Migrant Resettlement by Evolutionary Multiobjective Optimization

Mathematics, Engineering, Information Science, Computer Science, Artificial Intelligence,
migrant resettlement   multiobjective optimization   evolutionary algorithms   greedy algorithm   submodular optimization   humanitarianism   employment rate  

A Research Report on a New Framework for Solving Migrant Resettlement Using Multiobjective Evolutionary Optimization Against the backdrop of accelerated globalization and evolving socio-economic conditions, migration has become an undeniable global trend. From the perspective of humanitarian relief or the sustainable development of a globalized eco...

Reinforcement Learned Multiagent Cooperative Navigation in Hybrid Environment with Relational Graph Learning

Engineering, Mechanical Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
multiagent system   reinforcement learning   relational graph learning   hybrid environment   cooperative navigation   decentralized execution   collision avoidance  

Multi-agent Cooperative Navigation in Hybrid Environments: A New Reinforcement Learning Approach Based on Relational Graph Learning Mobile robotics is witnessing a surge in applications, fueled by advancements in artificial intelligence, with navigation capabilities being one of the core focus areas of research. Traditional navigation methods often...

An Intrusion Detection Approach for Industrial Internet of Things Traffic Using Deep Recurrent Reinforcement Learning and Federated Learning

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
Industrial IoT   Intrusion Detection   Federated Learning   Deep Reinforcement Learning   Temporal Dependencies   Data Privacy   Node Selection  

Intrusion Detection Approach for Industrial Internet of Things Traffic Using Deep Recurrent Reinforcement Learning and Federated Learning Academic Background The rapid development of the Industrial Internet of Things (IIoT) has profoundly transformed intelligent industrial systems, enabling data exchange, remote control, and smart decision-making b...

Adaptive Composite Fixed-Time RL-Optimized Control for Nonlinear Systems and Its Application to Intelligent Ship Autopilot

Engineering, Mechanical Engineering, Ocean Engineering, Transportation Engineering, Electrical Engineering, Information Science, Computer Science, Automation, Artificial Intelligence,
adaptive control   fixed-time control   reinforcement learning   nonlinear systems   neural networks   intelligent ships   optimization methods  

Nonlinear Fixed-Time Reinforcement Learning Optimized Control for Intelligent Ship Autopilots In recent years, intelligent autopilot technology has gradually become a research hotspot in the field of automation control. For complex nonlinear systems, the design of optimized control strategies, especially the achievement of system stability and perf...

Preference Prediction-Based Evolutionary Multiobjective Optimization for Gasoline Blending Scheduling

Chemistry, Chemical Engineering, Information Science, Automation, Artificial Intelligence,
preference prediction   multiobjective evolutionary optimization   gasoline blending   scheduling optimization   machine learning   cost efficiency   industrial applications  

Preference Prediction-Based Evolutionary Multiobjective Optimization for Gasoline Blending Scheduling Background Introduction With the continuous evolution of the global energy market, gasoline production and blending processes face increasing challenges. As a key product of the oil industry, gasoline’s blending and scheduling processes directly af...

Multilevel Ensemble Membership Inference Attack

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
machine learning   privacy attack   membership inference   data leakage   AI security  

In-depth Analysis of the Research Paper: MEMIA: Multilevel Ensemble Membership Inference Attack Introduction to the Research Background With the rapid development of digital technologies, artificial intelligence (AI) and machine learning (ML) have deeply permeated multiple domains, including healthcare, finance, retail, education, and social media....

Residual-Dense Network for Glaucoma Prediction Using Structural Features of Optic Nerve Head

Information Science, Artificial Intelligence, Medicine, Ophthalmology, Medical Imaging,
glaucoma   residual-dense network   optic nerve head   structural features   deep learning   optic cup   optic disc  

Using Residual Dense Network (RD-Net) for Glaucoma Prediction Based on Structural Features of the Optic Nerve Head Background and Research Purpose Glaucoma is one of the leading causes of blindness worldwide, often referred to as the “silent thief of sight.” It is characterized by the progressive degeneration of the optic nerve head (ONH), resultin...

Policy Consensus-Based Distributed Deterministic Multi-Agent Reinforcement Learning

Engineering, Electrical Engineering, Information Science, Computer Science, Artificial Intelligence,
policy consensus   distributed algorithms   multi-agent reinforcement learning   deterministic policy gradient   directed graphs   continuous control   deep reinforcement learning  

Policy Consensus-Based Distributed Deterministic Multi-Agent Reinforcement Learning Research Report Reinforcement Learning (RL) has made significant breakthroughs in recent years in various fields such as robotics, smart grids, and autonomous driving. However, in real-world scenarios, multi-agent collaboration problems, also known as Multi-Agent Re...

Spiking Diffusion Models

Information Science, Computer Science, Artificial Intelligence, Life Sciences, Biophysics,
spiking neural networks   diffusion models   low energy consumption   bio-inspired   image generation   temporal dynamics   threshold guidance  

Brain-Inspired Low-Power Generative Model: A Review on Spiking Diffusion Models Background Overview In recent years, the artificial intelligence field has seen a surge in cutting-edge technologies, with deep generative models (DGMs) demonstrating exceptional capabilities in producing images, text, and other types of data. However, these generative ...

Face Forgery Detection Based on Fine-grained Clues and Noise Inconsistency

Information Science, Electronic Information, Computer Science, Artificial Intelligence,
face forgery   deepfake detection   noise inconsistency   fine-grained clues   dual-domain attention fusion   transformer network   compressed domain  

In-depth Exploration of Face Forgery Detection Based on Fine-Grained Clues and Noise Inconsistency Background Introduction With the rapid advancement of artificial intelligence (AI) technologies, various generative models have achieved remarkable progress. This has made it increasingly easy to generate highly realistic “deepfake” face images. These...