine Learning Algorithm for Estimating Unconfined Compressive Strength Predictions by Hazel Abraham

“…This article offers an advanced argument in using a Machine Learning algorithm known as Gaussian Process Regression to predict the UCS for mixtures of soils. …”
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Prediction of Mechanical Properties of Cotton Fibers by a BP Neural Network Model Optimized by Genetic Algorithm by Junyang Wang, Limin Zhang, Xiang Liu, Jinchan Zhang, Wanxin Wang, Hong Xu

“…In this experiment, a general purpose BP neural network (BP) based on genetic algorithm (GA) was developed for predicting fiber properties. …”
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Algorithm for link prediction in self-regulating network with adaptive topology based on graph theory and machine learning by Evgeny Y. Pavlenko

“…On the basis of the developed model of network functioning with adaptive topology, a graph algorithm for link prediction is proposed, which is extended to the case of peer-to-peer networks. …”
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Optimization of Electric Transformer Operation Through Load Estimation Based on the K-Means Algorithm by Pedro Torres-Bermeo, José Varela-Aldás, Kevin López-Eugenio, Nancy Velasco, Guillermo Palacios-Navarro

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Hybrid Machine Learning Model for Predicting Shear Strength of Rock Joints by Daxing Lei, Yaoping Zhang, Zhigang Lu, Hang Lin, Yifan Chen

“…However, traditional machine learning (ML) models often suffer from local optima and limited generalization ability when dealing with complex nonlinear problems, thereby compromising prediction accuracy and stability. To address these challenges, this study proposes a hybrid ML model that integrates a multilayer perceptron (MLP) with the slime mold algorithm (SMA), termed the SMA-MLP model. …”
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