Effective Facial Expression Recognition System Using Artificial Intelligence Technique by Imad S. Yousif, Tarik A. Rashid, Ahmed S. Shamsaldin, Sabat A. Abdulhameed, Abdulhady Abas Abdullah

“…This paper presents an improved performance of the Facial Expression Recognition (FER) systems via augmentation in Artificial Neural Networks and Genetic Algorithms, two renowned artificial intelligence techniques possessing disparate strengths. …”
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Motion Planning and Tracking Control of Autonomous Vehicle Based on Improved A∗ Algorithm by Yunlong Bai, Gang Li, Ning Li

“…To overcome these potential limitations, an improved A∗ algorithm-based motion planning algorithm and a tracking control strategy based on model predictive control theory were proposed in this work. …”
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A new classification algorithm for low concentration slurry based on machine vision by Chuanzhen Wang, Xinyi Wang, Andile Khumalo, Fengcheng Jiang, Jintao Lv

“…Subsequently, a new low concentration classification model was systematically developed, encompassing aspects such as original image acquisition, data augmentation, dataset partitioning, classification algorithm design, and model evaluation. DCGAN was employed for image generation, achieving favorable outcomes with generator learning rate set at 5 × 10− 5, discriminator at 1 × 10− 6, and iteration number at 2000. …”
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Predictive diagnostics of computer systems logs using natural language processing techniques by Vladislav A. Kiriachek, Soltan I. Salpagarov

“…This study aims to develop and validate a method for predictive diagnostics and anomaly detection in computer system logs, using the Vertica database as a case study. …”
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The Artificial Intelligence and the dispute for different ways in its predictive use in the criminal process by Rodrigo Régnier Chemim Guimarães

“…Given the delicate cooperation that must exist between experts in criminal procedure and knowledge engineers in the selection and construction of the algorithms that will teach the machine for the preparation of the predictive research, which one would be appropriate? …”
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Public perception of accuracy-fairness trade-offs in algorithmic decisions in the United States. by Mehdi Mourali, Dallas Novakowski, Ruth Pogacar, Neil Brigden

“…When are individuals more likely to support equal treatment algorithms (ETAs), characterized by higher predictive accuracy, and when do they prefer equal impact algorithms (EIAs) that reduce performance gaps between groups? …”
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An Ensemble Learning-Based Predictive Parameterization Approach for Permanent Magnet Synchronous Machines by Sema Nur Ipek, Nur Bekiroglu, Murat Taskiran

“…An averaging voting ensemble model is developed by integrating the two highest-performing algorithms, LRNN and TRF, leveraging the strengths of both algorithms. …”
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ML-Based Control Strategy for PHEV Under Predictive Vehicle Usage Behaviour by Aleksandr Doikin, Aleksandr Korsunovs, Felician Campean, Oscar García-Afonso, Enrico Agostinelli

“…This study, based on extended real-world data (journeys history from 10 vehicles over 12 months), shows that trip patterns can be learnt quite effectively using classic ML classification algorithms. In particular, the RusBoosted ensemble classifier performed consistently well across the heterogeneous dataset (volume of data for training and variable imbalance in the datasets, reflecting the natural variability in the vehicle usage profiles), providing sufficiently accurate predictions for the proposed EMS strategy. …”
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A Decreasing Horizon Model Predictive Control for Landing Reusable Launch Vehicles by Guillermo Zaragoza Prous, Enric Grustan-Gutierrez, Leonard Felicetti

“…A novel approach to model predictive control (MPC) with a decreasing horizon is analysed for guiding and controlling reusable launch vehicles (RLVs) during powered descent phases. …”
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Population-level predictive variation in machine learning diagnosis of symptomatic bacterial vaginosis by Diandra P. Ojo, Cameron Celeste, Dion Ming, Ruogu Fang, Ivana K. Parker

“…To determine the ability of ML models to perform equitably, this study evaluates the performance of ML algorithms in predicting symptomatic BV across different ethnic groups using 16S rRNA sequencing data. …”
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Variable convergence train noise active control algorithm based on feedforward reference by LI Tao, HE Yuyao, WANG Ning, LI Zhuang, SHEN Zhaoyuan, XIAO Gang

