ANN-Based Maximum Power Tracking for a Grid-Synchronized Wind Turbine-Driven Doubly Fed Induction Generator Fed by Matrix Converter by Mohamed A. Alarabi, Sedat Sünter

“…To address this, an artificial neural network (ANN) is adopted to predict the optimal shaft speed, ensuring maximum power point tracking (MPPT) for a wind energy-driven DFIG connected to a matrix converter (MC). …”
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FORECASTING STOCK MARKET LIQUIDITY WITH MACHINE LEARNING: AN EMPIRICAL EVALUATION IN THE GERMAN MARKET by Bogdan Ionut ANGHEL

“…The study benchmarks four machine-learning algorithms— Random Forest, XGBoost, CatBoost and Long Short-Term Memory (LSTM) networks—for forecasting stock market liquidity in Germany’s DAX equity market. …”
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Unraveling the Drivers of ESG Performance in Chinese Firms: An Explainable Machine-Learning Approach by Hyojin Kim, Myounggu Lee

“…Empirical findings demonstrate that random forest algorithms significantly outperform multivariate linear regression in capturing nonlinear ESG relationships. …”
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A numerical framework for enhancing the seismic resilience of urban infrastructure in clayey basins using finite element modeling and AI optimization by Kaveh Dehghanian

“…AI-based sensitivity analysis has singled out key parameters influencing seismic resilience; real earthquake data validates model predictions. This study provides a systemic approach toward enhancing the seismic resilience of urban infrastructure in clayey basins, with information applicable for earthquake risk mitigation and infrastructure design.…”
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Travel Time Variability and Spatio-Temporal Analysis of Urban Streets Using Global Positioning System: A Review by Zainab Ahmed Alkaissi, Ruba Yousif Hussain

“…Travel time estimation algorithms based on speed data loop detectors induced insignificant differences when the study route was a relatively short and slow transition from free state to congestion state. …”
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Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

“…To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things. by Umhara Rasool Khan, Javaid A Sheikh, Aqib Junaid, Shazia Ashraf, Altaf A Balkhi

“…A detailed comparison of the five regression-based ML algorithms is presented, and it is observed that the ML models help in efficient use of resources while designing an antenna for bio-medical applications.…”
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The Discriminants of Long and Short Duration Failures in Fulfillment Sortation Equipment: A Machine Learning Approach by Abed Mutemi, Fernando Bacao

“…Under a variety of hyperparameter configurations, we test and compare the outcomes of eight different machine learning classification algorithms, seven individual classifiers, and a stacked ensemble. …”
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Deployment and Operation of Battery Swapping Stations for Electric Two-Wheelers Based on Machine Learning by Yu Feng, Xiaochun Lu

“…Then, on a 3000 m grid scale, a prediction model of BSS quantity with random forest, support vector regression, and gradient-boosting decision tree algorithm was built. …”
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MiR-124 Radiosensitizes human colorectal cancer cells by targeting PRRX1. by Yuqin Zhang, Lin Zheng, Jing Huang, Fei Gao, Xiaoshan Lin, Lian He, Dan Li, Zhijun Li, Yi Ding, Longhua Chen

“…We identified PRRX1, a new EMT inducer and stemness regulator as a novel direct target of miR-124 by using target prediction algorithms and luciferase assay. PRRX1 knockdown could sensitize CRC cells to IR similar to the effects caused by miR-124. …”
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Intelligent design and synthesis of energy catalytic materials by Linkai Han, Zhonghua Xiang

“…We provide the illustrations of predicting the properties of catalytic materials with ML assistance in different material types. …”
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Clustering and Vectorizing Acoustic Emission Events of Large Infrastructures’ Normal Operation by Theocharis Tsenis, Vassilios Kappatos

“…Latest machine learning outlier detection algorithms, like One-Class Support Vector Machine, Variational Auto-Encoder, and others, were incorporated, producing a vector of confidence on upcoming out-of-the-normal gate operation and failure prediction, achieving detection contrast enhancement on out-of-the-normal operation points up to 400%.…”
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Vehicle Pose Estimation Method Based on Maximum Correntropy Square Root Unscented Kalman Filter by Shuyu Liu, Ying Guo

“…The method first generates an estimate of the predicted state and covariance matrix through the Unscented Transform (UT), and then obtains the square root matrix of the covariance through Cholesky and QR decomposition to replace the original covariance, effectively preserving the positive definiteness of the covariance and improving the accuracy of the algorithm. …”
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DIGITAL TWINS AND THEIR APPLIANCE IN TRANSPORT ECONOMICS by O. N. Rimskaya, I. V. Anokhov

“…The consequence of this is the emergence of digital twins that allow modeling and predicting the behavior of both individual processes and enterprises as a whole.The aim of the article is to investigate the process of digitalization in the transport industry. …”
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Leveraging Feature Fusion of Image Features and Laser Reflectance for Automated Fish Freshness Classification by Caner Balım, Nevzat Olgun, Mücahit Çalışan

“…This work presents an original contribution by demonstrating, for the first time, the effectiveness of combining low-cost laser sensing and deep visual features for freshness prediction, with potential for real-time mobile deployment.…”
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CALCULATION OF WEIGHT COEFFICIENTS IN CONTINUOUS PARTICLE FILTER by K. A. Rybakov

“…In addition, it is planned to develop algorithms for predicting the states of stochastic diffusion and jump-diffusion systems based on the calculation of weight coefficients in the particle filter considered in this article.…”
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The siRNA Non-seed Region and Its Target Sequences Are Auxiliary Determinants of Off-Target Effects. by Piotr J Kamola, Yuko Nakano, Tomoko Takahashi, Paul A Wilson, Kumiko Ui-Tei

“…These observations may prove useful as parameters for off-target prediction algorithms and improve siRNA 'specificity' design rules.…”
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A Comparison of the Impacts of Radiosonde and AMSU Radiance Observations in GSI Based 3DEnsVar and 3DVar Data Assimilation Systems for NCEP GFS by Govindan Kutty, Xuguang Wang

“…The impact of observations can be dependent on many factors in a data assimilation (DA) system including data quality control, preprocessing, skill of the model, and the DA algorithm. The present study focuses on comparing the impacts of observations assimilated by two different DA algorithms. …”
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Accounting Management and Optimizing Production Based on Distributed Semantic Recognition by Ruina Guo, Shu Wang, Guangsen Wei

“…Additionally, a semantic recognition module is introduced to process the voice signals and generate prediction results. By leveraging extensive accounting management and production data for learning and analysis, the algorithm automatically uncovers patterns and laws within the data, extracting valuable information. …”
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Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater by Marco Baldan, Paolo Di Barba

“…Eventually, the ePINN predicts the temperature field within the graphite plate.…”
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