Gang Li

Improved harmony search algorithms by tournament selection operator

2015

Harmony search algorithm (HS) is a meta-heuristic algorithm which is inspired by a process involving musical improvisation. It is a stochastic optimization technique, which is similar to genetic algorithms (GAs) and particle swarm optimizers (PSOs). …

An electricity data cluster analysis method based on SAGA-FCM algorithm

2017

The key technology to analyzing electricity data is cluster methods, of which the traditional way has already lost its agility and quality due to the increasing data volume. To this end, this paper presented an …

Multi-objective optimization algorithm based on improved particle swarm in cloud computing environment

2018 · Discrete and Continuous Dynamical Systems - S

In cloud computing environment, in order to optimize the deployment scheduling of resources, it is necessary to improve the accuracy of the optimal solution, guarantee the convergence ability of the algorithm, and improve the performance …

lou yu zi kong xi tong ji cheng ji shu ji wei lai fa zhan fang xiang

2016

楼宇自控系统是一个整体的监控和管理系统，它存在于智能的建筑中，依靠自动化的控制网络将建筑里面的每一个独立的楼宇进行控制，并形成一个集成化的控制管理体系。这些独立的楼宇自动控制也是存在于整个系统中的，所以，为了能够高效的对楼宇进行管理和监控，就要在楼宇自动控制的集成技术中进行深入的分析和研究，从中探索其更优良的管理和监督功能，形成一个可持续发展的自动集成体系。该文就对楼宇自控系统技术发展和未来发展的前景进行探讨，发觉其技术动向。

Research on Structured Extraction Method for Function Points Based on Event Extraction

2022 · Electronics

Software size is a significant input for software cost estimation, and the implementation of software size estimation dramatically affects the results and efficiency of cost estimation. Traditionally, the software size estimation is implemented by strictly …

Multi-classification assessment of personal credit risk based on stacking integration

2022 · Procedia Computer Science

In the multi-category assessment of personal credit risk, the prediction accuracy of a single classifier is often low, and each category cannot be well distinguished. In this paper, the stacking ensemble algorithm is used to …

ENEX-FP: A BERT-Based Address Recognition Model

2023 · Electronics

In e-commerce logistics, government registration, financial transportation and other fields, communication addresses are required. Analyzing the communication address is crucial. There are various challenges in address recognition due to the address text’s features of free …

FAIR-BFL: Flexible and Incentive Redesign for Blockchain-based Federated Learning

2022

Vanilla Federated learning (FL) relies on the centralized global aggregation mechanism and assumes that all clients are honest. This makes it a challenge for FL to alleviate the single point of failure and dishonest clients. …

Improving neural network’s robustness on tabular data with D-layers

2023 · Data Mining and Knowledge Discovery

Abstract Artificial neural networks ( $${{{\texttt {ANN}}}}$$ <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mi>ANN</mml:mi> </mml:math> ) are widely used machine learning models. Their widespread use has attracted a lot of interest in their robustness. Many studies show that ’s …

TF-GAN: Satellite Anomaly Detection via Generative Adversarial Networks and Time–Frequency Spectrum

2024 · IEEE Transactions on Aerospace and Electronic Systems

Anomaly detection for a noncooperative satellite is a fundamental and significant step in space situation awareness. To effectively detect the abnormal state of an on-orbit satellite, this article proposes a novel generative adversarial network with …

A Refined Knowledge Distillation Network for Unsupervised Anomaly Detection

2024 · Electronics

Knowledge distillation has been proven to be an important component in unsupervised image anomaly detection and localization. However, a significant challenge remains in how the student network can extract more accurate feature information from the …

Anomaly-Free Prior Guided Knowledge Distillation for Industrial Anomaly Detection

2024

In industrial manufacturing, visual anomaly detection is critical for maintaining product quality by detecting and preventing production anomalies. Anomaly detection methods based on knowledge distillation demonstrate promising performance in addressing the unpredictability and diversity of …

Stain Normalization of Histopathological Images Based on Deep Learning: A Review

2025 · Diagnostics

Histopathological images stained with hematoxylin and eosin (H&E) are crucial for cancer diagnosis and prognosis. However, color variations caused by differences in tissue preparation and scanning devices can lead to data distribution discrepancies, adversely affecting …

C-DPSS: Channel dual-phase sparsity pruning framework for spiking neural networks

2026 · Neurocomputing

Spiking Neural Networks (SNNs) have emerged as an essential paradigm for brain-inspired computing, achieving superior energy efficiency on neuromorphic hardware. However, as network scale increases, SNNs encounter growing challenges in deployment efficiency. While structured pruning …