Adaptive Model Predictive Control for 4WD-4WS Mobile Robot: A Multivariate Gaussian Mixture Model-Ant Colony Optimization for Robust Trajectory Tracking and Obstacle Avoidance by Hayat Ait Dahmad, Hassan Ayad, Alfonso García Cerezo, Hajar Mousannif

“…This study uses a nonlinear model predictive controller (MPC) to ensure accurate trajectory tracking of a four-wheel drive, four-wheel steer (4WD-4WS) mobile robot. …”
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Impact of Optimization Algorithm Choice on Nonlinear Global Model for Photovoltaic Energy Generation Forecasting by Valdemar M. Cavalcante Junior, Tiago A. Fernandes, Renato Andrade Freitas, Nayara A. de M. S. Amâncio, Fabricio Bradaschia, Marcelo Cabral Cavalcanti

“…The article explores the relevance of choosing the optimization algorithm to obtain accurate parameter estimates in photovoltaic (PV) systems, with the aim of improving the energy efficiency of solar energy. …”
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Usage of the optimal fuzzy system models on chloride diffusion of concrete by Shuai Sun

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Geological Stratification Technology Based on Artificial Intelligence Algorithms and Its Application Effects by GAO Yuan, YAO Weihua, CAI Shaofeng, LI Liang, XUE Yuan, ZHAO Peipei, WANG Xiaoyang, WEI Wei

“…Good prediction results are achieved, and exploration and evaluation wells are used to predict development wells. …”
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Comparison of Energy Consumption Optimization in Sugar Factory Using Meta-Heuristic Algorithms by M. Boroun, M. Ghahderijani, A. A. Naseri, B. Beheshti

“…The total energy input reduction with the genetic algorithm was 17.05%, while the imperialist competitive algorithm achieved a higher reduction of 26.40%. …”
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Applications of digital health technologies and artificial intelligence algorithms in COPD: systematic review by Zhenli Chen, Jie Hao, Haixia Sun, Min Li, Yuan Zhang, Qing Qian

“…The rise of digital health technologies (DHTs) and artificial intelligence (AI) algorithms offers new opportunities to improve COPD predictive capabilities, diagnostic accuracy, and patient management. …”
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An Intelligent Gestational Diabetes Mellitus Recognition System Using Machine Learning Algorithms by Rasool Jader, Sadegh Aminifar

“…The healthcare system is one of the many parts of our daily lives that are being rethought thanks to the creation of intelligent systems by machine learning algorithms. In this article, a hybrid prediction model is suggested as a way to find out if a woman has gestational diabetes. …”
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Modern Tanscriptome Data Rrocessing Algorithms: a Review of Methods and Results of Approbation by M. V. Sprindzuk, L. V. Mozharovskaya, A. P. Konchits, L. P. Titov

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Modern Tanscriptome Data Rrocessing Algorithms: a Review of Methods and Results of Approbation by M. V. Sprindzuk, L. V. Mozharovskaya, A. P. Konchits, L. P. Titov

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A Quantitative Evaluation Method Based on Back Analysis and the Double-Strength Reduction Optimization Method for Tunnel Stability by Jinglai Sun, Fan Wang, Xinling Wang, Xu Wu

“…Compared with the traditional method, the proposed back analysis method can reduce errors in the predicted performance, and unlike the SRM, the ODSRM can avoid overestimating the safety factor with the same reduction factor. …”
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Research on Fractional-Order Control of Anchor Drilling Machine Optimized by Intelligent Algorithms by Jingkai Li, Jun Zhang, Jiaquan Xie, Wei Shi, Jianzhong Zhao

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Medical decision support systems for diagnosing diseases based on ensemble learning algorithms by Luma Jarallah

“…This paper proposes a stacked learning model derived from multiple ensembles learning algorithms, including Random Forest, Catboost and XGBoost. …”
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Comparison of Levenberg-Marquardt and Bayesian Regularization Learning Algorithms for Daily Runoff Forecasting by Aslı BOR, Merve OKAN

“…Our findings indicate that the estimated capability of the Bayesian Regularization algorithm were close to with Levenberg-Marquardt algorithm for training and testing, respectively. …”
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Multi-domain rule-based phenotyping algorithms enable improved GWAS signal by Abigail Newbury, Ahmed Elhussein, Gamze Gürsoy

“…Here, we assess the impact of various rule-based phenotyping algorithms on GWAS outcomes, examining factors such as power, heritability, replicability, functional annotations, and polygenic risk score prediction accuracy across seven diseases in the UK Biobank. …”
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Diabetes Mellitus Disease Prediction and Type Classification Involving Predictive Modeling Using Machine Learning Techniques and Classifiers by B. Shamreen Ahamed, Meenakshi S. Arya, S. K. B. Sangeetha, Nancy V. Auxilia Osvin

“…Various Machine-Learning (ML) algorithms are being used in order to predict and detect the disease to avoid further complications of health. …”
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How low can you go: evaluating electrode reduction methods for EEG-based speech imagery BCIs by Maurice Rekrut, Maurice Rekrut, Johannes Ihl, Tobias Jungbluth, Antonio Krüger, Antonio Krüger

“…In this study, we evaluated several electrode reduction algorithms in combination with various feature extraction and classification methods across three distinct EEG-based speech imagery datasets to identify the optimal number and position of electrodes for SI-BCIs. …”
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Evaluation of the Performance of Unsupervised Learning Algorithms for Intrusion Detection in Unbalanced Data Environments by Gutierrez-Portela Fernando, Almenares Mendoza Florina, Calderon-Benavides Liliana

“…Results showed that K-means++ achieved 95% purity with 95% and 99% prediction accuracies for normal and abnormal data, respectively, while I-forest delivered similar results and excelled in computational efficiency, consuming only 10% of CPU resources compared to 16% for other algorithms. …”
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Deep Learning-Based Algorithms for Real-Time Lung Ultrasound Assisted Diagnosis by Mario Muñoz, Adrián Rubio, Guillermo Cosarinsky, Jorge F. Cruza, Jorge Camacho

“…Real-time post-processing algorithms further refine prediction accuracy by reducing false-positives and false-negatives, augmenting interpretational clarity and obtaining a final processing rate of up to 20 frames per second with accuracy levels of 89% for consolidation, 92% for B-lines, 66% for A-lines, and 92% for detecting normal lungs compared with an expert opinion.…”
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Observing “tuned” advertising on digital platforms by Nicholas Carah, Lauren Hayden, Maria-Gemma Brown, Daniel Angus, Aimee Brownbill, Kiah Hawker, Xue Ying Tan, Amy Dobson, Brady Robards

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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

“…This article presents deep learning frameworks for predicting electricity demand in the Western region of Bangladesh, utilizing Artificial Neural Network (ANN) and Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithms. …”
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