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• W2954088740 abstract "The characterization of the resistance of transmission towers is a difficult and costly procedure which can be mitigated using statistical techniques. A stratified sampling process based on the characteristic of the terrain was shown in previous works to reduce the error in the statistical inference; however, such characteristics are usually unknown before a measure is made. In this work, we present a system which integrates artificial intelligence techniques, such as k-nearest neighbors, decision trees, or random forests, to automatically optimize the workflow of expert workers using various sources of data." @default.
• W2954088740 created "2019-07-12" @default.
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• W2954088740 date "2019-06-23" @default.
• W2954088740 modified "2023-09-30" @default.
• W2954088740 title "Design of an AI-Based Workflow-Guiding System for Stratified Sampling" @default.
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• W2954088740 doi "https://doi.org/10.1007/978-3-030-24097-4_13" @default.
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