“…Compared with the fixed-convergence FxLMS, variable-convergence NLMS, and SVSLMS control algorithms, it has the advantage of noise reduction up to about 3.6 dB.…”
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Advancements in Predictive Microbiology: Integrating New Technologies for Efficient Food Safety Models by Oluseyi Rotimi Taiwo, Helen Onyeaka, Elijah K. Oladipo, Julius Kola Oloke, Deborah C. Chukwugozie

“…Machine learning algorithms commonly employed in predictive modeling are discussed with emphasis on their application in research and industry and their advantages over traditional models.…”
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Prediction of formation pressure in underground gas storage based on data-driven method by SUI Gulei, FU Yujiang, ZHU Hongxiang, LI Zunzhao, WANG Xiaolin

“…The experimental results show that predictive performances of three predictive models are ranked from high to low: SVR, XGBoost, LSTM, among which the predictive performance of SVR is the most stable. …”
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Advanced Deep Learning Based Predictive Maintenance of DC Microgrids: Correlative Analysis by M. Y. Arafat, M. J. Hossain, Li Li

“…This paper presents advanced frameworks for microgrid predictive maintenance by performing a comprehensive correlative analysis of advanced recurrent neural network (RNN) architectures, i.e., RNNs, Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs) for photovoltaic (PV) based DC microgrids (MGs). …”
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Methodological Aspects of Predictive Mineragenic Studies Using Earth Remote Sensing Data by Petrov Vladislav, Ustinov Stepan, Minaev Vasilii

“…Of the entire range of areas of fundamental and exploratory scientific research, the main attention within the framework of predictive and mineragenic studies is paid to solving the following problems: 1) allocation of lineaments (fault zones) based on processing of digital elevation models; 2) determination of hydraulically active fault structures for the period of ore formation based on tectonophysical reconstructions; 3) analysis of multispectral characteristics of pre-ore, ore-accompanying and post-ore metasomatites based on statistical processing of Landsat-8 satellite data; 4) assessment of fluid-dynamic settings of deposit formation based on data on the composition, properties and genesis of mineral-forming fluids. 5) creation of weight of evidence models based on statistical algorithms for processing data on the dynamics of ore-genetic processes. …”
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Validating an Electronic Health Record Algorithm for Diabetes Screening Eligibility in the Emergency Department by Mary H. Smart, Janet Y. Lin, Brian T. Layden, Yuval Eisenberg, Kirstie K. Danielson, Ruth Pobee, Chuxian Tang, Brett Rydzon, Anjana Bairavi Maheswaran, A. Simon Pickard, Lisa K. Sharp, Angela Kong

“…We used sensitivity, specificity, likelihood ratios, and predictive values to estimate the algorithm’s ability to correctly identify patients eligible for diabetes screening, with manual chart review as the reference standard. …”
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Predictive modelling of air pollution affecting human tuberculosis risk on Mainland China by Boli Qin, Rongqing He, Xiaopeng Qin, Jiayan Jiang, Chenxing Zhou, Songze Wu, Jichong Zhu, Shaofeng Wu, Jiarui Chen, Jiang Xue, Kechang He, Chong Liu, Jie Ma, Xinli Zhan

“…Regression models were built using six algorithms, among which the random forest (RF) model showed superior performance. …”
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Evaluating the Nuclear Reaction Optimization (NRO) Algorithm for Gene Selection in Cancer Classification by Shahad Alkamli, Hala Alshamlan

“…In select datasets, it outperformed several state-of-the-art optimization algorithms. However, due to the absence of additional dimensionality reduction techniques, the number of selected genes remains relatively high. …”
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Vibration Control of Buildings Using Magnetorheological Damper: A New Control Algorithm by Aly Mousaad Aly

“…A magnetorheological (MR) damper is placed in the building between the first floor and ground for seismic response reduction. A new control algorithm to command the MR damper is proposed. …”
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Research and predictive analysis of pyrolysis characteristics of multi-source organic solid wastes by ZHANG Zihang, XING Bo, MA Zhongqing, HU Yanjun, ZHANG Zhixiao, YUAN Shizhen, LU Rufei, CHEN Yingquan, WANG Shurong*

“…Subsequently, the random forest (RF), gradient boosting decision tree (GBDT), and extreme gradient boosting (XGBoost) algorithms were utilized to predict the high heating value (HHV) of organic solid waste, the distribution of fast pyrolysis products, and the thermogravimetric curves under various atmospheres. …”
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