Optimizing electric bus performance via predictive maintenance: a combined experimental and modeling approach by Hisham Ibrahim, Ahmed M. Ali, Tamer Attia

“…IntroductionThis study explores the optimization of Electric Bus (EB) performance by integrating predictive maintenance strategies, utilizing real-time data and advanced modeling techniques.MethodsThe study involves installing measurement sensors to capture dynamic behavior and energy consumption during actual road trips, analyzing the collected data to refine vehicle dynamics models and assess battery degradation under various operational conditions, and employing a multi-objective optimization framework to minimize battery degradation while ensuring efficient energy use and maintaining operational requirements.Results and DiscussionThe study offers valuable insights into battery management strategies, revealing that battery degradation can be reduced by 25% through optimum driving behavior, which can be achieved in real driving conditions by avoiding aggressive driving. …”
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Predictive optimization in automotive supply chains: a BiLSTM-Attention and reinforcement learning approach by Asmae Amellal, Issam Amellal, Mohammed Rida Ech-charrat, Hamid Seghiouer

“…This predictive model achieved a Mean Squared Error (MSE) of 0.0525 and an R² value of 0.896, indicating high accuracy and an ability to explain substantial variance in customer behavior. …”
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Predictive modeling of ADME properties using M-polynomial based topological indices for biocompatible polysaccharides by W. Eltayeb Ahmed, Muhammad Naeem, Muhammad Kamran Siddiqui, Mohamed Abubakar Fiidow

“…The results support the biological relevance of topological descriptors in modeling drug behavior and underline their potential utility in computational drug design, especially for biocompatible polysaccharide-based delivery systems.…”
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Individual encounter prediction based on mobile internet record data by Qian LI, Hao JIANG, Jintao YANG

“…Studies on human movement behavior have drawn much attention with the availability of unprecedented amount of records with high accuracy involving individuals’ trajectories.The encounter prediction problem based on the session data generated by users’ mobile terminal was studied when users accessed the internet for data usage.Firstly,the network based on the encounter relations between users was constructed.Secondly,the network topology features were analyzed and user mobility characteristics and user internet behavior characteristics were introduced.Finally,the prediction model based on random forest was applied.The experimental results show that compared with the traditional network topology features,the prediction performance can be significantly improved by introducing the user mobility characteristics and user internet behavior characteristics.…”
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Model Predictive Excitation Controller for Synchronous Condenser Coordinated With Wind Farms in Sending-End System by Lingfeng Zheng, Yongzhi Zhou, Hongda Cai, Xiaoming Liu, Donglei Sun

“…The proposed controller predicts the future behavior of the system and determines the optimal control input using model predictive control (MPC) algorithm with extended and linearized state space model of sending-end system. …”
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Using the Language of elite athletes to predict their personality and on court transgressions by Maor Daniel Levitin, Itamar Zan Ger, Ze’ev Sovik, Ariel Taieb, Lyle Ungar, Michael Gilead

“…Abstract Personality is predictive of many behaviors, but personality questionnaires cannot be readily administered to persons of interest. …”
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Suicide risk prediction for Korean adolescents based on machine learning by Haitao Wang, Han Yuan, Yunong Zhang, Qixuan Wang, Zeng Gao, Mujuan Zhao

“…This study evaluates the predictive capability of national survey data, which includes factors such as lifestyle behaviors and mental health indicators, in forecasting adolescent suicidal behavior. …”
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Reconciling the FOPT and CIPT predictions for the hadronic tau decay rate by Miguel A. Benitez-Rathgeb, Diogo Boito, Andre H. Hoang, Matthias Jamin

“…In a recent work it was suggested that the discrepancy observed in the perturbation series behavior of the $\tau$ hadronic decay rate determined in the FOPT and CIPT approaches can be explained from a different infrared sensitivity inherent to both methods, assuming that the major source of the discrepancy is the asymptotic behavior of the series related to the gluon condensate renormalon. …”
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Reading Shakespeare sonnets: Combining quantitative narrative analysis and predictive modeling - an eye tracking study by Shuwei Xue, Jana Lüdtke, Teresa Sylvester, Arthur M. Jacobs

