Hello, I was proposed a new challenge from my research process and the truth is that I have not been able to face it due to my lack of knowledge.
I have a time series that indicates the number of visits to a post, on a daily basis, the idea is to create an alert system that notifies me when the numbers of visits are above and below the historical number, I have thought of implement time series but I don’t know the process to evaluate and create alerts visitors.xlsx (15.8 KB)
this is the base in case someone wants to help me
Hi @bruno29a I was talking to a professor who handles the subject better than me and he told me that he could look for a model that would best adapt in this case a SARIMA after that forecast one day and create a confidence interval and if the real value came out of that interval could generate an alert, is this possible with knime?
This is a very common problem in signal processing which can be solved in many different ways, e.g. using a Moving Average linear Model (or ARIMA, SARIMA, etc.).
I’m adding here below a different and very simple approach based on the -Moving Aggregation- node using two different configurations. One is based on Min-Max absolute values from beginning of signal. The second solution is using a sliding window of size 21 (which could be changed to what you want):
In other words, the first solution is telling you which are the historical Min-Max from the beginning of the signal history. The second solution only remembers the Min-Max historical value from the last 21 recorded samples of the signal.
I saw the thread you mention @ScottF and I guessed both threads were related. I’ll be glad to have feedback from you if you reach a solution to this problem based on SARIMA.
Thanks @Jalvear & @ScottF for your answers.