Predictions of failed satellite retrieval of air quality using machine learning by E. Malina, E. Malina, J. Brence, J. Adams, J. Tanevski, J. Tanevski, S. Džeroski, S. Džeroski, V. Kantchev, K. W. Bowman

“…Depending on the instrument and algorithm, the yield of good remote soundings can be a few percent owing to interferences such as clouds, non-linearities in the retrieval algorithm, and systematic errors in the radiative transfer algorithm, leading to inefficient use of computational resources. …”
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Prediction Model of Music Popular Trend Based on NNS and DM Technology by Yichen Xu, Mingxun Wang, Hao Chen, Fan Hu

“…In the prediction of the number of songs played by 10 artists, the NNS algorithm proposed in this paper reduces the prediction effect from the original 0.074 and 0.045 to 0.044 and 0.032, respectively, and the error rates are reduced by 35.7% and 29.4%, respectively, compared with the learning algorithm and the decision tree algorithm. …”
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The Improved Antlion Optimizer and Artificial Neural Network for Chinese Influenza Prediction by Hongping Hu, Yangyang Li, Yanping Bai, Juping Zhang, Maoxing Liu

“…It is shown that the predicted model IALO-BPNN has smaller errors than other six predicted models, which illustrates that the IALO has potentiality to optimize the weights and basis of BP neural network for predicting the Chinese influenza effectively. …”
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Local Differential Privacy Graph Data Modeling Method for Link Prediction by HANQilong, WUXiaoming

“…The simulation experiments show that the PSRR-LDP algorithm has better link prediction performance while ensuring privacy.…”
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Demand Prediction of Emergency Supplies under Fuzzy and Missing Partial Data by Ming Zhang, Hanlin Wu, Zhifeng Qiu, Yifan Zhang, Boquan Li

“…Weights were introduced in the filling and logic test conditions were added after filling so that filling results were of higher truthfulness and accuracy. (3) The preprocessed data are input into the improved algorithm based on the genetic algorithm and BP neural networks (GABP) to obtain the demand prediction model. …”
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Needle in a haystack: Harnessing AI in drug patent searches and prediction. by Leonardo Costa Ribeiro, Valbona Muzaka

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Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

“…Finally, aiming at improving the bearing fault prediction accuracy, the GWO algorithm is used to optimize the parameters. …”
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PV Polaris – Automated PV System Orientation Prediction by Ernst Wittmann, Claudia Buerhop-Lutz, Savannah Bennett, Vincent Christlein, Jens Hauch, Christoph J. Brabec, Ian Marius Peters

“…This study introduces an automated Monte Carlo Search based algorithm called PV Polaris which is capable of predicting the systems orientation within 18 s, with uncertainties of less than 2° in tilt and 4° in azimuth. …”
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Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index by Hadisuwito et al.

“…Therefore, we need an algorithm that can predict the dryness factor. So, the most significant fire potential can be predicted during the dry season. …”
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Quality Prediction Model Based on Novel Elman Neural Network Ensemble by Lan Xu, Yuting Zhang

“…In this paper, we propose a novel prediction algorithm based on an improved Elman neural network (NN) ensemble for quality prediction, thus achieving the quality control of designed products at the product design stage. …”
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Cost Index Predictions for Construction Engineering Based on LSTM Neural Networks by Jiacheng Dong, Yuan Chen, Gang Guan

“…The present study proposed a new framework based on LSTM, so as to explore the applicability and optimization mechanism of the algorithm in the field of cost indexes prediction. …”
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The TB27 Transcriptomic Model for Predicting Mycobacterium tuberculosis Culture Conversion by Maja Reimann, Korkut Avsar, Andrew DiNardo, Torsten Goldmann, Gunar Günther, Michael Hoelscher, Elmira Ibraim, Barbara Kalsdorf, Stefan Kaufmann, Niklas Köhler, Anna Mandalakas, Florian Maurer, Marius Müller, Dörte Nitschkowski, Ioana Olaru, Cristina Popa, Andrea Rachow, Thierry Rolling, Helmut Salzer, Patricia Sanchez-Carballo, Maren Schuhmann, Dagmar Schaub, Victor Spinu, Elena Terhalle, Markus Unnewehr, Nika Zielinski, Jan Heyckendorf, Christoph Lange

“…Methods: Using a multi-step machine learning algorithm to identify an RNA-based algorithm to predict the remaining time to culture conversion at flexible time points during anti-tuberculosis therapy.  …”
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Human Heart Disease Prediction System Using Data Mining Techniques by Sidra Javed, Hamza Javed, Ayesha Saddique, Beenish Rafiq

“…To address this problem, Decision Tree is used to predict the heart disease. In this study the collected data is pre-processed, Decision Tree algorithm and ID3 were then applied to predict the heart disease.   …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. …”
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Hysteretic curve characteristics in rectangular shear walls predicted by machine learning by Jungui Dong, Ce Chen

“…An interpretable empirical guidance machine learning (IEG-ML) was proposed for predicting these feature points. IEG-ML aligns with empirical trends from extensive experiments and is explainable via explicit formulas. …”
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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…With the development of financial technology, the traditional experience-based and single-network credit default prediction model can no longer meet the current needs. …”
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A Local–Global Graph KAN for Multi‐Class Prediction of PPI by Minghui Liu, Ying Qu

“…Therefore, using machine learning to treat multiple PPI predictions as binary classifications has become an alternative, but there is a problem of data imbalance. …”
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An Inference Framework of Markov Logic Network for Link Prediction in Heterogeneous Networks by Zhongbin Li, Kun Yue, Lixing Yu, Jiahui Wang

“…The presence of multiplex edges and sparse links often hampers the efficacy of link prediction (LP) tasks. By harnessing the expressive power of Markov logic network (MLN) formulations, multiplex edges can be unified to enhance LP effectiveness. …”
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