Time series forecasts are used to predict a future value or a classification at a particular point in time. Here’s a brief overview of their common uses and how they are developed. Industries from ...
Singular Spectrum Analysis (SSA) is a powerful nonparametric method that has emerged as a vital tool in the analysis and forecasting of time series data. By utilising matrix decomposition techniques, ...
Artificial intelligence (AI) technologies are currently revolutionizing industries and enabling automation on a scale we've never seen before. Of course, none of this is possible without data. These ...
In the ever-evolving landscape of capital infrastructure projects, government agencies find themselves performing an intricate dance. The heightened focus on the timely and budget-conforming ...
Pre-trained foundation models are making time-series forecasting more accessible and available, unlocking its benefits for smaller organizations with limited resources. Over the last year, we’ve seen ...
In the wake of the disruptive debut of DeepSeek-R1, reasoning models have been all the rage so far in 2025. IBM is now joining the party, with the debut today of its Granite 3.2 large language model ...
According to IBM, attention is not all you need when forecasting certain outcomes with generative AI. You also need time. Earlier this year, IBM made its open-source TinyTimeMixer (TTM) model ...
1. Difference Equations -- 2. Lag Operators -- 3. Stationary ARMA Processes -- 4. Forecasting -- 5. Maximum Likelihood Estimation -- 6. Spectral Analysis -- 7 ...
With legacy load forecasting models struggling with unpredictable events that are becoming ever more common, power-hungry AI offers a solution.
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