OALib Journal
  OALib Journal is an all-in-one open access journal (ISSN Print: 2333-9705, ISSN Online: 2333-9721). It accepts a manuscript for the peer-review processing, typesetting, publication and then allocated to one of the 322 subject areas. The article processing charge for publishing in OALib journal is Only $99. For more details, please contact service@oalib.com. Submit now
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Sep 15, 2023Open    Access

Heavy-Head Sampling Strategy of Graph Convolutional Neural Networks for q-Consistent Summary-Explanations with Application to Credit Evaluation Systems

Xinrui Dou
Machine learning systems have found extensive applications as auxiliary tools in domains that necessitate critical decision-making, such as healthcare and criminal justice. The interpretability of these systems’ decisions is of paramount importance to instill trust among users. Recently, there have been developments in globally-consistent rule-based summary-explanation and its max-support (MSGC) problem, enabling the provision of explanations for specific decisions along with pertinent dataset s...
Open Access Library J.   Vol.10, 2023

Sep 03, 2021Open    Access

The Exploration of the Approach to Data Preparation for Chinese Text Analysis Based on R Language

Jiang Li
This paper explores how to prepare data for analyzing the Chinese texts with R language based on the theory of Welbers, particularly comparing the R package Rwordseg with jiebaR to see the results of Chinese text segmentation at the step of preprocessing.
Open Access Library J.   Vol.8, 2021

May 26, 2020Open    Access

New Principle of Busbar Protection Based on Active Power and Extreme Learning Machine

Syed Hassan Lal Gilani, Xingxing Dong, Haiyan Xu
In order to improve the reliability of busbar protection, a new fast busbar protection algorithm based on active power and extreme learning machine is proposed. By performing S-transformation on the fault voltage and current traveling wave, the active power amplitude within 0.1 ms after the fault is obtained. Simulate different fault types in the busbar area and build a bus fault feature vector sample set. The intelligent model of fault learning of extreme learning machine is established, and th...
Open Access Library J.   Vol.7, 2020

Feb 23, 2018Open    Access

Spreading Dynamic of a PLSGP Giving up Smoking Model on Scale-Free Network

Yanling Fei, Xiongding Liu
A new PLSGP (potential smokers-light smokers-persistent smokers-giving up smokers-potential smokers) model with birth and death rates on complex heterogeneous networks is presented. Using the mean-field theory, we obtain the basic reproduction number R0 and find that basic reproduction number for constant contact is independent of the topology of the underlying networks. When R0<1, the smoki
Open Access Library J.   Vol.5, 2018

May 22, 2017Open    Access

An SIS Epidemic Model with Infective Medium and Feedback Mechanism on Scale-Free Networks

Xiongding Liu, Tao Li, Yuanmei Wang, Chen Wan, Jing Dong
In this paper, a modified SIS (susceptible-infected-susceptible) model with infective medium and feedback mechanism on scale-free networks is presented. The model is suited to describe some epidemic spreading which are not only transmitting by medium but also spreading between individuals by direct contacts. Considering biological relevance and people’s subjecti
Open Access Library J.   Vol.4, 2017


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