Mapping football tactical behavior and collective dynamics with artificial intelligence: a systematic review by José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, José E. Teixeira, Eduardo Maio, Eduardo Maio, Eduardo Maio, Pedro Afonso, Pedro Afonso, Samuel Encarnação, Samuel Encarnação, Samuel Encarnação, Guilherme F. Machado, Guilherme F. Machado, Ryland Morgans, Tiago M. Barbosa, Tiago M. Barbosa, António M. Monteiro, António M. Monteiro, Pedro Forte, Pedro Forte, Pedro Forte, Ricardo Ferraz, Ricardo Ferraz, Luís Branquinho, Luís Branquinho, Luís Branquinho, Luís Branquinho

“…By synthesizing findings from 32 studies, this review elucidates the available AI-based techniques to analyze tactical behavior and identify the collective dynamic based on artificial neural networks, deep learning, machine learning, and time-series techniques. …”
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CLASSIFYING ANDROID MALWARE CATEGORIES BASED ON DYNAMIC FEATURES: AN INTEGRATION OF FEATURE REDUCTION AND SELECTION TECHNIQUES by abdullah alsraratee, Ahmed Al-Azawei

“…This study utilizes machine learning techniques namely, K-Nearest Neighbor, Random Forest and Decision Tree to classify Android malware based on dynamic analysis. …”
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Coordinate Representations for Interference Reduction in Motor Learning. by Sang-Hoon Yeo, Daniel M Wolpert, David W Franklin

“…However, any difference in the limb's endpoint location typically changes the hand position, joint angles and the hand orientation making it ambiguous as to which of these changes underlies the ability to learn dynamics that normally interfere. Here we examine the extent to which each of these three possible coordinate systems--Cartesian hand position, shoulder and elbow joint angles, or hand orientation--underlies the reduction in interference. …”
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Transfer learning nonlinear plasma dynamic transitions in low dimensional embeddings via deep neural networks by Zhe Bai, Xishuo Wei, William Tang, Leonid Oliker, Zhihong Lin, Samuel Williams

“…Deep learning algorithms provide a new paradigm to study high-dimensional dynamical behaviors, such as those in fusion plasma systems. …”
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Concurrent Contribution of Co-Contraction to Error Reduction During Dynamic Adaptation of the Wrist by Andria J Farrens, Kristin Schmidt, Hannah Cohen, Fabrizio Sergi

“…MRI-compatible robots provide a means of studying brain function involved in complex sensorimotor learning processes, such as adaptation. To properly interpret the neural correlates of behavior measured using MRI-compatible robots, it is critical to validate the measurements of motor performance obtained via such devices. …”
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Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis by Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim

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Deep Reinforcement Learning for Dynamic Pricing and Ordering Policies in Perishable Inventory Management by Yusuke Nomura, Ziang Liu, Tatsushi Nishi

“…The results show that dynamic programming with action reduction achieved an average of 63.1% reduction in computation time compared to vanilla dynamic programming. …”
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Optimization of dynamic incentive strategies for public transportation based on reinforcement learning and network synergy effect by Yifang Chen, Shunlin Wang

“…Abstract Aiming at the challenges of peak passenger congestion, user behavior heterogeneity and insufficient network synergy faced by public transportation systems in urbanization, this study proposed the Dynamic Incentive Strategy-Heterogeneous Response Synergy Model (DIS-HARM). …”
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Multi-camera spatiotemporal deep learning framework for real-time abnormal behavior detection in dense urban environments by Sai Babu Veesam, B. Tarakeswara Rao, Zarina Begum, R. S. M. Lakshmi Patibandla, Arvin Arun Dcosta, Shonak Bansal, Krishna Prakash, Mohammad Rashed Iqbal Faruque, K. S. Al-mugren

“…Multi Scale Graph Attention Networks (MS-GAT) are used to achieve interaction-aware anomaly detection, which has resulted in up to 30% reduction in false positives. RL-DCAT or the Reinforcement Learning Based Dynamic Camera Attention Transformer works very efficiently for optimizing surveillance focus, which helps reduce 40% of the computational overhead and increases recall by 15%. …”
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A Novel Deep Learner for Human Behavior Prediction Over Public Video Surveillance by Bayan Alabdullah, Bisma Batool Fatima, Haifa F. Alhasson, Mohammed Alshehri, Yahya AlQahtani, Nouf Albhassabi, Hui Liu

“…Identifying human behavior effectively is essential for spotting anomalies in video surveillance systems, particularly in dynamic environments. …”
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Dynamic Dual-Phase Forecasting Model for New Product Demand Using Machine Learning and Statistical Control by Chien-Chih Wang

