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Quantum FP-growth algorithm using GPU simulation- application to digital soil mapping
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DOI：10.1016/j.asoc.2025.114011.png)
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Abstract
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• A novel Quantum FP-growth was proposed and its time and space complexity analyzed. • QFP-growth implementation and extensive experiments were conducted. • Iterative QAE is the most accurate and efficient for support counting. • GPU simulation benefits QFP-growth, but cuQuantum’s StateVector had minimal impact. • First quantum itemset mining application in Digital Soil Mapping for soil science.
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6.6
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1.4W
Citations:
4.8W
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Cited Papers
SoilGrids 2.0: producing soil information for the globe with quantified spatial uncertainty.png)
SOIL
OAAI
SOILIF4.3
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EXPERT SYSTEMSIF2.3
PREAI
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