In a global economy marked by fragile supply chains, scarce resources and rising energy costs, the spotlight is on forecasting to address these issues. In 2022, McKinsey & Company uncovered a staggering $600 billion annual food waste, equating to 33% – 40% of global food production, spotlighting the devastating consequences
Time series data is widely used in various fields, such as finance, economics, and engineering. One of the key challenges when working with time series data is detecting level shifts. A level shift occurs when the time series’ mean and/or variance changes abruptly. These shifts can significantly impact the analysis and forecasting of the time series and must be detected and handled properly.
Even with today's technology, it's hard to know precisely when, where and how weather-related damage will occur. Flooding costs are expected to rise drastically during the next 20 years and climate change is a constant threat. Unfortunately, natural disasters are here to stay, but we can try our best to
