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KI-Glossar

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Anomaly Detection in Streams

Algorithm identifying in real-time observations that deviate significantly from expected patterns in a temporal data stream.

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Concept Drift

Gradual or abrupt change in the underlying distribution of temporal data, requiring dynamic adaptation of predictive models.

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Temporal Aggregation

Process of reducing temporal granularity by combining multiple data points according to statistical functions (mean, sum, max).

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Kalman Filtering

Recursive algorithm for optimal estimation of the state of a linear dynamic system from noisy real-time observations.

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Partial Autocorrelation

Measure of correlation between an observation and its past values while eliminating the effect of intermediate observations.

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Temporal Resampling

Process of modifying the sampling frequency of a time series through interpolation or aggregation to standardize data.

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ARIMA Models in Streams

Adaptive extension of ARIMA models handling continuous time series with dynamic updating of autoregressive parameters.

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Wavelet Transformation

Time-frequency decomposition analyzing time series at different scales to capture local and transient patterns.

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Temporal Synchronization

Temporal alignment of multiple heterogeneous data streams to ensure consistency in real-time multivariate analyses.

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Temporal Vector Quantization

Compression of temporal sequences into optimized discrete representations preserving essential characteristics of the flow.

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Temporal Quantile Regression

Conditional modeling of time series quantiles to capture uncertainty and extremes in forecasts.

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