Parameter estimation in solar power plant systems: a comparative study of recursive and iterative techniques by Kiavash Hossein Sadeghi, Mahmood Shafikhah, Arash Marashian, Emad Roshandel, Abolhassan Razminia

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Current Applications, Challenges, and Future Directions of Artificial Intelligence in Emergency Medicine: A Narrative Review by Mehrdad Farrokhi, Amir H Fallahian, Erfan Rahmani, Ali Aghajan, Morteza Alipour, Parisa Jafari Khouzani, Hossein Boustani Hezarani, Hamed Sabzehie, Mohammad Pirouzan, Zahra Pirouzan, Behnaz Dalvandi, Reza Dalvandi, Parisa Doroudgar, Habib Azimi, Fatemeh Moradi, Amitis Nozari, Maryam Sharifi, Hamed Ghorbani, Sara Moghimi, Fatemeh Azarkish, Soheil Bolandi, Hooman Esfahani, Sara Hosseinmirzaei, Arezou Niknam, Farzaneh Nikfarjam, Parham Talebi Boroujeni, Mahyar Noorbakhsh, Parham Rahmani, Fatemeh Rostamian Motlagh, Khadijeh Harati, Masoud Farrokhi, Sina Talebi, Lida Zare Lahijan

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Machine learning ensemble technique for exploring soil type evolution by Xiangyuan Wu, Kening Wu, Shiheng Hao, Er Yu, Jinghui Zhao, Yan Li

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Urban intersection traffic flow prediction: A physics-guided stepwise framework utilizing spatio-temporal graph neural network algorithms by Yuyan Annie Pan, Fuliang Li, Anran Li, Zhiqiang Niu, Zhen Liu

“…Compared to traditional models such as ARIMA, KNN, and Random Forest, PG-STGNN significantly improves prediction accuracy, achieving MAPE reductions of 19.9 %, 18.6 %, 6.1 %, 20.7 %, 5.0 %, 1.8 %, and 1.1 % against KNN, ARIMA, RF, BP, T-GCN, STGCN, and ST-ED-RMGC, respectively. …”
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The application of machine learning algorithms for predicting length of stay before and during the COVID-19 pandemic: evidence from Wuhan-area hospitals by Yang Liu, Yang Liu, Renzhao Liang, Chengzhi Zhang

“…We employed six machine learning algorithms to predict the probability of LOS.ResultsAfter implementing variable selection, we identified 35 variables affecting the LOS for COVID-19 patients to establish the model. …”
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Forward Predicting Chromatic-Optical Parameters of the Mixed Light of White-Red Light-Emitting Diode Configurations Based on Deep Learning Algorithms by Songsheng Lin, Huanting Chen, Yin Zheng, Quanji Xie, Xuehua Shen, Huichuan Lin, Shuo Lin, Yan Li

“…Four deep learning algorithms were evaluated. Each model was trained to reconstruct the SPD curves and predict the corresponding optical and chromatic parameters. …”
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Optimizing Pile Bearing Capacity Prediction Using Specific Random Forest Models Optimized by Meta-Heuristic Algorithms for Enhanced Geomechanically Applications by Nengyuan Chen

“…To achieve highly accurate predictions of Pile Bearing Capacity (PBC), the study employs a cutting-edge approach featuring Specific Random Forest (RF) prediction models, strategically enhanced with two potent meta-heuristic algorithms: the Snake Optimizer (SO) and the Equilibrium Optimizer (EO). …”
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Predicting low birth weight risks in pregnant women in Brazil using machine learning algorithms: data from the Araraquara cohort study by Audêncio Victor, Francielly Almeida, Sancho Pedro Xavier, Patrícia H.C. Rondó

“…Abstract Background Low birth weight (LBW) is a critical factor linked to neonatal morbidity and mortality. Early prediction is essential for timely interventions. This study aimed to develop and evaluate predictive models for LBW using machine learning algorithms, including Random Forest, XGBoost, Catboost, and LightGBM. …”
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A Review of Reliability Assessment and Lifetime Prediction Methods for Electrical Machine Insulation Under Thermal Aging by Jian Zhang, Jiajin Wang, Hongbo Li, Qin Zhang, Xiangning He, Cui Meng, Xiaoyan Huang, Youtong Fang, Jianwei Wu