“…Forecasting demand for newly introduced products presents substantial challenges within high-mix, low-volume manufacturing contexts, primarily due to cold-start conditions and unpredictable order behavior. This research proposes the Dynamic Dual-Phase Forecasting Framework (DDPFF) that amalgamates machine learning-based classification, similarity-driven analogous forecasting, ARMA-based residual compensation, and statistical process control for adaptive model refinement. …”
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Machine learning: enhanced dynamic clustering for privacy preservation and malicious node detection in industrial internet of things by Nabeela Hasan, Saima Saleem, Mudassir Khan, Abdulatif Alabdultif, Mohammad Mazhar Nezami, Mansaf Alam

“…This research introduces ML-DCPP, a Machine Learning-based Dynamic Clustering and Privacy Preservation framework tailored to safeguard IIoT ecosystems. …”
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Machine learning-enhanced fully coupled fluid–solid interaction models for proppant dynamics in hydraulic fractures by Dennis Delali Kwesi Wayo, Sonny Irawan, Lei Wang, Leonardo Goliatt

“…Abstract This study presents a hybrid modeling framework for predicting proppant settling rate (PSR) in hydraulic fracturing by integrating symbolic physics-based derivations, parametric simulations, and ensemble machine learning. Symbolic expressions were formulated using Stokes’ law, drag equations, and pressure-gradient dynamics. …”
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Machine learning assisted CFD optimization of fuel-staging natural gas burners for enhanced combustion efficiency and reduced NOx emissions by Muhammad Mubashir, Dekui Shen, Habib Kraiem, Aymen Flah, Nahar F. Alshammari, Muhammad Mubashar Hanif

“…Using Computational Fluid Dynamics (CFD) simulations combined with Machine Learning (ML)-assisted predictive modeling, the burner geometry, fuel–air mixing behavior, and heat transfer dynamics were systematically optimized. …”
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Design of a dynamic trust management and defense decision system for shared vehicle data based on blockchain and deep reinforcement learning by Jinxiang Chen, Yan Li, Jiaxing Deng, Beicheng Qin, Chengcai He, Qiangsheng Huang, Jingchun Wu

“…The DQN-based system achieves a performance increase exceeding 20% compared to Q-learning, highlighting its decision-making efficacy. (3) Malicious Behavior Detection Rate: Measures the system’s ability to detect and address malicious activities. …”
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Multi-Degree Reduction of Said–Ball Curves and Engineering Design Using Multi-Strategy Enhanced Coati Optimization Algorithm by Feng Zou, Xia Wang, Weilin Zhang, Qingshui Shi, Huogen Yang

“…This algorithm utilizes a good point set combined with opposition-based learning to refine the initial population distribution, employs a fitness–distance equilibrium approach alongside a dynamic spiral search strategy to harmonize global exploration with local exploitation, and integrates an adaptive differential evolution mechanism to boost convergence rates and robustness. …”
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Designing and implementing SMILE: An AI-driven platform for enhancing clinical decision-making in mental health and neurodivergence management by Antonio Pesqueira, Maria Jose Sousa, Ruben Pereira, Mark Schwendinger

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Intra-BLA alteration of interneurons’ modulation of activity in rats, reveals a dissociation between effects on anxiety symptoms and extinction learning by Rinki Saha, Lisa-Sophie Wüstner, Darpan Chakraborty, Rachel Anunu, Silvia Mandel, Joyeeta Dutta Hazra, Martin Kriebel, Hansjuergen Volkmer, Hanoch Kaphzan, Gal Richter-Levin

“…Moreover, this increased synaptic activity was followed by a reduction in intrinsic excitability. While intra-BLA NF-KD resulted in impaired extinction learning, without increased symptoms of anxiety, intra-BLA reduction of EphA7 expression resulted in increased symptoms of anxiety, as measured in the elevated plus maze, but without affecting fear conditioning or extinction learning. …”
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Tracking Long-Term Ozone Pollution Dynamics in Chinese Cities with Meteorological and Emission Attribution by Hongrui Li, Xiaoyong Liu, Zijian Liu, Mengyang Li, Tong Wu, Peicheng Li, Peng Zhou

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Adaptive Remaining Capacity Estimator of Lithium-Ion Battery Using Genetic Algorithm-Tuned Random Forest Regressor Under Dynamic Thermal and Operational Environments by Uzair Khan, Mohd Tariq, Arif I. Sarwat

“…The model effectively captures the battery’s dynamic behavior and inherent non-linearity. The Mean Absolute Error (MAE) and Root Mean Square Error (RMSE) achieved during testing demonstrate promising accuracy and superior prediction. …”
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