Results 71 to 80 of about 846,186 (212)

Implementasl Algoritma Charm-L Dalam Menggali Frequent Closed Itemset [PDF]

, 2006
Himpunan Frequent Closed Itetnset Dapat Digunakan Untuk Mengeta.Hui Support Dari Semua Frequent Itemset Secara Tepat, Dan Jumlabnya Jebih Sedikit Daripada Jmnlah Frequent Itemset Yang Ditemukan Pada Minimum Support Yang Sama Algoritma CHARM-L ...
Kurniawati, Yenny
core  

Class Association Rule Pada Metode Associative Classification

IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2011
Frequent patterns (itemsets) discovery is an important problem in associative classification rule mining.  Differents approaches have been proposed such as the Apriori-like, Frequent Pattern (FP)-growth, and Transaction Data Location (Tid)-list ...
Eka Karyawati, Edi Winarko
doaj   +1 more source

A Design‐Driven Machine Learning Approach for Invariant Mining in a Smart Grid

IET Cyber-Physical Systems: Theory &Applications, Volume 11, Issue 1, January/December 2026.
An ICS is vulnerable to cyber‐attacks arising from within its communication network or directly from the SCADA and devices such as PLCs. The study reported here presents a scenario‐specific invariant mining approach to detect anomalies in plant behaviour.
Danish Hudani, Muhammad Haseeb, Muhammad Taufiq, Muhammad Azmi Umer, Nandha Kumar Kandasamy, Aditya P. Mathur   +5 more
wiley   +1 more source

Extraction of Safe Operation Rules and Identification of Vulnerable Nodes in Power Grids Based on Time‐Series Association Analysis

IET Generation, Transmission &Distribution, Volume 20, Issue 1, January/December 2026.
This paper presents a data‐driven framework for operational safety rule extraction and vulnerable node identification in power grids with high renewable penetration. The effectiveness of the proposed method is verified on the IEEE 39‐bus system for static security assessment. ABSTRACT High renewable energy penetration introduces significant uncertainty
Zhilin Huang, Zheng Xu, Yudun Li, Yanqi Hou, Facai Xing, Zhi Gao, Yiping Yu   +6 more
wiley   +1 more source

IMPLEMENTASI ALGORITMA APRIORI UNTUK MENEMUKAN FREQUENT ITEMSET DALAM KERANJANG BELANJA [PDF]

, 2016
Algoritma apriori menggunakan pendekatan iteratif dimana k-itemset digunakan untuk mengeksplorasi (k+1)-itemset. Calon (k+1)-itemset yang mengandung frekuensi subset yang jarang muncul atau dibawah threshold akan dipangkas dan tidak dipakai menentukan ...
I Ketut Gede Darma Putra, Adie Wahyudi Oktavia Gama, I Putu Agung Bayupati   +2 more
core  

A Fast Approach for Up-Scaling Frequent Itemsets

IEEE Access, 2020
With the rapid growth of data scale and diversification of demand, people have an urgent desire to extract useful frequent itemset from datasets of different scales. It is no doubt that the traditional method can solve the problem.
Runzi Chen, Shuliang Zhao, Mengmeng Liu
doaj   +1 more source

From Prediction to Prevention: Using Text Mining and Explainable Machine Learning for Urban Bus Accident Analytics

Risk Analysis, Volume 46, Issue 1, January 2026.
ABSTRACT Urban bus accidents present major safety and operational challenges, particularly in densely populated metropolitan areas. This study develops a machine learning‐based analytical framework to identify, quantify, and interpret the factors associated with severe bus accidents.
Bowei Chen, Yufei Huang, Yu Zheng, Xiaofeng Liu   +3 more
wiley   +1 more source

Mining frequent closed itemsets with the frequent pattern list [PDF]

Proceedings 2001 IEEE International Conference on Data Mining, 2002
The mining of a complete set of frequent itemsets will lead to a huge number of itemsets. Fortunately, this problem can be reduced to the mining of frequent closed itemsets (FCIs), which results in a much smaller number of itemsets. The approaches to mining frequent closed itemsets can be categorized into two groups: those with candidate generation and
Tseng, Fan-Chen, Hsu, Ching-Chi, Chen, Henry   +2 more
openaire   +2 more sources

Correlation Analysis of Influencing Factors of Autonomous Vehicle Accidents Based on Improved Apriori Algorithm

Journal of Advanced Transportation, Volume 2026, Issue 1, 2026.
The purpose of this study was to explore the risk factors for autonomous vehicle (AV) crashes and their interdependencies. A total of 659 AV crash data were collected between 2018 and July 2024 from AV crash reports published by the California Department of Motor Vehicles.
Tao Wang, Wenzhi Tang, Juncong Chen, Wenwu Chen, Mohammad Rezwan Habib   +4 more
wiley   +1 more source

RPriori: A Divide‐and‐Conquer Frequent Itemset Mining Algorithm With Improved Time‐Space Efficiency on Large Transactional Data

Complexity, Volume 2026, Issue 1, 2026.
Frequent itemset mining (FIM) is a fundamental task in data mining with applications ranging from market basket analysis and recommendation systems to fraud detection and bioinformatics. However, mining frequent itemsets from massive datasets remains computationally challenging due to high execution time and memory consumption.
Rahat Ali Shah, Jamal Uddin, Hameed Hussain, Khaistah Khan, Shujaat Ali, Dilawar Shah, Muhammad Tahir, Shonak Bansal   +7 more
wiley   +1 more source