Results 61 to 70 of about 794 (166)
Data‐Driven Materials Research and Development for Functional Coatings
Functional coatings play a vital role in various industries for their protective and functional properties. However, its design often involves time‐consuming experimentation with multiple materials and processing parameters. To overcome these limitations, data‐driven approaches are gaining traction in materials science. This review provides an overview
Kai Xu +8 more
wiley +1 more source
Factors significantly associated with physical activity outcomes in people with dementia in the final regression models. The figure highlights that psychosocial factors are associated with different constructs related to physical activity. Only the presence of intrapersonal barriers to physical activity was associated with both total physical activity ...
Nicolas Farina +5 more
wiley +1 more source
Negative and Positive Association Rules Mining from Text Using Frequent and Infrequent Itemsets
Association rule mining research typically focuses on positive association rules (PARs), generated from frequently occurring itemsets. However, in recent years, there has been a significant research focused on finding interesting infrequent itemsets ...
Sajid Mahmood +2 more
doaj +1 more source
Mining frequent itemsets from streaming transaction data using genetic algorithms
This paper presents a study of mining frequent itemsets from streaming data in the presence of concept drift. Streaming data, being volatile in nature, is particularly challenging to mine.
Sikha Bagui, Patrick Stanley
doaj +1 more source
This paper proposes an electric vehicle (EV) load diagnosis algorithm considering data privacy. The validity of the algorithm in this paper is verified by using the real collected EV load data. Abstract Accurate forecasting of electric vehicle (EV) load is essential for grid stability and energy management. EV load forecasting is influenced by multiple
Ruien Bian +3 more
wiley +1 more source
Reconstructing thicket clump formation using association rules analysis
Association rules (or market basket) analysis was effective in eliciting common associations between species and size classes across different stages of thicket clump formation in a savanna. Vachellia karroo established alone in open grassland, whereas a suite of clump‐initiating species recruited in close association with large V.
Rhys Nell +2 more
wiley +1 more source
Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach
Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of
A. V. Senthil Kumar, R. S. D. Wahidabanu
doaj
An association rule-based approach for frequent item mining of multi-stage access data
The processing of large-scale datasets is complex and requires high efficiency. The database needs to be scanned multiple times by traditional Apriori algorithms to generate candidate itemsets, resulting in significantly reduced efficiency, but also have
Silong Wu
doaj +1 more source
A Robust Technique for Closed Frequent and High Utility Itemsets Mining: Closed-FHUIM
Frequent itemset mining (FIM) and high utility itemset mining (HUIM) are popular data mining techniques used in various real-world applications such as retail-market, bio-medicine, and click-stream analysis.
Muhammad Waheed Ashraf +2 more
doaj +1 more source
Frequent Itemsets Mining With Differential Privacy Over Large-Scale Data
Frequent itemsets mining with differential privacy refers to the problem of mining all frequent itemsets whose supports are above a given threshold in a given transactional dataset, with the constraint that the mined results should not break the privacy ...
Xinyu Xiong +6 more
doaj +1 more source