“…., 2017), the present study analyzed the eye movement behavior of participants reading three of the 154 sonnets as a function of seven lexical features extracted via Quantitative Narrative Analysis (QNA). …”
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Predictive Probability Density Mapping for Search and Rescue Using an Agent-Based Approach With Sparse Data by Jan-Hendrik Ewers, David Anderson, Douglas Thomson

“…To improve the precision and efficiency of these predictions, simulated agents can be created to emulate the behavior of the lost person. …”
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My heart belongs here: an investigation into the predictive role of destination psychological ownership on tourism ethnocentrism by David Amani, Betty Begashe, Esther Ernest Mfumbilwa

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Vagus nerve stimulation as a predictive coding modulator that enhances feedforward over feedback transmission by Shinichi Kumagai, Shinichi Kumagai, Tomoyo Isoguchi Shiramatsu, Kensuke Kawai, Hirokazu Takahashi

“…Vagus nerve stimulation may facilitate neural plasticity and adaptive behavior through acetylcholine and noradrenaline (norepinephrine), which differentially modulate feedforward and feedback signaling. …”
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Predictive modeling of pediatric drug-induced liver injury: Dynamic classifier selection with clustering analysis by Zixin Shi, Linjun Huang, Haolin Wang

“…Objective This study introduces a framework that integrates clustering analysis with dynamic classifier selection (DCS) techniques to enhance pediatric DILI prediction. The proposed method addresses challenges such as patient heterogeneity and class imbalance, while optimizing predictive performance to support clinical decision-making. …”
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Sizing and Characterization of Load Curves of Distribution Transformers Using Clustering and Predictive Machine Learning Models by Pedro Torres-Bermeo, Kevin López-Eugenio, Carolina Del-Valle-Soto, Guillermo Palacios-Navarro, José Varela-Aldás

“…This study applies clustering techniques and predictive models to analyze and predict the behavior of transformer demand, optimize utilization factors, and improve infrastructure planning. …”
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Nonlinear Model Predictive Control of Heaving Wave Energy Converter with Nonlinear Froude–Krylov Forces by Tania Demonte Gonzalez, Enrico Anderlini, Houssein Yassin, Gordon Parker

“…This paper presents the application of a nonlinear model predictive controller (MPC) to enhance the energy extraction of a heaving point absorber. …”
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Modulated Model Predictive Speed Controller for PMSM Drives Employing Voltage-Based Cost Function by Ahmed Aboelhassan, Shuo Wang, Giampaolo Buticchi, Vasyl Varvolik, Michael Galea, Serhiy Bozhko

“…On the other hand, modulated model predictive control (M²PC) has been employed recently for different applications for faster dynamic response and better power quality. …”
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Explainable Predictive Model for Suicidal Ideation During COVID-19: Social Media Discourse Study by Salah Bouktif, Akib Mohi Ud Din Khanday, Ali Ouni

“…ConclusionsConsidering the dynamic nature of suicidal behavior posts, we proposed a fused architecture that captures both localized and generalized contextual information that is important for understanding the language patterns and predict the evolution of suicidal ideation over time. …”
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Rhythmic manipulation of objects with complex dynamics: predictability over chaos. by Bahman Nasseroleslami, Christopher J Hasson, Dagmar Sternad

“…This study investigated a rhythmic manipulation task, which involved continuous interaction with a nonlinear object that led to unpredictable object behavior. Using a simplified virtual version of the task of carrying a cup of coffee, we studied how this unpredictable object behavior affected the selected strategies. …”
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A Bayesian model for predicting monthly fire frequency in Kenya. by Levi Orero, Evans Otieno Omondi, Bernard Oguna Omolo

“…This work introduces a statistical model that captures the behavior of fire count data, incorporating temporal explanatory factors and emphasizing the predictive significance of maximum temperature and rainfall. …”
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A pan-cancer analysis: predictive role of ZNF32 in cancer prognosis and immunotherapy response by Minghan Li, Chang Su, Qianru Wang, Yuetong Chen, Di Jiang, Weijia Wang, Shunjin Chen, Xiangping Li, Ming Fu, Juan Lu

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