Results 51 to 60 of about 498 (210)

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

open access: yesRisk 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

Mining High Utility Itemsets Based on Pattern Growth without Candidate Generation

open access: yesMathematics, 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

FTKHUIM: A Fast and Efficient Method for Mining Top-K High-Utility Itemsets

open access: yesIEEE 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

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

open access: yesJournal 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

Identifying the Focus Word in Natural Language Questions Based on Association Rules

open access: yesInternational Journal of Intelligent Systems, Volume 2026, Issue 1, 2026.
Knowledge base‐based intelligent question‐answering systems have insufficient understanding of the questions. In the early stages of research, it is effective in most cases that the existing natural language question‐understanding methods can answer questions by connecting entities and relationships when ignoring the identification of focus words ...
Xin Hu   +5 more
wiley   +1 more source

PUC: parallel mining of high-utility itemsets with load balancing on spark

open access: yesJournal 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

mHUIMiner: A Fast High Utility Itemset Mining Algorithm for Sparse Datasets

open access: yes, 2017
High utility itemset mining is the problem of finding sets of items whose utilities are higher than or equal to a specific threshold. We propose a novel technique called mHUIMiner, which utilises a tree structure to guide the itemset expansion process to
Peng, AY   +5 more
core   +1 more source

Taming the Triangle: On the Interplays Between Fairness, Interpretability, and Privacy in Machine Learning

open access: yesComputational Intelligence, Volume 41, Issue 4, August 2025.
ABSTRACT Machine learning techniques are increasingly used for high‐stakes decision‐making, such as college admissions, loan attribution, or recidivism prediction. Thus, it is crucial to ensure that the models learnt can be audited or understood by human users, do not create or reproduce discrimination or bias and do not leak sensitive information ...
Julien Ferry   +4 more
wiley   +1 more source

High Utility Itemset Mining by Using Binary PSO Algorithm

open access: yes, 2022
The goal of pattern mining is to find some novel patterns from a given database. High utility itemset mining (HUIM) is a research direction of the pattern mining as a sub-domain of data mining.
TAO BODONG
core  

A novel transformer health state direct prediction method based on knowledge and data fusion‐driven model

open access: yesHigh Voltage, Volume 10, Issue 3, Page 710-725, June 2025.
Abstract Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer, thereby facilitating the formulation of power outage maintenance plans and power dispatch strategies. However, existing prediction methods based on the structure of ‘splicing prediction and diagnosis method’ suffer ...
Peng Zhang   +5 more
wiley   +1 more source

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