Results 61 to 70 of about 6,703 (218)
Parallel Implementation of Apriori Algorithm Based on MapReduce [PDF]
International Journal of Networked and Distributed Computing (IJNDC), 2013 Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task.
Ning Li, Li Zeng, Qing He, Zhongzhi Shi
doaj +1 more source
Total Variation Regularized GRACE(‐FO) Inversion
Journal of Geophysical Research: Solid Earth, Volume 131, Issue 5, May 2026.Abstract Gravity estimation from satellite‐satellite tracking missions such as GRACE(‐FO) is an ill‐posed inverse problem. The conventional approach to regularized inversion of GRACE(‐FO) measurements uses L2 ${L}_{2}$‐Tikhonov regularization with a heuristic constraint matrix derived based on knowledge of spatiotemporal distribution of the signal ...
G. Jacob +4 more
wiley +1 more source
A Prefixed-Itemset-Based Improvement for Apriori Algorithm
Computer Science & Information Technology ( CS & IT ), 2016 9 pages, 2 ...
Shoujian Yu, Yiyang Zhou
openaire +2 more sources
Application of Data Assimilation Methods to Reconstruct the 3–5 December 2015 Etna Eruption
Geophysical Research Letters, Volume 53, Issue 7, 16 April 2026.Abstract The assessment of volcanic hazards is crucial to develop effective emergency plans, especially for volcanoes close to urban areas or under air traffic routes. Impact assessment for expected scenarios relies on underlying numerical models that require eruption source parameters as inputs, and forecasts drastically depend on their robust ...
B. Martínez Montesinos +7 more
wiley +1 more source
Usage Apriori and clustering algorithms in WEKA tools to mining dataset of traffic accidents
Journal of Information and Telecommunication, 2018 The aim of this study is finding approaches for investigating association rules mining algorithms and clustering to offer new rules from a broad set of discovered rules which taken from traffic accident data at Alghat Provence in KSA.
Faisal Mohammed Nafie Ali +1 more
doaj +1 more source
Advanced Intelligent Discovery, Volume 2, Issue 2, April 2026.Combining machine learning and probabilistic statistical learning is a powerful way to discover and design new materials. A variety of machine learning approaches can be used to identify promising candidates for target applications, and causal inference can help identify potential ways to make them a reality.
Jonathan Y. C. Ting, Amanda S. Barnard
wiley +1 more source
Energy Science &Engineering, Volume 14, Issue 4, Page 2318-2344, April 2026.A new energy paradigm assisted by AI. ABSTRACT The tremendous penetration of renewable energy sources and the integration of power electronics components increase the complexity of the operation and power system control. The advancements in Artificial Intelligence and machine learning have demonstrated proficiency in processing tasks requiring ...
Balasundaram Bharaneedharan +4 more
wiley +1 more source
ZAMM - Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, Volume 106, Issue 4, April 2026.ABSTRACT The Duffing oscillator is often considered as “the” prototype of a nonlinear oscillator as it exhibits many characteristic phenomena of nonlinear dynamics. One of these phenomena is the occurrence of multiple periodic solutions as considered here for the case of the harmonically excited slightly damped Duffing oscillator.
Hannes Dänschel +3 more
wiley +1 more source
Personalized and Explainable Aspect‐Based Recommendation Using Latent Opinion Groups
Computational Intelligence, Volume 42, Issue 2, April 2026.ABSTRACT The problem of explainable recommendation—supporting the recommendation of a product or service with an explanation of why the item is a good choice for the user—is attracting substantial research attention recently. Recommendations associated with an explanation of how the aspects of the chosen item may meet the needs and preferences of the ...
Maryam Mirzaei +2 more
wiley +1 more source
Symbolic Data Mining in Databases Using the Apriori Algorithm
, 2013 This thesis discusses symbolic data mining, its concepts and uses in the discovery of knowledge hidden in large datasets. Data mining is a multidisciplinary field, drawing work from areas including database technology, machine learning, statistics ...
Imouokhome, Eseohen
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