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Daily Runoff Prediction Model Based on Multivariate Variational Mode Decomposition and Correlation Reconstruction by DING Jie, TU Peng-fei, FENG Yu, ZENG Huai-en

“…Then, the Microbial Enhanced Algorithm-Back Propagation(MEA-BP) model was used for multiple predictions, and the average values were taken, and evaluation indicators were employed to assess the seven operating conditions. …”
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A novel wind speed prediction model based on neural networks, wavelet transformation, mutual information, and coot optimization algorithm by Faezeh Amirteimoury, Farshid Keynia, Elaheh Amirteimoury, Gholamreza Memarzadeh, Hanieh Shabanian

“…To tackle this issue, this paper proposes a new wind speed prediction model that combines four techniques: Discrete Wavelet Transform, which smooths the wind speed signal; Mutual Information, which selects the most informative part of the wind speed time series; Coot Optimization Algorithm for optimal feature selection; and Bidirectional Long Short-Term Memory for capturing complex patterns. …”
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A Finite Control Set Model Predictive Control Algorithm With Low Complexity for Neutral-Point Clamped Converters With Switching Constraints by Dimas A. Schuetz, Fernanda de M. Carnielutti, Mokhtar Aly, Margarita Norambuena, Jose Rodriguez, Humberto Pinheiro

“…This paper proposes a Finite Control Set Model Predictive Control algorithm with low complexity for three-phase grid-tied Neutral-Point Clamped converters with switching constraints. …”
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Enhanced Prediction of California Bearing Ratio (CBR) Values in Geotechnical Engineering Using Decision Tree Algorithm and Meta-Heuristic Optimizations by Linda Davies, Dominik Jánošík

“…This paper presents a novel approach to the accurate prediction of CBR values. Using the DT algorithm, the method creates complex and incredibly accurate predictive models. …”
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Modeling and Predicting the Changes in Hearing Loss of Workers with the Use of a Neural Network Data Mining Algorithm: A Field Study by Sajad ZARE, Mohammad Reza GHOTBIRAVANDI, Hossein ELAHISHIRVAN, Mostafa Ghazizadeh AHSAEED, Mina ROSTAMI, Reza ESMAEILI

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Advanced reference crop evapotranspiration prediction: a novel framework combining neural nets, bee optimization algorithm, and mode decomposition by Ahmed Elbeltagi, Okan Mert Katipoğlu, Veysi Kartal, Ali Danandeh Mehr, Sabri Berhail, Elsayed Ahmed Elsadek

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A Hierarchical Control Algorithm for a Pursuit–Evasion Game Based on Fuzzy Actor–Critic Learning and Model Predictive Control by Penglin Hu, Chunhui Zhao, Quan Pan

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Bus Arrival Time Prediction Based on the Optimized Long Short-Term Memory Neural Network Model With the Improved Whale Algorithm by Bing Zhang, Lingfeng Tang, Dandan Zhou, Kexin Liu, Yunqiang Xue

“…This article proposes using the improved whale optimization algorithm–long short-term memory (IWOA–LSTM) model to predict bus arrival times and improving the whale algorithm by optimizing the hyperparameters of the LSTM model, so that the advantages and disadvantages of the whale algorithm and the LSTM model can complement each other, thus enhancing the robustness of the model. …”
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An online clustering algorithm predicting model for prostate cancer based on PHI-related variables and PI-RADS in different PSA populations by Jiyuan Hu, Qi Miao, Jiayi Ren, Hongbo Su, Xianlu Zhang, Jianbin Bi, Gejun Zhang

“…Some researches have created nomograms for predicting risk, but these are not easily visualized. …”
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DGCA3QM: DESIGN OF A DUAL GENETIC ALGORITHM BASED AUTOREGRESSION MODEL FOR CORRELATIVE PREDICTION OF AIR QUALITY METRICS by Harna M. Bodele, G. M. Asutkar, Kiran G. Asutkar

“…To overcome these issues, this text proposes design of a Dual Genetic Algorithm (DGA) based Auto regression model for Correlative prediction (AC) of Air Quality Metrics. …”
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A diagnostic prediction model for anti-neutrophil cytoplasmic antibody associated vasculitis combined with glomerulonephritis based on machine learning algorithm by Wang Jian-mei, Zhu Ge-li, Cao Chen-lin, Peng Qing-quan

“…RF and artificial neural network algorithms were jointly used to further screen characteristic genes. …”
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