Hui Li

An Effective Hybrid Fraud Detection Method

2015 · Lecture notes in computer science

The rapid growth of data makes it possible for us to study human behavior patterns. Knowing the patterns of human behavior is of great use to help us detect the unusual fraud human behavior. Existing …

Class Management under the Environment of New Media

2016

With the constant progress and development of society, we have already stepped into the Information Age, in which a variety of emerging new media has trickled into people's real life. All kinds of online study …

Healthcare Fraud Detection Based on Trustworthiness of Doctors

2016

Big data is now rapidly expanding into various domains such as banking, insurance and e-commerce. Data analysis and related studies have attracted more attentions. In health insurance, abuse of diagnosis is one of the key …

Forum topic detection based on hierarchical clustering

2016

Forum has become one of the main platforms for people to express their personal point of view, with a lot of information surging in the forum everyday. How to detect automatically a forum topic among …

Information Literacy Assessment with a Modified Hybrid Differential Evolution with Model-Based Reinitialization

2018 · Computational Intelligence and Neuroscience

Information literacy assessment is extremely important for the evaluation of the information literacy skills of college students. Intelligent optimization technique is an effective strategy to optimize the weight parameters of the information literacy assessment index …

PoV: An Efficient Voting-Based Consensus Algorithm for Consortium Blockchains

2020 · Frontiers in Blockchain

The blockchain has a great vogue in recent years, and its core consensus algorithms also become the focus of research. At present, most of the research on consensus mechanisms are oriented to the public blockchain …

Intention Propagation for Multi-agent Reinforcement Learning

2021

A hallmark of an AI agent is to mimic human beings to understand and interact with others. In this paper, we propose a \emph{collaborative} multi-agent reinforcement learning algorithm to learn a \emph{joint} policy through the …

Fusion Estimation for Multi-sensor Nonlinear System with Disorder and Packet Loss

2020

For a multi-sensor nonlinear system with disorder and packet loss, a fusion estimation algorithm is presented in this paper. Firstly, for equally spaced measurement sampling system, the disorder measurement is sorted by using measurement prediction …

One Method for Implementing Privacy Protection of Electronic Invoices Based on Blockchain

2021 · 2021 IEEE International Conference on Power Electronics, Computer Applications (ICPECA)

In view of the fact that the blockchain system is essentially a distributed ledger, the data privacy of electronic invoices needs to be protected, and the electronic invoice circulation environment needs security support, we proposed …

Multi-Objective Optimization-Based Recommendation for Massive Online Learning Resources

2021 · IEEE Sensors Journal

As an important research topic in intelligent teaching systems, personalized recommendation services of learning resources can effectively solve the “information overload” problem and provide effective learning. However, the traditional learning resource recommendation technology mainly aims …

Finding nash equilibrium for imperfect information games via fictitious play based on local regret minimization

2022 · International Journal of Intelligent Systems

Finding Nash equilibrium in the domain of imperfect information games as a challenging problem has received much attention. Neural Fictitious Self-Play (NFSP) is a popular model-free machine learning algorithm and has computed approximate Nash equilibrium …

Research on automatic scoring algorithm for English composition based on machine learning

2024

It is difficult to extract deep semantic features for English composition scoring methods based on artificial features, and it is difficult for English composition scoring methods based on neural networks to extract shallow features such …

Efficient and Privacy-Preserving Federated Learning Against Poisoning Adversaries

2024 · IEEE Transactions on Services Computing

The ever-growing data scale and increasingly strict privacy restraint have recently drawn extensive attention to federated learning (FL) as a multi-party machine learning paradigm for achieving high-quality model construction without data collection. Nevertheless, uploading local …

Fuzzy based Fall Risk Prediction in Older Adults

2024

The global elderly population is increasing rapidly, leading to a rise in chronic illnesses and co-existing conditions, which in turn results in higher healthcare expenses. Accidental falls are among the leading causes of injury-related deaths …

Adaptive Labeled Multi-Bernoulli Filter With Pairwise Markov Chain Model and Student's <i>t</i> Noise

2024 · IEEE Transactions on Aerospace and Electronic Systems

In the multitarget tracking (MTT) field, the MTT algorithm with hidden Markov chain (HMC) models typically assumes that process and measurement noises in the motion process obey independent Gaussian distributions. However, these assumptions of independence …

Research on coal mine gas overrun risk assessment based on analytic hierarchy process-principal component analysis and cloud model algorithm

2024

In response to the inadequacies of the current methods for assessing the risk of coal mine gas overrun limits, including weak foundational techniques and limited visualization, this study integrates the AHP-PCA and cloud model algorithms …

"Research on the Application of AI in Principle Courses of Vocational and Technical Education——Taking the Course of "Principles of Optical Fiber Communication" as An Example"

2025

With the rapid progress of artificial intelligence technology, the principle courses in vocational and technical education are faced with the problems of boring teaching content, single teaching method and one-sided evaluation system. Taking the course …

Advancing SMoE for Continuous Domain Adaptation of MLLMs: Adaptive Router and Domain-Specific Loss

2025

Recent studies have explored Continual Instruction Tuning (CIT) in Multimodal Large Language Models (MLLMs), with a primary focus on Task-incremental CIT, where MLLMs are required to continuously acquire new tasks.However, the more practical and challenging …

RecSys-DAN: Discriminative Adversarial Networks for Cross-Domain Recommender Systems

2019 · IEEE Transactions on Neural Networks and Learning Systems

Data sparsity and data imbalance are practical and challenging issues in cross-domain recommender systems (RSs). This paper addresses those problems by leveraging the concepts which derive from representation learning, adversarial learning, and transfer learning (particularly, …