Machine learning model for classifying high school students’ academic performance in mathematics amidst the COVID-19 context by Gisella Luisa Elena Maquen-Niño, Moisés Alvin Miguel_Flores, Leysi Yarely Aurich_Mio, Ivan Adrianzén Olano, Percy Edwin De la Cruz Vélez de Villa, Diana Mercedes Castro Cárdenas

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Optimizing electric vehicle energy consumption prediction through machine learning and ensemble approaches by Izhar Hussain, Kok Boon Ching, Chessda Uttraphan, Kim Gaik Tay, Adeeb Noor, Sufyan Ali Memon

“…Among the optimization techniques, Optuna proves to be the most effective for tuning the KNN model. …”
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A Tunnel Lining Line Identification Algorithm Based on Supervised Heatmap by Heng SONG, Yisheng ZHANG, Tianbao GENG, Dongjie WANG

“…Therefore, using 8~10 outer points to supervise model learning in the first 10 rounds yields the most significant improvements. …”
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Algorithm of reconstruction combined midface defects after resection malignant tumors by M. V. Bolotin, A. M. Mudunov, V. Yu. Sobolevsky, V. I. Sokorutov

“…The purpose of reconstruction is not only the elimination of cosmetic deformity, but also the restoration of such vital functions as breathing, swallowing, speech and binocular vision. Till that time, no algorithm has been developed for choosing a method for the reconstruction and there is no comparative analysis of the available methods.The study objective is to improve the functional and aesthetic results of treatment patients with malignant tumors of the upper jaw and midface.Materials and methods. …”
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Shape Optimization of Multi-chamber Acoustical Plenums Using the BEM, Neural Networks, and the GA Method by Ying-Chun CHANG, Ho-Chih CHENG, Min-Chie CHIU, Yuan-Hung CHIEN

“…The results reveal that the maximum value of the transmission loss (TL) can be improved at the desired frequencies. Consequently, the algorithm proposed in this study can provide an efficient way to develop optimal multi-chamber plenums for industry.…”
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Bandit Algorithms for Efficient Toxicity Detection in Competitive Online Video Games by Jacob Morrier, Rafal Kocielnik, R. Michael Alvarez

“…Using data from the popular first-person action game Call of Duty®: Modern Warfare® III, we show that our algorithm consistently outperforms baseline algorithms that rely solely on individual players’ past behavior, achieving improvements in detection rate of up to 24.56 percentage points or 51.5%. …”
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Wafer Defect Classification Algorithm With Label Embedding Using Contrastive Learning by Jeongjoon Hwang, Somi Ha, Dohyun Kim

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A hybrid model based on learning automata and cuckoo search for optimizing test item selection in computerized adaptive testing by Chanjuan Jin, Weiming Pan

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Influence of soil parameters on dynamic compaction: numerical analysis and predictive modeling using GA-optimized BP neural networks by Yu Zhang, Xueshui Chen, Huakang Ge, Zhigang Guo, Xu Li

“…Orthogonal experimental design and single factor analysis were used to quantify the influence of each parameter on the compaction volume. In order to improve the prediction accuracy, this paper introduces genetic algorithm (GA) to optimize the BP neural network model, constructs a multi-factor dynamic compaction prediction model, and compares it with the traditional BP model. …”
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Recurrent academic path recommendation model for engineering students using MBTI indicators and optimization enabled recurrent neural network by Anupama V, Sudheep Elayidom M

“…To address this issue, an intelligent recommendation model is proposed that assists students in discovering the most suitable academic path based on their personal background and personality traits. …”
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Construction of Clinical Predictive Models for Heart Failure Detection Using Six Different Machine Learning Algorithms: Identification of Key Clinical Prognostic Features by Qu FZ, Ding J, An XF, Peng R, He N, Liu S, Jiang X

“…Finally, a correlation analysis was conducted to examine the relationships between these features and other significant clinical features.Results: The logistic regression (LR) model was determined to be the optimal machine learning algorithm in this study, achieving an accuracy of 0.64, a precision of 0.45, a recall of 0.72, an F1 score of 0.51, and an AUC of 0.81 in the training set and 0.91 in the testing set. …”
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Hybrid Darknet53-SVM model with random grid search optimization for enhanced colorectal cancer histological image classification by Pragati Patharia, Prabira Kumar Sethy, K. Lakshmipathi Raju, Anita Khanna, Ashoka Kumar Ratha, Santi Kumari Behera, Aziz Nanthaamornphong

