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Found 6 results

1. ## Create forecast based on signal value

Hi, I'm trying to create forecast when the pressure will reach low alarm after last top up (top up indicate with red mark in pic below) Now, I'm temporary using this formula: \$signal.agileFilter(10min).forecastLinear(3d, 1 mo) But this formula will calculate the forecast with 3 days ago data, not the last top up. Is there another way to create the forecast based on specific signal value? not a fixed day? Thank you
2. ## Signal forecasting trained on only the current cycle

When creating signal forecasts, especially for cyclic signals that degrade, we often use forecastLinear() in formula to easily forecast a signal out into the future to determine when a threshold is met. The methodology is often the same regardless of if we are looking at a filter, a heat exchanger, or any other equipment that fouls overtime or any equipment that needs to go through some periodic maintenance when a KPI threshold is met. A question that comes up occasionally from users is how to create a signal forecast that only uses data from the current operation cycle for signal forecasting. The forecastlinear() operator only takes into account a historical training period and does not determine if that data is coming from the current cycle or not (which results in unexpected results). Before entering the formula, you will need to define: a condition that identifies the current cycle, here i have called it "\$runningCycle" a Signal to do a linear forecast on, i have called it "\$signal" To forecast out into the future based on only the most recent cycle, the following code snippet can be used in formula: \$training = \$runningCycle.setmaximumduration(10d).toGroup(capsule(now()-2h, now())) \$forecast=\$Signal.predict(\$training, timesince(toTime('2000-01-01T00:00Z'))) \$signal.forecastSplice(\$forecast, 1d) In this code snippet, there are a few parameters that you might want to change: .setMaximumDuration(10d): results in a longest cycle duration of 10 days, this should be changed to be longer than the longest cycle you would expect to see capsule(now-2h, now()): this creates a period during which seeq will look for the most recent cycle. In this case it is any time in the last 2 hours. If you have very frequent data (data comes in every few seconds to minutes) then 2 hours or less will work. If you have infrequent data (data that comes in once a day or less) then extend this so that it covers the last 3-4 data points. \$signal.forecastSplice(\$forecast, 1d): When using forecastLinear(), there is an option to force the prediction through the last sample point. This date parameter (1 day in this case) does something similar- it blends the last historical data point with the forecast over the given time range. In other words, if the last data point was a value of 5, but my first forecasted datapoint had a value of 10, this parameter is the time frame over which to smooth from the historical data point to the forecast. Here is a screenshot of my formula : and the formula in action:
3. ## A signal for training duration parameter in ForecastLinear

Hi all, So I am trying to create a linear forecast that has a constantly changing training duration as one of the parameter. For example : \$inputsignal.ForecastLinear(\$durationsignal,forecastduration) This is because sometimes the input signal has a step change and I would want to reset the forecast duration to start again from this step change. Is this something possible to execute? or is there any alternative method? Thanks all.
4. ## Showing Scorecard metric of when signal crosses threshold

Hi, My aim is to create an organizer topic with a metric that shows the forecast when a signal will cross a threshold. Is there a way to do this? Or is there another way where I can show in a Date format of when a certain signal is forecasted to cross a threshold that I can insert and automatically update in the organizer.
5. ## Combining past Signal Data with Future Predictions

When performing certain types of analysis, it is desirable to combine past measured data with some future prediction, whether that prediction is dynamic or static. Future predicted data can be used for degradation or maintenance date predictions, future performance modeling, signal forecasting, or a wide variety of other potential use cases. Combining some future data with a measured signal is simple in Seeq! Another major benefit? As new data comes in the predicted values can be automatically updated with the actual data! Here is one way to join past measured data with some future forecast signal. Signals To combine measured and forcasted data we will need: Measured Data - a signal(s) that will replace the predicted signal as it becomes available Prediction / Forecast Signal - This could be a flat signal entered in formula, a signal developed in the prediction tool, or some other signal that extends out into the future Method for Combining the Signals 1. Create Future Data Valid Condition This Condition defines the period of time in which the Forcasted signal will be spliced into the Measured Data signal. The formula is based on the last known measured time stamp. In formula we will create a condition by inputting the code snippet below and calling it \$validPlanningRange Formula: /* Define the period when planning data should be used. This time period will start at now (i.e., the last available measured data point) and extend to some point in the future. */ //Define a search window to look for now, This must have a past time to start in, and a future time to look through \$searchPeriod = capsule('2018-08-01T00:00-08:00', '2020-01-01T00:00-08:00') //Identify now by finding the last available measured time stamp \$now = \$measuredData.toGroup(\$searchPeriod).last().getKey() //Create a condition representing now to now plus 6 months \$nowCapsule = capsule(\$now, \$now + 6 months) condition(7 months, \$nowCapsule) Variable Descriptions \$searchPeriod - Capsule defining the search window which will be used to located the most recent data point. For best performance, the start date should be periodically updated to limit the number of measured data points which will be returned. The end date can be set way into the future. \$now - Date representing the point in time where the combined signal we are creating will switch from historical to future data. \$nowCapsule - This creates a capsule which is then made into a condition for use in the next step Create Combined Signal. For maximum performance, recommend keeping the capsule length to the minimum necessary duration (e.g., don't add 1 year if only 6 months is the standard analysis window). 2. Create a Combined Master Signal Once again, in formula we will input the code below to create a new signal that is the combination of the Measured Data and a Forcast Signal Formula \$measuredData.splice(\$forecastSignal,\$validPlanningRange) The result is one signal that combines our Measured Data and a Forecast Signal: The Master Signal appears as dashed line whereas the measured data appears as a solid line. The dashed line indicates the signal is uncertain and therefore, expected to change. 3. Make sure the Master Signal is Auto-Updating By default when the page is loaded or the time range adjusted, the Master Signal will be recalculated and any new data from the Measured Signal will replace the Forecast Signal. Additionally, the analysis can be set to Auto Update.
6. ## Prediction using Regression

Hi Everyone, I have a case scenario where we would like to predict the number of days before a parameter reaches a set limit. For example, I wanted to see in my trend a dash line where my Tank Level would reach 80%. Correct me if I am wrong but the Predictive Tool for Seeq uses co-variance signals to generate a forecasted signal. What I wanted to achieve is to forecast the predictive value of a signal in the next succeeding days or hours. Am I able to do so in SEEQ? Regards, Ricky
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