Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

“… This research aimed to automate the fitting of kinetic models using genetic algorithms (GAs) to optimize the estimation of kinetic parameters—the reaction rate constant (k) and the initial value of total titratable acidity (TTA, C₀)—and enhance predictive accuracy. …”
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Integrating Machine Learning Algorithms to Construct a Triaptosis-Related Prognostic Model in Melanoma by Xie J, Zhang M, Qi M

“…The TCGA-SKCM cohort served as the training dataset, and GEO datasets were used for validation.Results: A robust prognostic model based on triaptosis-associated signature (TAS) was established using the SurvivalSVM algorithm. This model showed superior predictive performance, with consistently high concordance index (C-index) values across independent validation datasets. …”
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Integration of Machine Learning and Wavelet Algorithms for Processing Probing Signals: An Example of Oil Wells by Zukhra Abdiakhmetova, Zhanerke Temirbekova

“…Furthermore, machine learning models, including standard regression algorithms and neural networks, are leveraged to enhance signal interpretation and predictive capabilities. …”
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Cutting-Edge Stochastic Approach: Efficient Monte Carlo Algorithms with Applications to Sensitivity Analysis by Ivan Dimov, Rayna Georgieva

“…In recent years, researchers have developed advanced algorithms based on the analysis of variance (ANOVA) technique for computing numerical sensitivity indicators. …”
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Using Deep Learning algorithms to detect the success or failure of the Electroconvulsive Therapy (ECT) sessions by usef faghihi, Cyrus kalantarpour

“…So far, to our knowledge, researchers have used multi-parametric magnetic resonance imaging (MRI) techniques combined with statistical methods and/or linear machine learning algorithms to predict patients’ responses to ECT. However, the aforementioned methods are very expensive and time-consuming. …”
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Identification and verification of diagnostic biomarkers for deep infiltrating endometriosis based on machine learning algorithms by Shanping Shi, Chao Huang, Xiaojian Tang, Hua Liu, Weiwei Feng, Chen Chen

“…By analyzing the GSE141549 dataset from the Gene Expression Omnibus (GEO) database, using bioinformatics methods and three machine learning algorithms (LASSO, Random Forest, and Support Vector Machine), the key feature gene USP14 was identified. …”
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Sensitivity and Performance Evaluation of Multiple-Model State Estimation Algorithms for Autonomous Vehicle Functions by Olivér Törő, Tamás Bécsi, Szilárd Aradi, Péter Gáspár

“…The paper examines the suitability of different probabilistic state estimation methods, namely, the Extended Kalman Filter (EKF) and the more general Particle Filter (PF) with the addition of the Interacting Multiple Model (IMM) approach. These algorithms are not capable of predicting motion for long term in road traffic conditions, though their robustness and model classification capability are essential for the overall system. …”
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AUTOMATIC ALGORITHMS OF AGRICULTURAL FIELDS SEGMENTATION ON AERIAL IMAGES FOR REMOTE SENSING AND ENVIRONMENTAL MONITORING by V. A. Kovalev, A. A. Kalinovsky, A. A. Dmitruk, V. A. Liauchuk

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Comparison of Single Exponential Smoothing and Double Moving Average Algorithms to Forecast Beef Production by Tundo, Rachmat Hidayat Insani, Rasiban, Untung Suropati

“…The two algorithms are compared to get the lowest error rate. …”
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Comparative Analysis of KNN and Neavy Bayes Algorithms in Socio-Economic Data Classification in Indonesia by Kiki Buhori, Andrianingsih

“…Based on this problem, the data mining classification method is used in determining the algorithm that is suitable for predicting socio-economic data in Indonesia. …”
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Prediction of cardiovascular diseases based on GBDT+LR by Zengxiao Chi, Li Liu, Liqin Yi, Lin Shi

“…The cardiovascular disease prediction model using the GBDT+LR algorithm has the best prediction performance. …”
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Prediction of Corona-Virus Using Deep Learning by Laith Al-Ali

“…Thus, this research provides an important indicator for the possible prediction of COVID-19 infection. …”
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Integrating response surface methodology and decision tree algorithms for valorization of cheese whey wastewater by Iremsu Kayan, Nilgun Ayman Oz

“…The machine learning (ML) method validates that RSM predictions are consistent and accurate. The results show that it is possible to combine traditional optimization methods with more advanced ML methods to facilitate the design and the operation of the treatment plants.…”
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TONE MAPPING METHOD AND IMAGE PROCESSING algorithms under BRIght ambient lightING by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

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Comparison of Different Machine Learning Algorithms to Classify Epilepsy Seizure from EEG Signals by Pankaj Kunekar, Chanchal Kumawat, Vaishnavi Lande, Sushant Lokhande, Ram Mandhana, Malhar Kshirsagar

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Early Fault-Tolerant Quantum Algorithms in Practice: Application to Ground-State Energy Estimation by Oriel Kiss, Utkarsh Azad, Borja Requena, Alessandro Roggero, David Wakeham, Juan Miguel Arrazola

“…The results show that the predictions from the quantum algorithm align closely with the DMRG-converged energies at larger bond dimensions while requiring several orders of magnitude fewer samples than theoretical estimates suggest. …”
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Selection Algorithms of the Optimal Reinforcement for Strength and Crack Resistance of Reinforced Concrete Elements and Their Verification by T. M. Hlukhava

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Integrating novel stellarator single-stage optimization algorithms to design the Columbia stellarator experiment by A. Baillod, E.J. Paul, G. Rawlinson, M. Haque, S.W. Freiberger, S. Thapa

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Big Data and AI Algorithms for Sustainable Development Goals: A Topic Modeling Analysis by Prema Nedungadi, Simi Surendran, Kai-Yu Tang, Raghu Raman

“…In energy, AI-driven solutions optimize forecasting, grid management, and renewable integration, while in industry, they bolster infrastructure resilience through innovations like predictive maintenance and automated quality control within Industry 4.0 frameworks. …”
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Intrusion Detection System to Advance Internet of Things Infrastructure-Based Deep Learning Algorithms by Hasan Alkahtani, Theyazn H. H. Aldhyani

“…The obtained features were processed using deep learning algorithms. The experimental results showed that the proposed systems achieved accuracy as follows: CNN = 96.60%, LSTM = 99.82%, and CNN-LSTM = 98.80%. …”
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