reinforcement learning

Hybrid Physics-Informed Reinforcement Learning for Plasma Characterization in Electrical Wire Explosions

Abstract Accurate prediction of discharge observables in electrical wire explosions is challenging due to the inherent nonlinearities in plasma behavior, especially when experimental datasets are limited. This study presents a hybrid physics-informed modeling framework that combines analytical scaling laws with a reinf...

Reinforcement-Learning based Self-Healing Banking Transaction System against Malware Attacks in IoT Networks

The IoT technology that was at the height of popularity in the banking industry has resulted, improved real-time transaction processing, enhancing the availability of smart financial products and services, and the automated payment systems are more feasible than the traditional banking IoT security models. However, the...

Computational modelling of decision-making in suicide attempters

Importance. Suicide is a leading cause of mortality, yet its prevention remains a challenge. Suicide attempters exhibit disrupted decision-making, but the specific cognitive processes driving this impairment and their utility for risk stratification are unclear. Objective. To determine which computational decision-maki...

A Privacy-Preserving Decentralized Partition-Autonomous Planning Method for Interconnected Multi-Microgrid Distribution Systems Driven by Federated Proximal Policy Optimization

INTRODUCTION: The rapid integration of distributed renewable energy and ICT infrastructure has made interconnected multi-microgrid distribution systems essential for low-carbon power grids, yet centralized coordination exposes sensitive operational data to privacy risks, including eavesdropping and membership inference...

Reinforcement Learning-Based Resource Allocation and Request Routing Optimization Algorithm for Edge AIGC Services

With the explosive growth of artificial intelligence generated content (AIGC) applications, deploying lightweight tiny neural networks (TNNs) at the edge to mitigate the high latency and cost of large cloud models has become an important trend in mobile computing. However, resource heterogeneity in edge environments, t...

Parrot Mambo Minidrone as a benchmark platform for low-cost UAV research: a review of control, autonomy, software validation, safety and experimental evaluation

Low-cost minidrone platforms are increasingly used in Unmanned Aerial Vehicle (UAV) research for safe indoor experimentation, controller development and engineering education. The Parrot Mambo Minidrone is particularly attractive because of its compact size, onboard sensing, MATLAB/Simulink compatibility and suitabilit...

Real-Time Stock Trend Analysis and Investment Support Tool Using Deep Learning

Financial markets' volatility, driven by economic, political, and psychological factors, complicates stock price forecasting and investment decisions. This paper proposes a real-time stock trend analysis and investment support system using a hybrid deep learning ensemble of GRU, LSTM, and Transformer models with attent...

Multi-centre cutting service composition in cloud manufacturing: a hierarchical decision model with guillotine cutting evaluation

In material-intensive Cloud Manufacturing (CMfg), traditional Service Composition and Optimal Selection (SCOS) approaches often treat cutting services as abstract functional units, which may lead to biased cost estimation and infeasible assignments. This study proposes a hierarchical decision-aid model named DiCACE to...

Flexible fuzzy reinforcement learning MCDM approach for bioprinter selection through resolving criteria dependencies

Selecting a suitable bioprinter remains a challenging task involving conflicting criteria that are difficult to weigh. Existing fuzzy multi-criteria decision-making (MCDM) methods fail to derive the fuzzy priorities of criteria while maintaining efficiency, and it is also difficult to consider the dependencies among th...

Durability Characterization and Prediction of Bio-Cement Concrete Using RCPT and Machine Learning Approaches

Concrete durability is significantly compromised by chloride ingress, which accelerates reinforcement corrosion and reduces service life. This study investigates the use of bio-cement incorporation (1%) to improve the resistance of M25, M40, and M60 concretes against chloride penetration at 28, 56, and 90 days, assesse...

Digital Twin-Based Performance Optimization of Thermal Systems in Smart Manufacturing

One of the key issues associated with the intelligent manufacturing is the thermal management. The temperature homogeneity and efficiency define the quality of goods to be produced as well as the production costs. The authors suggest a novel intelligent hybrid digital twin architecture which allows for real-time optimi...

DyPart: A Reinforcement Learning Framework for Dynamic and Self-Adaptive Model Partitioning in Volatile End-Edge-Cloud Environments