machine learning
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With evolving targets and techniques, the digital landscape is quaking. Are you cyber-ready for the threats?
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Research shows how to understand the role of individual neurons in a neural network.
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Like biological brains, artificial neural networks may depend on slow-wave sleep for learning.
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Machine learning enables fast, cost-effective, and accurate methane emissions detection in remote areas.
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Despite streams of data being available on platforms about the condition of topside and drilling equipment, most experts agree that only a small fraction of such data is used. Whether for a fleet or single platform, AI can transform an offshore enterprise.
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An AI-based application enabled operators to preempt ESP failures while optimizing production.
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Artificial intelligence systems can be trained to recognize visual content in drawings and provide a simplified context. The complete paper highlights the use of AI to process a scanned drawing and redrawing it on a digital platform.
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Time-stamped data anomalies can lead to more-accurate identification and faster diagnosis.
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Increasing accuracy in models is often obtained through the first steps of data transformations. This guide explains the difference between the key feature-scaling methods of standardization and normalization and demonstrates when and how to apply each approach.
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This paper presents a fatigue-prediction methodology designed to extend the life of unbonded flexible risers and improve the accuracy of floating production, storage, and offloading vessel response analysis.