User:Jaired

I am Jaired Collins, a student at Missouri Southern State University in Joplin, MO, currently majoring in computational mathematics. Outside of academia, I enjoy cycling, weights, table tennis, tennis, and cooking.

Week 1 (29 May - 1 Jun)

Tuesday

• Initial meeting to get introduced into the program.
• Lunch meeting with mentors.
• Obtained MU and MSCS account logins and ID card
• Paperwork

Wednesday

• Met with Dr. Corliss to get acquainted with the GasDay lab and receive a key.
• Met with Dr. Povinelli and another student to set up initial parameters of the project.
• Literature review.

Thursday

• More literature review
• Seminar with GasDay
• Meeting with Dr. Povinelli and student to establish a weekly plan and talk about the project.

Friday

• Literature review
• Planned for a presentation at a GasDay Seminar on the 21st of June
• Data cleaning

Week 2 (4 Jun - 8 Jun)

Monday

• Meeting with Dr. Corliss
• Meeting with Dr. Povinelli and Colin
• Literature search
• Cleaned up more data

Tuesday

• Meeting with Dr. Corliss
• Data cleaning with bash and Matlab
• Played around with data and SVMs in MatLab
• Meeting with research consultant
• Literature review

Wednesday

• Cross validation with k-Fold
• GasDay Camp
• Literature search

Thursday

• More built-in SVM work in MatLab
• GasDay camp
• REU working lunch meeting, bad presentation

Friday

• Meeting with Dr. Corliss
• Creation of ShareLaTeX project
• Converted temporal pressure data into nonuniform time series data
• Tried resampling time series data into uniform data

Week 3 (11 Jun - 15 Jun)

Monday

• Meeting with Dr. Corliss
• Meeting with Dr. Povinelli
• Resampled nonuniform data
• Forecasting with ARIMA
• Left computer running to finish ARIMA models

Tuesday

• Examined and saved ARIMA models
• Dissimilarity-based approach to prediction, where correlation coefficients between sensors are used as features
• SVM and k-fold cross validation at k = 5, 10, and 20

Wednesday

• Meeting with Dr. Corliss to elucidate LS-SVM for regression
• Coding LS-SVM
• RCR lunch meeting

Thursday

• Meeting with Dr. Corliss, further explained LS-SVM
• GasDay seminar
• Coding of LS-SVM for regression
• Meeting with Dr. Povinelli
• Called contact to clarify threshold values

Friday

• Out for wedding

Week 4 (18 Jun - 22 Jun)

Monday

• Out for wedding

Tuesday

• Wrote working abstract
• Wrote summaries for related works section
• Read Anomaly Detection in Streaming Non-stationary Temporal Data
• Read Chapter 5 of Operations & Maintenance Best Practices Release 3.0
• Tested different features in LS-SVM; residuals are very low

Wednesday

• Meeting with Dr. Corliss, showed LS-SVM results
• Work on conference paper with graduate student
• LS-SVM Tuning
• Work on PPT for presentation

Thursday

• Practice presentation at GasDay Seminar
• Working REU lunch
• Knowledge and Information Discovery with Dr. Povinelli
• Project meeting with Dr. Povinelli and graduate student

Friday

• Recursive nonlinear autoregressive model with LS-SVM
• Clarification on building different models with different time horizons instead of recursive approach
• Coding nonlinear autoregressive model with LS-SVM with multiple time horizons
• Work on abstract
• Work on background

Week 5 (25 Jun - 29 Jun)

Monday

• Worked on slides for presentation on Thursday
• Tried to debug direct multiple time horizon least squares support vector machine nonlinear autoregressive model (LS-SVM NAR)
• Showed abstract to Dr. Povinelli, got feedback
• Resampled data to 1 minute and wrote several MATLAB scripts to automate the LS-SVM NAR process
• Came to the conclusion that LS-SVM NAR is not predicting well at all. Plotted values were erroneous and coincidentally showed promising results

Tuesday

• Meeting with Dr. Corliss
• Read more into SVMs and SVRs to help the LS-SVM NAR algorithm
• Implementation of radial basis function kernel for LS-SVM NAR

Wednesday

• Debugging LS-LSVM NAR with RBF kernel with test cases
• Tuning LS-LSVM NAR hyperparameters
• Presentation preparation

Thursday

• More preparation for REU Midterm
• GasDay Seminar
• Midterm presentations
• KID Seminar
• Meeting with Dr. Povinelli to discuss project

Friday

• Put a lot of effort into making LS-SVM work
• Meeting with Dr. Povinelli to help with LS-SVM and things to do while he is on vacation

Week 6 (2 Jul - 6 Jul)

Monday

• Confirmed some math with Dr. Corliss
• Messing around with LS-SVM to get it to work
• Created normalized time series
• Extracted correlated information from multiple sensors

Tuesday

• Implemented long short-term memory recurrent neural network, peaks too often
• Tried several configurations of LS-SVM NAR
• Created "artificial" data with extra troughs in it to improve accuracy of troughed data with LS-SVM
• Literature search on time series/forecast*/machine learning

Wednesday

• Created "artificial" data with extra peaks in it to improve accuracy of peaked data with LS-SVM
• Manual ensemble of peaked, trough, and normal LS-SVM models for forecasting
• Created several figures to show LS-SVM for regression

Thursday

• Remote desktop into a better computer to use more training data
• Started working on a programmatic rule-based ensemble of differently trained models
• REU working lunch with Dr. Corliss

Week 7 (9 Jul - 13 Jul)

Monday

• Meeting with Dr. Povinelli to discuss project and his and graduate student's visit to the customer company
• Created different figure of LS-SVM to only include the 30 minute forecast value every minute
• Analyzed all sensor information from all the sites to find anomalies

Week 8 (16 Jul - 20 Jul)

More experiments with algorithm

Week 9 (23 Jul - 27 Jul)

Work on final draft of research paper
Work on poster

Week 10 (30 Jul - 3 Aug)

Prepare final presentation