A data-knowledge-driven interval type-2 fuzzy neural network with interpretability and self-adaptive structure
Interval type-2 fuzzy neural networks (IT2FNNs) have gained sustainable attention and wide
applications because of their power of adaptive fuzzy modeling. Although the existing …
applications because of their power of adaptive fuzzy modeling. Although the existing …
Rule-based back propagation neural networks for various precision rough set presented KANSEI knowledge prediction: a case study on shoe product form features …
Nonlinear operators for KANSEI evaluation dataset were significantly developed such as
uncertainty reason techniques including rough set, fuzzy set and neural networks. In order to …
uncertainty reason techniques including rough set, fuzzy set and neural networks. In order to …
A new framework for metaheuristic-based frequent itemset mining
This paper proposes a novel framework for metaheuristic-based Frequent Itemset Mining
(FIM), which considers intrinsic features of the FIM problem. The framework, called META …
(FIM), which considers intrinsic features of the FIM problem. The framework, called META …
An improved eclat algorithm based association rules mining method for failure status information and remanufacturing machining schemes of retired products
L Wang, Y Guo, Y Guo, X Xia, Z Zhang, J Cao - Procedia CIRP, 2023 - Elsevier
Mining association rules between failure status information (FSI) and remanufacturing
machining schemes (RMMS), and establishing their association rule base, is the basis and …
machining schemes (RMMS), and establishing their association rule base, is the basis and …
[PDF][PDF] 基于多维技术创新地图与关联规则挖掘的技术机会识别方法研究
岳俊举， 冯立杰， 冯奕程， 王金凤 - 情报学报, 2017 - ijosi.org
摘要识别技术机会是决定技术创新成败的关键, 提高技术机会识别能力对于企业乃至产业发展至
关重要. 该研究以专利数据分析为基础, 首先通过技术创新要素提取与关联规则挖掘获得技术 …
关重要. 该研究以专利数据分析为基础, 首先通过技术创新要素提取与关联规则挖掘获得技术 …
Selection of satisfied association rules via aggregation of linguistic satisfied degrees
F Ren, Z Pei, K Wu - IEEE Access, 2019 - ieeexplore.ieee.org
Many association rule mining algorithms have been well-established, such as Apriori, Eclat,
FP-Growth, or LCM algorithms. However, the challenge is that the huge size of association …
FP-Growth, or LCM algorithms. However, the challenge is that the huge size of association …
A multi-resident activity recognition approach based on frequent itemset mining features
W Yuan, J Cao, Z Jin, F Xia… - 2019 IEEE 17th …, 2019 - ieeexplore.ieee.org
Activity recognition is one of the most important supporting technologies for smart-home
applications, and most existing works conducted on this topic assume that there is only one …
applications, and most existing works conducted on this topic assume that there is only one …
Prototype infrastructure cloud expert system DNA Analysis (CESDA) as the basis of sustainability DNA software improvement in Indonesia
B Al Kindhi, TA Sardjono… - 2017 European …, 2017 - ieeexplore.ieee.org
Expert system DNA analysis is not a new application for the medical world, this expert
system has long been used as a tool for analyzing the structure of DNA. The function of this …
system has long been used as a tool for analyzing the structure of DNA. The function of this …
An adaptive gradual relational association rules mining approach
DL MIHOLCA - Studia Universitatis Babeș-Bolyai Informatica, 2018 - 193.231.18.162
This paper focuses on adaptive Gradual Relational Association Rules mining. Gradual
Relational Association Rules capture gradual generic relations among data features. We …
Relational Association Rules capture gradual generic relations among data features. We …
Dynamic machine learning for supervised and unsupervised classification
AM Sîrbu - 2016 - theses.hal.science
The research direction we are focusing on in the thesis is applying dynamic machine
learning models to salve supervised and unsupervised classification problems. We are …
learning models to salve supervised and unsupervised classification problems. We are …