Model Training. ITRE shall provide training for users of the model, including organizations, agencies, consultants and researchers designated by the Sponsor and stakeholders. Training will consist of technical workshops on how to use the model, how it is calibrated, and how to interpret the output. Training will also include presentations oriented toward MPO member agencies and technical staff members that detail how the model can be used as a decision tool, what assumptions have been incorporated in the model, and how to use the model output to assess project and policy alternatives.
Model Training. Klarity and Third Party AI Providers will not process any Customer Data for any purpose other than those expressly contemplated within this Agreement. For the avoidance of doubt, Klarity and Third Party AI Providers will not collect, use or retain any Customer Data to train or retrain any generative AI, whether directly or indirectly.
Model Training. This task will include delivery of the model files to the City and providing basic training on use of the model to access and review model results and make very simple model runs. The training will not include instruction on model calibration, changing flow factors or I/I rates, or major model updates.
Subtask 2.1 – Prepare Model Files and Training Plans
Model Training. Figure 8.1 shows how model training was performed. Based on the original eSTS data, 100 bootstrapped training datasets were drawn with 3826 patients each (sampling with replacement, ≈ 63.2% of the original data). These datasets were randomly split into two complementary parts to tune the hyperparameters of the ML models using grid search ( 3 to train the models and 1 to test their performance, same parts for all methods). Performance of
Model Training. KEA provides models, stemmers and stopword lists for EN, ES and FR. For DE it provides a stemmer and a stopword list but no model. Therefore, the first measure has been to close the language gap and to train a model for German using annotated DW data generated by the GFAI keyword extraction tool. For unsupervised extraction of keyphrases with the GFAI tool see section 6.2.5. We are currently exploring the following issues:
1. Impact of large numbers of extracted keyphrases
2. Impact of training corpus size on F-score and score diversity and keyphrase length
3. Comparison of models trained with author-annotated keyphrases and automatically annotated keyphrases (GFAI tool)
4. Impact of applying KEA to smaller text units such as paragraphs and sentences
5. Impact of different training corpora (in-domain versus out of domain)
Model Training. Model Training. At the completion of the Master Plan, Consultant will conduct up to three (3) inhouse training sessions with City staff to review and discuss protocols for the future update and use of the hydraulic model. Focus of training will be to evaluate development projects and perform operational analysis for optimizing system operation. Model training materials Summary of guidelines, recommendations, and findings from the condition assessment task. Develop risk management guidelines and recommendations specific to the water utility assets using the LoF, CoF, and BRE scores. Develop prioritized replacement/rehabilitation projects based on high risk assets and the projects previously included in other studies that have not been completed. Develop cost estimates for projects and/or tools and technology to complete the recommendations. Provide additional recommendations and/or items for future consideration. Water Utility Asset Renewal and Replacement Study Report (Draft Report for City review and comment; Final Report) Findings from the Renewal and Replacement Study will be incorporated into the recommended capital improvement program (see Task 8 below) Based on the findings from the Water Utility Asset Renewal and Replacement Study (see Task 7), Consultant will incorporate recommendations considering the results from the hydraulic analysis and the material, age, service and leak history. The criteria shall address the estimation for remaining life expectancy of an existing asset, assess any economic, service performance, system reliability, or environmental risk that might justify replacing the asset and develop logical and practical weighting or ranking criteria that could be employed to determine a 20-year CIP program. The projects shall be prioritized and ranked based on the critical needs of replacement, emergency preparedness, and in order of importance. The CIP shall group the projects by anticipated year for construction and summarize the estimated annual costs. Consultant will provide mapping and tables that illustrate the recommended CIP projects.
Model Training. Provide training on the model and GIS integration, customer projections by growth areas, demand allocation by physical address or parcel, demand projections by growth areas, and improvement prioritization. OWNER will attend software training provided by Xxxxxxx. (42 hours)
