Analysis of Brand Communication Influence of Professional Sports Clubs Based on Complex System Discrete Model by Hui Zhang

“…In recent years, because the complex system discrete model has brought good results in the application of many research directions such as human management analysis, control system prediction, and animal group prediction, how to combine the complex system discrete model with the prediction of enterprise brand communication effect has become a current research hotspot. …”
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Intelligent ESG portfolio optimization: A multi-objective AI-driven framework for sustainable investments in the Indian stock market by Apurv Gaurav, Kripamay Baishnab, Piyush Kumar Singh

“…For predictive modeling, MBi-LSTM showed the lowest errors in all the parameters. …”
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AI‐Driven TENGs for Self‐Powered Smart Sensors and Intelligent Devices by Aiswarya Baburaj, Syamini Jayadevan, Akshaya Kumar Aliyana, Naveen Kumar SK, George K Stylios

“…This review explores the synergistic potential of AI‐driven TENG systems, from optimizing materials and fabrication to embedding machine learning and deep learning algorithms for intelligent real‐time sensing. These advancements enable improved energy harvesting, predictive maintenance, and dynamic performance optimization, making TENGs more practical across industries. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…Additionally, multi-factor logistic regression analysis identified clinical predictors associated with PD-RBD, and these clinical features were integrated with the radiomics signatures to develop predictive models using various machine learning algorithms. …”
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Fuzzy logic in real-time decision making for autonomous drones by Abdelwahed Motwakel, Adnan Shaout, Arif Muntasa, Manar Ahmed Hamza, Anwer Mustafa Hilal, Sitelbanat Abdel-gaddir Alhadi, Elmouez Samir Abd Elhamee

“… The rapid advancement of drone technology has expanded their applications across various sectors, necessitating robust real-time decision-making systems. Traditional algorithms often falter in dynamic and unpredictable environments. …”
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ML-based Plant Stress Detection from IoT-sensed Reduced Electromes by Marcos De Oliveira Jr, Gregory Sedrez, Gerson Geraldo H. Cavalheiro

“…The results validated the proposed approach, with the best performance obtained with the PAA+SAX techniques combined with the SVM algorithm, achieving good data reduction and improving stress detection, without compromising data quality. …”
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Modeling of settlement of shallow-founded rocking structures using explainable physics-guided machine learning by Sivapalan Gajan, Christopher Kantor

“…SHAP analysis reveals that the PGML model predictions and their dependency on input features are consistent with the existing domain knowledge, and that the inclusion of physics in PGML models help improve the prediction accuracy, especially in cases where other input features fail to capture the combined complex interaction among the variables involved.…”
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System Layout and Grasp Efficiency Optimization for a Multirobot Waste Sorting System by Bart Engelen, Sander Teck, Jef R. Peeters, Karel Kellens

“…The findings demonstrate substantial improvements in picking efficiency of up to 3.6% and pick rates up to 37.5%, underscoring the potential of advanced heuristic algorithms in robotic waste sorting systems. Future work will focus on refining gripper designs and exploring predictive algorithms to further enhance grasp success rates.…”
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Performance validation of global MPPT for efficient power extraction through PV system under complex partial shading effects by Muhammad Abu Bakar Siddique, Dongya Zhao, Khmaies Ouahada, Ateeq Ur Rehman, Habib Hamam

“…This study developed an adapted perturb and observe based model predictive control (APO-MPC) maximum power point tracking (MPPT) approach in MATLAB/Simulink, comprising six series-connected PV modules, a boost converter, and load. …”
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Robotic Motion Intelligence Using Vector Symbolic Architectures and Blockchain-Based Smart Contracts by Daswin De Silva, Sudheera Withanage, Vidura Sumanasena, Lakshitha Gunasekara, Harsha Moraliyage, Nishan Mills, Milos Manic

“…The rapid adoption of artificial intelligence (AI) systems, such as predictive AI, generative AI, and explainable AI, is in contrast to the slower development and uptake of robotic AI systems. …”
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Use Cases of Machine Learning in Queueing Theory Based on a <i>GI</i>/<i>G</i>/<i>K</i> System by Dmitry Efrosinin, Vladimir Vishnevsky, Natalia Stepanova, Janos Sztrik

