Scalable data assimilation with message passing by Oscar Key, So Takao, Daniel Giles, Marc Peter Deisenroth

“…Data assimilation is a core component of numerical weather prediction systems. The large quantity of data processed during assimilation requires the computation to be distributed across increasingly many compute nodes; yet, existing approaches suffer from synchronization overhead in this setting. …”
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An Efficient Trajectory Negotiation and Verification Method Based on Spatiotemporal Pattern Mining by Yongqi Liu, Miao Wang, Zhaohua Zhong, Kelin Zhong, Guoqing Wang

“…Therefore, this paper develops a framework for trajectory negotiation and verification and describes the trajectory prediction, negotiation, and verification processes based on a four-dimensional trajectory. …”
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A Machine Learning Approach to Evaluate the Performance of Rural Bank by Jun Wei, Tao Ye, Zhe Zhang

“…On the other hand, they mainly focus on causal inference and lack systematic quantitative conclusions from the perspective of prediction. This paper is the first to comprehensively investigate the predictability of multidimensional features on commercial bank performance using boosting regression tree. …”
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Navigating Samarinda's climate: A comparative analysis of rainfall forecasting models by Mislan, Andrea Tri Rian Dani

“…The superior points in this research are: • Modeling rainfall data in Samarinda City using several forecasting methods: Exponential Smoothing, ARIMA, and Neural Network. • The Neural-Network algorithm used is Backpropagation with data standardization. • Information about predicted high rainfall can be used to issue early warnings of floods or landslides. …”
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Ship path planning and tracking based on rapidly exploring random tree star and convex optimization by Chang ZHOU, Te YU, Jiapeng LIU, Dihua LU, Qingshan ZENG

“…Finally, model predictive control (MPC) algorithm is employed to generate ship control output sequences, enabling safe and efficient navigation around obstacles from the starting point to the destination. …”
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Buoy and Winch Collaborative Control System Based on Deep Reinforcement Learning by Yang Gu, Jianjun Ni, Zaiming Geng, Bing Zhao, Haowen Yang

“…The main contributions include the development of two simulation environments for training DRL agents, designing a reward function to guide the exploration process, proposing a buoy control algorithm based on the discrete soft actor-critic (SAC) algorithm, and proposing a winch cable length prediction algorithm based on a lightweight transformer model. …”
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AI-Powered Eye Tracking for Bias Detection in Online Course Reviews: A Udemy Case Study by Hedda Martina Šola, Fayyaz Hussain Qureshi, Sarwar Khawaja

“…We selected Udemy courses, a platform with over 70 million learners. Predict (version 1.0.), developed by Stanford University, was used with the algorithm on the consumer neuroscience database (n = 180,000) from Tobii eye tracking (Tobii X2-30, Tobii Pro AB, Danderyd, Sweden). …”
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An Optical Sensor for Measuring In-Plane Linear and Rotational Displacement by Suhana Jamil Ahamed, Michael Aaron McGeehan, Keat Ghee Ong

“…Variations in reflected R, G, B and C light intensities, caused by displacements, were used to predict linear and rotational motion via a polynomial regression algorithm. …”
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Between Two Worlds: Investigating the Intersection of Human Expertise and Machine Learning in the Case of Coronary Artery Disease Diagnosis by Ioannis D. Apostolopoulos, Nikolaos I. Papandrianos, Dimitrios J. Apostolopoulos, Elpiniki Papageorgiou

“…These results highlight a potential synergistic relationship between human expertise and advanced algorithmic predictions, suggesting a hybrid approach as a promising direction for enhancing CAD diagnostics.…”
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RBF-Learning-Based Many-Objective Metaheuristic for Robust and Optimal Controller Design in Fixed-Structure Heading Autopilot by Nattapong Ruenruedeepan, Sujin Bureerat, Natee Panagant, Nantiwat Pholdee

“…A key feature of the method is its generation of a target Pareto front, in which a z-surrogate model makes predictions to guide design solutions toward achieving optimal performance. …”
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A spatio-temporal infection epidemic model with fractional order, general incidence, and vaccination analysis by Sara Soulaimani, Abdelilah Kaddar, Fathalla A. Rihan

