Jump to content
  • To Search the Seeq Knowledgebase:


Search the Community

Showing results for tags 'prediction'.

  • Search By Tags

    Type tags separated by commas.
  • Search By Author

Content Type


  • Community Technical Forums
    • General Seeq Discussions
    • Seeq Admin Forum
    • Training Resources
    • Product Suggestions
    • Seeq Data Lab
  • Community News
    • Seeq Blog Posts
    • News Articles
    • Press Releases
    • Upcoming Events
    • Resources


  • Seeq FAQs
  • Online Manual
    • General Information

Find results in...

Find results that contain...

Date Created

  • Start


Last Updated

  • Start


Filter by number of...


  • Start



About Me



Level of Seeq User

Found 11 results

  1. Using some of the new Asset Group features in R52 we can easily create unique prediction training ranges for each asset. In this example we are going to create three separate training ranges for three assets. Step 1 - Find the assets you want to model with your prediction and add them to a new asset group Step 2 - Create a Manual Condition for each asset with your desired training range for each particular asset. These training ranges can be as simple as single capsules or as complex as a Manual Condition combined with a mode of operation condition. Step 3 - Add t
  2. When you are evaluating the efficacy of a regression, there a few commons methods. You might simply take the difference between your predicted value and your actual value, then create capsules when this value deviates from some critical magnitude. I'll outline an alternative approach, by calculating the r-squared (r2) value over each capsule (in my case, days), but this can be applied to any condition like batches or a Manual Condition of training and validation. The general outline is: 1. Build a prediction in Seeq using the Prediction tool. You can specify your training window by a cond
  3. Use Case: It is common in industry to seek to use the behavior of upstream process variables to predict what the behavior of a downstream variable might be minutes, hours or days from the present time. Solution: A traditional predictive modeling workflow can be applied to solve this problem. Identify an appropriate training data set Perform any necessary data cleansing Create a predictive model Evaluate the model fit Improve the model Operationalize the model What differentiates this use case from any other predictive modeling
  4. When addressing a business problem with analytics, we should always start by asking ourselves 4 key questions: Why are we talking about this: what is the business problem we are trying to address, and what value will solving this problem generate? What data do I have available to help with solving this problem? How can I build an effective analysis to identify the root of my problem (both in the past, and in future)? How will I visualize the outputs to ensure proactive action to prevent the problem from manifesting? This is where you extract the value. With that
  5. We were very excited to announce that in R21.0.44+ we can now add best fit curves and their corresponding r2 value to the Scatter Plot display. Something that could further enhance this display would be adding in the ability to display the trend line equation on the chart beside the r2.
  6. Scenario: I have created a regression or prediction model for my process but i want to apply that same regression model to another set of signals or a different period of time. This could be helpful for comparing how one piece of equipment is operating when compared against a regression built for another system. It could be used to predict how a system will behave based on how some other similar system behaved. It could be used predict how a system will behave before you have enough information to build that system or run its own model, or any number of applications where we might want to
  7. The following steps will create a prediction model for every capsule in a condition. Step 1. pick a condition with capsules that isolate the desired area of regression. Any condition with non-overlapping capsules will work as long as there are enough sample points within its duration. For this example, an increasing temperature condition will be used. However, periodic conditions and value search conditions will work as well. Step 2. Create a time counter for each capsule in the condition. This can be done with the new timesince() function in the formula tool. The timesince() fun
  8. Hi All, I'm working on some data , wherein i have 6 Independent variable and 1 dependent variable. while running the Regression model on this data, i get very less Accuracy of model as mentioned in below screenshot. Note :- As far as data Pre-processing is concern , i have scale the features and also imputes the missing values on the basis of mean imputation. Do let me know if there's any pre-processing feature is there in seek to deal with data. Regards, JItesh Vachheta
  9. Seeq Version: R21.0.42+ Scenario: A user has a regularly updating signal and wants to predict a future value based on some amount of previous data. For this example the User wants to predict the Area A Temperature 3 days in the future based on the previous week (7 days) of data. Steps: 1. Bring in the regularly updating Temperature signal. 2. The Formula Tool can be used to create a condition that contains a single capsule referenced from the current time. This capsule will be based on the current time and extend 7 days in the past and 3 days into t
  10. 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 forec
  11. 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
  • Create New...