Which machine learning technique has revolutionized inventory forecasting for scientific equipment retailers by incorporating both seasonal research cycles and unpredictable grant funding patterns?

The intersection of science and retail has transformed inventory management through advanced technologies. Machine learning algorithms now help scientific equipment retailers predict stock needs with unprecedented accuracy. This poll tests your knowledge of how cutting-edge ML techniques are being applied to optimize inventory in specialized scientific supply chains, reducing waste while ensuring critical research materials remain available when needed.

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Ensemble Models combining Random Forests with LSTM neural networks
Simple linear regression with seasonal adjustments
Unsupervised clustering algorithms with no temporal components
Rule-based expert systems that rely on pre-programmed inventory thresholds