“…Trajectories of various compartments closely align with theoretical equilibrium points, affirming the model’s predictive precision. Furthermore, simulations indicate the potential for attaining disease-free equilibria with heightened vaccination rates, underscoring the pivotal role of vaccination strategies in epidemic control and disease eradication. …”
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Advance path loss model for LoRaWAN coverage estimation by Van Lic Tran, Tran Dang Khoa Phan, Tran Thi Minh Hanh, Vu Van Thanh, Thai Van Tien, Thai Vu Hien, Tran Anh Kiet

“…Unlike previous studies, this research considers environmental factors such as topography and urban structures, enhancing prediction accuracy. This technique would be essential for optimizing essential for optimizing LPWAN deployments and ensuring efficient resource utilization. …”
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Impedance-Driven Decoupling Water–Nitrogen Stress in Wheat: A Parallel Machine Learning Framework Leveraging Leaf Electrophysiology by Shuang Zhang, Xintong Du, Bo Zhang, Yanyou Wu, Xinyi Yang, Xinkang Hu, Chundu Wu

“…A parallel modelling strategy was implemented employing Gradient Boosting, Random Forest, and Ridge Regression, selecting the optimal algorithm per feature based on predictive performance. …”
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Dense Crowd Dynamics and Pedestrian Trajectories: A Multiscale Field Dataset from the Festival of Lights in Lyon by Oscar Dufour, Huu-Tu Dang, Jakob Cordes, Raphael Korbmacher, Mohcine Chraibi, Benoit Gaudou, Alexandre Nicolas, Antoine Tordeux

“…Abstract The dynamics of dense crowds have received considerable attention from researchers seeking fundamental understanding or aiming to develop data-driven algorithms to predict pedestrian trajectories. However, current research mainly relies on data collected in controlled settings. …”
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Impact Analysis of BIM on Power Substation Project Costs: Techno-Economic Data Evidence from China by Ding Liu, Lizhong Qi, Yi Sun, Jingguo Rong, Su Zhang, Guangze Yu

“…The findings demonstrate that the distribution of the CV% of total project costs and the CV% of some specific cost items became more concentrated after the application of BIM, which indicates that BIM enhanced the ability to predict and control project costs. Moreover, five cost items and five shape patterns of cost items were identified as key to the impact of BIM. …”
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AI-Driven Future Farming: Achieving Climate-Smart and Sustainable Agriculture by Karishma Kumari, Ali Mirzakhani Nafchi, Salman Mirzaee, Ahmed Abdalla

“…Using sophisticated algorithms to predict soil conditions, improving agricultural yield projections, diagnosing water stress from sensor data, and identifying plant diseases and weeds through image recognition, crop mapping, and AI-guided crop selection are some of the main applications investigated. …”
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Research on Image Feature Extraction and Environment Inference Based on Invariant Learning by Yujian Ding, Xiaoxu Ma, Bingxue Yang

“…The results show that on the test set, the IRM-ResNet18 network’s prediction accuracy is 88.6%, and its accuracy and stability are significantly better than those of ResNet18. …”
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Snow Leopard Infrared Camera Image Detection Method Based on Improved EfficientDet Model by DAI Tianhong, LIU Chao

“… In view of the difficulty of snow leopard detection and recognition in infrared camera images, a snow leopard detection algorithm is proposed based on EfficientDet, which combines domain migration and new attention mechanism.Firstly, the algorithm adopts image enhancement to expand the training sample and adds non-snow leopard images to optimize the dataset structure to improve the robustness of the model. …”
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IASB Framework: Construction of Data Asset Accounting System Based on PO-BP Model by Haixia Guo

“…The PO algorithm optimizes the weights and biases of the BP neural network, improving its global search and local development capabilities. …”
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Optimization of Bayesian Neural Networks using hybrid PSO and fuzzy logic approach for time series forecasting by Farideh Sobhanifard

“…Thus, in this paper, a hybrid innovative Gaussian Particle Swarm Optimization and fuzzy logic model is proposed to optimize the Bayesian Neural Networks in weight and structure. A hybrid algorithm to improve the performance of Neural Networks and the total number of weights in Neural Networks by determining the size of each particle, which is inspired by the prediction process. …”
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