IEEE

A Design of Hybrid Model and Bayesian Neural Networks for Smart Grid Stability Prediction

Abstract: The latest evolution in power systems, is ‘smart grids'that offers real time monitoring, control features as well as effective management of renewable energy sources. Nonetheless, with the ...
IEEE

Variational Bayesian Learning-Based Target Localization and Time Synchronization With Quantized TOA Measurements in Wireless Sensor Networks

Abstract: Precise positioning is becoming increasingly crucial across various applications, including rescue operations, intelligent transportation, logistics, and environmental monitoring. However, ...
IEEE

A Novel Bayesian-Optimized Hybrid Recurrent Neural Networks for Predicting Lettuce Harvest Time in Controlled-Environment Agriculture

Abstract: Accurately predicting the harvest time of a crop remains a significant challenge in agricultural management and sustainable crop production, as it is essential for optimising harvesting ...
IEEE

High-Efficient Memristor-Based Bayesian Convolutional Neural Networks for Out-of-Distribution Detection by Uncertainty Estimation

Abstract: By using the nonvolatile and stochastic properties of memristor, memristors crossbar arrays can efficiently accelerate Bayesian neural networks (BNNs). However, Bayesian convolutional neural ...
IEEE

Bayesian-Inspired Cross-Spectral Fusion Network for Robust Depth Estimation

Abstract: Depth estimation is a critical task in multimedia, with widespread applications in autonomous driving, robotics, and 3D reconstruction. Traditional methods relying on single-spectral data ...
IEEE

LLM and Bayesian Network Integrated Simulation Framework for Electric Vehicle User Charging Behaviorals

Abstract: Electric vehicle (EV) users’ behaviors are influenced by users’ willingness, which is not directly observable. Emerging large language models (LLMs) have advantages in handling this problem.
IEEE

Bayesian Optimization for Adaptive Network Reconfiguration in Urban Delivery Systems

Abstract: Urban delivery systems face numerous challenges due to fluctuating demand and dynamic traffic conditions, necessitating efficient route management for improved performance. We introduce a ...
IEEE

Dynamic Vehicle Stability Analysis Using IoT Sensors and Bayesian Network Approach

Abstract: A new way to improve vehicle stability analysis is to combine IoT sensors with sophisticated analytical methods like Bayesian networks. It investigates how to use Bayesian networks to handle ...
IEEE

BAYES-GAIT: A Bayesian Deep Neural Network for Continuous Gait Reference Trajectory Generation Using an Enhanced Loss Function

Abstract: Background: Adaptive gait trajectory prediction is essential to achieve natural and stable locomotion in prosthetic limbs and legged robots, particularly under varied conditions such as ...
IEEE

Smart Operation Guidance for Ship Engine Rooms: Integrating Bayesian Networks and Reinforcement Learning

Abstract: Ship engine rooms are critical propulsion centers requiring precise operational coordination for maritime safety and efficiency. Current manual operations rely heavily on crew expertise, ...
IEEE

Electric Power Prediction Model based on Bayesian Deep Q-network

Abstract: Electric power forecasting is important for the stable operation and efficiency optimization of power grid. This paper proposes a Bayesian Deep Q-Network (BDQN) based power prediction model, ...