Obesity Prediction Using Synthetic Minority Oversampling Technique for Numeric and Continous and XGBoost Approaches by Tiara Azahra Wika Putri, Umu Sa’adah, Ummu Habibah

“…This study investigates the effect of using SMOTE-NC on the XGBoost algorithm in predicting obesity. The main objective of this research is to determine the effect of implementing SMOTE-NC and also the features that are most influential in the prediction process. …”
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Research on global ship cargo capacity prediction based on multi-source heterogeneous data by Shuhang Chen, Zhihuan Wang, Zhihuan Wang, Tianye Lu, Jiayang Zhu, Chunchang Zhang, Chunchang Zhang, Xiangming Zeng, Xiangming Zeng, Jiayi Wang, Zandi Shang, Zandi Shang

“…Results demonstrate that the K-nearest neighbors (KNN) algorithm achieves 88% predictive accuracy on validation data—a 19-percentage-point improvement over conventional methods (69%). …”
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GARMT: Grouping-Based Association Rule Mining to Predict Future Tables in Database Queries by Peixiong He, Libo Sun, Xian Gao, Yi Zhou, Xiao Qin

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Ways to predict interstitial lung disease in patients with systemic sclerosis: results of an observational study by D. V. Khorolsky, A. A. Klimenko, E. S. Pershina, N. M. Babadeva, A. A. Kondrashov, N. A. Shostak, E. P. Mikheeva, E. V. Zhilyaev

“…Classification trees (CTr) were constructed to predict the development of widespread ILD using the CHAID algorithm (exhaustive). …”
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Prediction of Moisture Content in Kiwi (Actinidia deliciosa) Dried Using Machine Learning Approaches by Halil Nusret BULUS, Soner CELEN

“… Predicting product drying kinetics is crucial for achieving optimal drying processes without compromising product quality. …”
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Multi-feature fusion-based consumer perceived risk prediction and its interpretability study. by Lin Qi, Yunjie Xie, Qianqian Zhang, Jian Zhang, Yanhong Ma

“…Using the PCA-K-medoids-XGBoost algorithm, we developed a predictive model for perceived risk. …”
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Research on Active Anti-collision Method of Unmanned Mine Truck Based on Predicted Trajectory by LI Cheng, ZHANG Qian, WANG Bin

“…Then, collision prediction is made on the predicted trajectory, and the OBB (oriented bounding box) collision detection method is used to find the nearest vehicle according to the current position of the vehicle. …”
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Predicting electromagnetically induced transparency based cold atomic engines using deep learning by Manash Jyoti Sarmah, Himangshu Prabal Goswami

“…We develop an artificial neural network model to predict quantum heat engines working within the experimentally realized framework of electromagnetically induced transparency. …”
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Global intraspecific diversity of marine forests of brown macroalgae predicted by past climate conditions by Eliza Fragkopoulou, Ester A. Serrão, Olivier De Clerck, Jorge Assis

“…Here, we explain and predict the genetic diversity of cold and temperate brown macroalgae using genetic data from 29 species and a machine-learning algorithm that incorporates contemporary and past climate conditions during the Last Glacial Maximum (~20,000 years ago) based on the niche centroid hypothesis. …”
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Conjugate Cellular Automata and Neural Network Approach: Failure Load Prediction of Masonry Panels by Iuliia Glushakova, Qihan Liu, Yu Zhang, Guangchun Zhou

“…The NN uses a backpropagation algorithm and two hidden layers with sigmoid activation functions to predict failure loads. …”
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Nonlinear Autoregressive Neural Network and Extended Kalman Filters for Prediction of Financial Time Series by Ghassane Benrhmach, Khalil Namir, Abdelwahed Namir, Jamal Bouyaghroumni

“…We examine the use of the nonlinear autoregressive neural network method as a prediction technique for financial time series and the application of the extended Kalman filter algorithm to improve the accuracy of the model. …”
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Forecasting CO2 emissions in BRICS countries using the grey breakpoint prediction models by Huiping Wang, Xinge Guo

“…Abstract In this paper, three novel grey breakpoint prediction models are proposed based on calculating the development coefficient and grey action of grey prediction models after fuzzy breakpoints, unifying the calculation methods for parameter estimation and the relevant time-response equations, and using the particle swarm optimisation algorithm to optimise the two-stage background values. …”
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PREDICTING STUNTING IN TODDLERS IN WEST JAVA USING LINEAR REGRESSION BASED ON POVERTY LEVELS by Nabila Aulia Rahmah, Nabila Khairunisa, Naufal Ammar Hidayatulloh, Ultach Enri

“…The aim of this research is to use the linear regression method based on the proportion of poverty to predict the risk of stunting in children under five in West Java. …”
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Best practices in the laboratory diagnosis, prognostication, prediction, and monitoring of Graves’ disease: role of TRAbs by Sanjay Kalra, Shahjada Selim, Dina Shrestha, Noel Somasundaram, Syed Abbas Raza, Manash P. Baruah, Saptarshi Bhattacharya, Sharvil Gadve, Ganapathi Bantwal, Rakesh Sahay

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Accuracy Assessment of Tomato Harvest Working Time Predictions from Panoramic Cultivation Images by Hiroki Naito, Tomohiko Ota, Kota Shimomoto, Fumiki Hosoi, Tokihiro Fukatsu

“…The system integrates a deep learning model, the Mask ResNet-50 convolutional neural network, to count harvestable fruits from images and a predictive algorithm to estimate working time based on the fruit count. …”
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PICNIC accurately predicts condensate-forming proteins regardless of their structural disorder across organisms by Anna Hadarovich, Hari Raj Singh, Soumyadeep Ghosh, Maxim Scheremetjew, Nadia Rostam, Anthony A. Hyman, Agnes Toth-Petroczy

“…PICNIC successfully predicts condensate members by learning amino acid patterns in the protein sequence and structure in addition to the intrinsic disorder. …”
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Predicting shear capacity of Recycled Aggregate Concrete beams using Artificial Neural Network by Ha HOANG, Tuan-Dung PHAM, Xuan-Tung NGUYEN, Minh Van NGO

“…This study investigates the application of an Artificial Neural Network (ANNs) utilizing a Multi-Layer Perceptron (MLP) architecture to predict the shear capacity of Recycled Aggregate Concrete (RAC) beams. …”
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Remaining Useful Life Prediction of Aero-Engine Based on Improved GWO and 1DCNN by Lihua Shen, Yucheng Wang, Baorui Du, Hailong Yang, He Fan

“…To mitigate the local optimum entrapment inherent in deep learning hyperparameter optimization, an improved Gray Wolf Optimizer incorporating dynamic perturbation factors is proposed. This algorithm is subsequently deployed to optimize hyperparameters within the redesigned predictive architecture. …”
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Traffic Conflict Prediction for Sharp Turns on Mountain Roads Based on Driver Behavior Patterns by Quanchen Zhou, Jiabao Zuo, Yafei Zhao, Mingwu Ren

“…The findings showed that unsafe driver behavior on sharp turns was common, while the combination of “speeding–tailgating–frequent lane changing” behavior increased conflict risk by 3.7 times. A predictive LSTM neural network model was developed with driver, vehicle, road, and environmental factors. …”
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Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems by Jun Zha, Xiaofei Peng, Zhiyan Cai, Fei Xue

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