“…Machine learning (ML) in queueing theory combines the predictive and optimization capabilities of ML with the analytical frameworks of queueing models to improve performance in systems such as telecommunications, manufacturing, and service industries. …”
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MPN-RRT*: A New Method in 3D Urban Path Planning for UAV Integrating Deep Learning and Sampling Optimization by Yue Zheng, Ang Li, Zihan Chen, Yapeng Wang, Xu Yang, Sio-Kei Im

“…Compared to conventional RRT*, the MPN-RRT* achieves a 47.8% reduction in planning time (from 89.58 s to 46.77 s) and a 19.8% shorter path length (from 476.23 m to 381.76 m) in simpler environments, alongside smoother trajectories quantified by a 91.2% reduction in average acceleration (from 14.67 m/s² to 1.29 m/s²). …”
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Validation of the Recording of Acute Exacerbations of COPD in UK Primary Care Electronic Healthcare Records. by Kieran J Rothnie, Hana Müllerová, John R Hurst, Liam Smeeth, Kourtney Davis, Sara L Thomas, Jennifer K Quint

“…Responses were reviewed independently by two respiratory physicians. Positive predictive value (PPV) and sensitivity were calculated.…”
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AI and Machine Learning in V2G technology: A review of bi-directional converters, charging systems, and control strategies for smart grid integration by Nagarajan Munusamy, Indragandhi Vairavasundaram

“…AI-powered predictive analytics can forecast energy demand and supply, enabling proactive charging and discharging strategies. …”
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Identification of metabolic biomarkers in idiopathic pulmonary arterial hypertension using targeted metabolomics and bioinformatics analysis by Chuang Yang, Yi-Hang Liu, Hai-Kuo Zheng

“…This study used metabolomics, machine learning algorithms and bioinformatics to screen for potential metabolic biomarkers associated with the diagnosis of PAH. …”
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Hybrid Renewable Energy Systems—A Review of Optimization Approaches and Future Challenges by Akvile Giedraityte, Sigitas Rimkevicius, Mantas Marciukaitis, Virginijus Radziukynas, Rimantas Bakas

“…Moreover, the integration of metaheuristic algorithms with machine learning has enabled dynamic adaptability and predictive optimization, paving the way for real-time energy management. …”
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Insight Thoughts for Intelligent Traffic Management-Based SDN by Sara Sadiq Jawad, Dheyaa Jasim Kadhim, Yusmadi Yah Bt Jusoh

“…This paper introduces the integration of AI algorithms into the SDN controller so that you can make intelligent decisions using predictive analytics of future traffic, what it requires, and network capacity requirements. …”
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Iterative Assessment of Edge Criticality: Efficiency Enhancement or Hidden Insufficiency Detection by Vasily Lubashevskiy, Hamza Ejjbiri, Ihor Lubashevsky

“…Second, the analysis reveals hidden inner insufficiency in edge ranking for some algorithms, as evidenced by the fact that algorithm iterations can reduce decomposition efficiency. …”
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Outdoor Clothing Design for Traffic Safety Based on Big Data and Artificial Intelligence by Ya Zhou, Yun Shi

“…The first experiment is to test the accuracy of various machine learning algorithms for clothing size measurement. The results obtained are as follows: the predicted value of the DBN neural network is the closest to the actual value, the average prediction accuracy of DBN for the cuff size is 90%, and the average prediction accuracy for the neck circumference is 91.5%. …”
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Design of the Urban Lighting Control System Based on Optical Multisensor Technology and the GM Model by Weili Wu, Xiang Tang

“…The results of the evaluations show that the fresh method is successful in dimming, prediction, and control. This conclusively demonstrates the efficacy of the paper’s proposed design solution, which integrates optical multisensor technology with sophisticated control algorithms and data analysis to improve the quality of life in urban areas by boosting the efficiency and sustainability of the urban lighting system.…”
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