A new adaptive grey prediction model and its application by Jianming Jiang, Ming Zhang, Zhongyong Huang

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Transmission Error Prediction of RV Reducer based on SSA-BP by Houzhen Sun, Hongbing Yuan, Bin Yu

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Potential Biomarkers for Predicting the Risk of Developing Into Long COVID After COVID‐19 Infection by Zhiyong Hou, Yu Ming, Jun Liu, Zhong Wang

“…Among the 67 candidate genes were processed with machine learning algorithms and logistic regression, a subgroup consisting of CEP55, CDCA2, MELK, and DEPDC1B, was at last identified as potential biomarkers for predicting the risk of the progression into long COVID after COVID‐19 infections. …”
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Location, Location, Location: The Power of Neighborhoods for Apartment Price Predictions Based on Transaction Data by Christopher Kmen, Gerhard Navratil, Ioannis Giannopoulos

Subjects: “…real estate price prediction…”
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A Novel Deep Learner for Human Behavior Prediction Over Public Video Surveillance by Bayan Alabdullah, Bisma Batool Fatima, Haifa F. Alhasson, Mohammed Alshehri, Yahya AlQahtani, Nouf Albhassabi, Hui Liu

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PREDICTION OF THE POOR RATE K-MEANS AND GENERALIZED REGRESSION NEURAL NETWORK ALGORITHMS (CASE STUDY: NORTH SUMATRA PROVINCE) by Nita Suryani, Arnita Arnita, Rinjani Cyra Nabila, Amanda Fitria

“…In this study, poverty levels were mapped using the K-Means algorithm, and GRNN was then utilized for modeling and prediction. …”
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Prediction after a Horizon of Predictability: Nonpredictable Points and Partial Multistep Prediction for Chaotic Time Series by Vasilii A. Gromov, Philip S. Baranov

“…The resulting strategy demonstrates accurate results for both benchmark and real-world time series, with the number of predicted steps exceeding that of any other published algorithm.…”
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Application of Machine Learning Algorithms in Real-Time Monitoring of Conveyor Belt Damage by Damian Bzinkowski, Miroslaw Rucki, Leszek Chalko, Arturas Kilikevicius, Jonas Matijosius, Lenka Cepova, Tomasz Ryba

“…Similarly, identification of the preset damage was possible using machine learning algorithms, demonstrating the feasibility of the system for fault diagnosis and predictive maintenance.…”
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Comparison and Analysis of Algorithms for Coordinated EV Charging to Reduce Power Grid Impact by Cesar Diaz-Londono, Paolo Maffezzoni, Luca Daniel, Giambattista Gruosso

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Application of Battery Life Prediction Technology in EMUs by DAI Yi, YU Tianjian, CHENG Shu, WU Xun, LIU Jiawen

Subjects: “…remaining useful life(RUL) prediction…”
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Heart Disease Prediction Using a Hybrid Feature Selection and Ensemble Learning Approach by Isha Gupta, Anu Bajaj, Manav Malhotra, Vikas Sharma, Ajith Abraham

“…This study leverages the UCI heart disease dataset to assess the effectiveness of various Machine Learning models in predicting heart diseases. This paper proposed an advanced prediction method that combines feature selection using a hybrid of Genetic Algorithm (GA) and Cuckoo Search Optimization (CSO) with a majority voting ensemble of Convolutional Neural Network and Random Forest. …”
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Predicting Wastewater Characteristics Using Artificial Neural Network and Machine Learning Methods for Enhanced Operation of Oxidation Ditch by Igor Gulshin, Nikolay Makisha

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Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads by Bingbing Li, Weichao Zhuang, Boli Chen, Hao Zhang, Sheng Yu, Jianrun Zhang, Guodong Yin

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Research on formant estimation algorithm for high order optimal LPC root value screening by Hua LONG, Shumeng SU

“…Objectives: The existing linear prediction (LP) formant estimation algorithms are difficult to locate formant precisely because of the pseudo root interference and interaction between poles.Because of the low order fitting formant of LP prediction,the accuracy of formant extraction is fundamentally limited.It is difficult to remove false roots and spectrum aliasing caused by pole interaction in the formant extraction of high-order LP.In order to solve the problem of large error of LP formant detection,a formant estimation algorithm based on high-order LP coefficient root value screening was proposed. …”
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AQSA—Algorithm for Automatic Quantification of Spheres Derived from Cancer Cells in Microfluidic Devices by Ana Belén Peñaherrera-Pazmiño, Ramiro Fernando Isa-Jara, Elsa Hincapié-Arias, Silvia Gómez, Denise Belgorosky, Eduardo Imanol Agüero, Matías Tellado, Ana María Eiján, Betiana Lerner, Maximiliano Pérez

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Research Progress on Machine Learning Prediction of Compressive Strength of Nano-Modified Concrete by Ruyan Fan, Ankang Tian, Yikun Li, Yue Gu, Zhenhua Wei

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Ensemble Learning-Based Metamodel for Enhanced Surface Roughness Prediction in Polymeric Machining by Elango Natarajan, Manickam Ramasamy, Sangeetha Elango, Karthikeyan Mohanraj, Chun Kit Ang, Ali Khalfallah

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Explainable and Interpretable Model for the Early Detection of Brain Stroke Using Optimized Boosting Algorithms by Yogita Dubey, Yashraj Tarte, Nikhil Talatule, Khushal Damahe, Prachi Palsodkar, Punit Fulzele

“…<b>Results:</b> The performance of three boosting algorithms is studied for stroke prediction, which include Gradient Boosting (GB), AdaBoost (ADB), and XGBoost (XGB) with XGB achieved the best outcome overall with a training accuracy of 96.97% and testing accuracy of 92.13%. …”
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Comparative Study of Sphere Decoding Algorithm and FCS-MPC for PMSMs in Aircraft Application by Joseph O. Akinwumi, Yuan Gao, Xin Yuan, Sergio Vazquez, Harold S. Ruiz

“…In this study, we propose a long prediction horizon finite control set model predictive control (FCS-MPC) framework for PMSMs. …”
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Study on an interpretable prediction model for pile bearing capacity based on SHAP and BP neural networks by Shunbo Li, Mingwei Hai, Qi Zhang, Bin Zhou, Miao Wang, Zhuo Zhao

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