Results 51 to 60 of about 2,164 (156)
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 +5 more
wiley +1 more source
Mining Correlated High Utility Itemsets in One Phase
IEEE Access, 2020 High-utility itemset mining (HUIM) in transaction databases has been extensively studied to discover interesting itemsets from users' purchase behaviors. With this, business managers can adjust their sale strategies appropriately to increase profit. HUIM
Bay Vo +8 more
doaj +1 more source
FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets
IEEE Access, 2023 High-utility itemset mining (HUIM) is an important task in the field of knowledge data discovery. The large search space and huge number of HUIs are the consequences of applying HUIM algorithms with an inappropriate user-defined minimum utility threshold
Vinh V. Vu +8 more
doaj +1 more source
Improving the quality of the personalized electronic program guide [PDF]
, 2003 As Digital TV subscribers are offered more and more channels, it is becoming increasingly difficult for them to locate the right programme information at the right time.
McDonald, Kieran +4 more
core +1 more source
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 +6 more
wiley +1 more source
Mining High Utility Itemsets Based on Pattern Growth without Candidate Generation
Mathematics, 2020 Mining high utility itemsets (HUIs) has been an active research topic in data mining in recent years. Existing HUI mining algorithms typically take two steps: generating candidates and identifying utility values of these candidate itemsets.
Yiwei Liu, Le Wang, Lin Feng, Bo Jin
doaj +1 more source
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 +3 more
wiley +1 more source
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 +4 more
wiley +1 more source
PUC: parallel mining of high-utility itemsets with load balancing on spark
Journal of Intelligent Systems, 2022 Distributed programming paradigms such as MapReduce and Spark have alleviated sequential bottleneck while mining of massive transaction databases. Of significant importance is mining High Utility Itemset (HUI) that incorporates the revenue of the items ...
Brahmavar Anup Bhat +2 more
doaj +1 more source
Utility-driven Data Analytics on Uncertain Data
, 2019 Modern Internet of Things (IoT) applications generate massive amounts of data, much of it in the form of objects/items of readings, events, and log entries.
Chao, Han-Chieh +4 more
core +1 more source