Predictive Factors of Purchase Behaviors on Facebook by Yezid Alfonso Cancino Gómez, Pedro Mauricio Torres Duque, Laima Catherine Alfonso Orjuela, Lugo Manuel Barbosa Guerrero, Jairo Jamith Palacios Rozo

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Predictive analytics in customer behavior: Anticipating trends and preferences by Hamed GhorbanTanhaei, Payam Boozary, Sogand Sheykhan, Maryam Rabiee, Farzam Rahmani, Iman Hosseini

Subjects: “…Predictive analytics…”
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The predictive effect of heterogeneous investor behavior on commodity pricing by Hang Shao, Zhou Li

“…Thirdly, heterogeneous investors’ positions have both short- and long-term predictive effects on commodity prices. In summary, this paper demonstrates the importance of investor behavior for commodity pricing and provides policymakers with regulatory insights.…”
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The Role of Planned Behavior in Predicting Customer Orientation by Hasanbarog Zhila Mahrooz, Rasouli Eshaq, Ardabili Farzad Sattari, Azadi Behnam

Subjects: “…behavior prediction…”
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Leveraging LLMs for predictive insights in food policy and behavioral interventions by Micha Kaiser, Paul M. Lohmann, Peter Ochieng, Billy Shi, Cass R. Sunstein, Lucia A. Reisch

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Neuromarketing: Strategies for Visual Perception in Predicting Consumer Behavior by Mauricio Quisimalin Santamaria, Alice Garzón Moantaguano, Anabel Parra Jiménez

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MATHEMATICAL MODELS FOR THE PREDICTION OF THE ENCAPSULATION BEHAVIOR IN FOOD SYSTEMS by Iuliana Vinitila

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Driving behavior recognition and prediction based on Bayesian model by Xinsheng WANG, Zhen BIAN

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Modeling contextual big data for user behavior prediction by Shu WU, Qiang LIU, Liang WANG

Subjects: “…contextual big data;context modeling;user modeling;behavior prediction…”
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Behavioral fingerprints predict insecticide and anthelmintic mode of action by Adam McDermott‐Rouse, Eleni Minga, Ida Barlow, Luigi Feriani, Philippa H Harlow, Anthony J Flemming, André E X Brown

“…Here, we use high‐throughput imaging and quantitative phenotyping to measure Caenorhabditiselegans behavioral responses to compounds and train a classifier that predicts mode of action with an accuracy of 88% for a set of ten common modes of action. …”
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Study on Fractal Multistep Forecast for the Prediction of Driving Behavior by Longhai Yang, Hong Xu, Xiqiao Zhang, Shuai Li, Wenchao Ji

“…Based on these real-time data, the behavior of vehicles can be analyzed. The prediction of vehicle behavior provides data support for the fine management of traffic. …”
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Review of Research on Trajectory Prediction of Road Pedestrian Behavior by YANG Zhiyong, GUO Jieru, GUO Zihang, ZHANG Ruixiang, ZHOU Yu

“…In path planning for shared spaces between autonomous vehicles and pedestrians, accurate and efficient pedestrian trajectory prediction is critical for ensuring road safety. Pedestrian trajectory prediction not only relies on historical behavior data but also requires a comprehensive consideration of the complex dynamic interactions between pedestrians and vehicles, traffic infrastructure, and multi-directional vehicles. …”
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Personalization of Robot Behavior Using Approach Based on Model Predictive Control by Mateusz Jarosz, Bartlomiej Sniezynski

“…This paper proposes a novel approach to personalizing robot behavior using Model Predictive Control (MPC). Social humanoid robots, equipped with advanced sensors and human-like capabilities, are increasingly integrated into human environments, necessitating adaptable and intuitive communication interfaces. …”
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Financial Behaviors and Their Predictive Power on Stress: A Neutrosophic QCA Approach by Suly Sendy Pérez-Castañeda, Blanca Estela Hernández-Bonilla, Dorie Cruz-Ramírez, Beatriz Sauza-Ávila, Gisela Janeth Espinosa-Martínez

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A predictive method for the shear strength—displacement behavior of rockfill materials by Tennison Freire de Souza Junior, Sidnei Helder Cardoso Teixeira, Alessander Kormann

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Shifts in MJO behavior enhance predictability of subseasonal precipitation whiplashes by Tat Fan Cheng, Bin Wang, Fei Liu, Guosen Chen, Mengqian Lu

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A Novel Technique for Predicting the Thermal Behavior of Stratospheric Balloon by Yunpeng Ma, Jun Huang, Mingxu Yi

“…This paper is devoted to introduce a novel method of the operational matrix of integration for Legendre wavelets in order to predict the thermal behavior of stratospheric balloons on float at high altitude in the stratosphere. …”
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Predicting the Swelling Behavior of Acrylic Superabsorbent Polymers Used in Diapers by Shuxin Zhang, Yangyang Peng, Ran Jiang, Wenqiang Liu, Huanlei Yang, Na Yun, Xinsheng Chai

“…Based on a previously developed kinetic swelling model and the information from the above investigations, a semiempirical model for predicting the swelling behavior of superabsorbent polymers (SAPs) under different conditions has been developed. …”
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Learner preferences prediction with mixture embedding of knowledge and behavior graph by Xiaoguang LI, Lei GONG, Xiaoli LI, Xin ZHANG, Ge YU

“…To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences predication with mixture embedding of knowledge and behavior graph was proposed.First, considering using graph convolution network (GCN) to fit structural information, GCN was extended to knowledge graph and behavior graph, the purpose of which was to obtain learners’ overall learning pattern and individual learning pattern.Then, the difference between knowledge structure and behavior structure was used to fit learners’ individual preferences, and recurrent neural network was used to encode and decode learners’ preferences to obtain the distribution of learners’ preference distribution.The experimental results on the real datasets demonstrate that the proposed model has a good effect on predicting learner preferences.…”
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Learner preferences prediction with mixture embedding of knowledge and behavior graph by Xiaoguang LI, Lei GONG, Xiaoli LI, Xin ZHANG, Ge YU

“…To solve the problems of inaccurate prediction of learner preference and insufficient utilization of structural information in the knowledge recommendation model, for the knowledge structure and learner behavior structure in the learner’s preference prediction model, the model of learner preferences predication with mixture embedding of knowledge and behavior graph was proposed.First, considering using graph convolution network (GCN) to fit structural information, GCN was extended to knowledge graph and behavior graph, the purpose of which was to obtain learners’ overall learning pattern and individual learning pattern.Then, the difference between knowledge structure and behavior structure was used to fit learners’ individual preferences, and recurrent neural network was used to encode and decode learners’ preferences to obtain the distribution of learners’ preference distribution.The experimental results on the real datasets demonstrate that the proposed model has a good effect on predicting learner preferences.…”
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