“…To enhance the classification performance, Darknet53 was hybridized with a SVM by replacing the dense layer, and hyperparameters were optimized using a Random Grid Search algorithm. The optimized hybrid model exhibited a remarkable improvement, with an Acc. of 99.7%, Sen. of 99.7%, Spec. of 99.91%, Prec. of 99.98%, and F1-score of 99.98%, alongside significant improvements in other metrics. …”
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Reconstruction of Highway Vehicle Paths Using a Two-Stage Model by Weifeng Yin, Junyong Zhai, Yongbo Yu

“…To address the challenge of multiple possible paths due to missing trajectory data, this study proposes a novel two-stage model for vehicle path reconstruction. In the first stage, a Gaussian Mixture Model (GMM) is integrated into a path choice model to estimate the mean and standard deviation of travel times for each road segment, utilizing an improved Expectation Maximization (EM) algorithm. …”
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A Mobile Agent Routing Algorithm in Dual-Channel Wireless Sensor Network by Kui Liu, Sanyang Liu, Hailin Feng

“…A mobile agent routing algorithm (MARA) is presented in this paper, and then based on the dual-channel communication model, the two-layer network combination optimization strategy is also proposed. …”
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Enhancing the prediction of groundwater quality index in semi-arid regions using a novel ANN-based hybrid arctic puffin-hippopotamus optimization model by Moustafa Gamal Snousy, Hussein M. Elshafie, Ashraf R. Abouelmagd, Najmaldin Ezaldin Hassan, Mahmoud E. Abd-Elmaboud, Ali Akbar Mohammadi, Ashraf M.T. Elewa, E. EL-Sayed, Ahmed M. Saqr

“…Study focus: This study presents a novel hybrid arctic puffin–hippopotamus optimization (HPHO) algorithm combined with an artificial neural network (ANN) to improve irrigation water quality index (IWQI) predictions in semi-arid areas. …”
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Mathematical Modeling of Optimal Drone Flight Trajectories for Enhanced Object Detection in Video Streams Using Kolmogorov–Arnold Networks by Aida Issembayeva, Oleksandr Kuznetsov, Anargul Shaushenova, Ardak Nurpeisova, Gabit Shuitenov, Maral Ongarbayeva

“…While most research focuses on improving detection algorithms, the relationship between flight parameters and detection performance remains poorly understood. …”
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Implementation of SVM Algorithm to Predict Song Popularity based on Sentiment Analysis of Lyrics by Quiin Latifah Almatin Lubis, Arif Akbarul Huda

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An optimal weighting-based hybrid classifier for Children's congenital heart diseases signal processing by Morteza Ebrahimpour, Mehdi Khashei

“…The main objective of the proposed optimal weighting-based CNN-LSTM-SVM (OCLS) hybrid classifier is to simultaneously leverage the unique advantages of CNN in feature extraction from input signals, LSTM in modeling the sequential patterns of signals, SVM in classifying regular patterns, and especially the proposed weighting algorithm to optimally integrate the outputs of these components. …”
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Identification of soil texture and color using machine learning algorithms and satellite imagery by Jiyang Wang

“…For future research, it is recommended to explore the combination of SVR with optimization techniques such as genetic algorithms to further improve the accuracy of soil texture and color predictions.…”
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Performance of machine learning algorithms to evaluate the physico-mechanical properties of nanoparticle panels by Derrick Mirindi, James Hunter, David Sinkhonde, Tajebe Bezabih, Frederic Mirindi

“…This review analyzes secondary data on nanoparticle integration in board production, aiming to evaluate the relationships among physical (water absorption (WA) and thickness swelling (TS)) and mechanical (modulus of rupture (MOR), modulus of elasticity (MOE); and internal bond (IB) strength) properties and to predict performance using machine learning (ML) algorithms. These algorithms include Pearson correlation, hierarchical clustering, and decision tree (DT) models. …”
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