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Articles 61 - 63 of 63
Full-Text Articles in Other Operations Research, Systems Engineering and Industrial Engineering
Development Of Dynamic Mass-Energy-Thermodynamics Constrained Hybrid Neural Network Models For Process Systems Applications, Angan Mukherjee
Development Of Dynamic Mass-Energy-Thermodynamics Constrained Hybrid Neural Network Models For Process Systems Applications, Angan Mukherjee
Graduate Theses, Dissertations, and Problem Reports (ETD)
First-principles models can provide very good predictions even for cases when there are no data at all, or data are limited in certain range of operating conditions, or for cases where data collection is infeasible. However, the development of accurate first-principles models for complex nonlinear dynamic systems can be time consuming, computationally expensive, and may be infeasible for certain systems due to lack of sufficient knowledge (information). It is also challenging to adapt first-principles models for time-varying systems. Furthermore, it can be difficult, if not impossible, to develop accurate models for some complex phenomena that are poorly understood. On the …
Automation Of Productive Machinery. Bases For An Innovative Business Model, Carlos Guillermo Hernández-Cenzano, Angel Contreras-Cruz, Eduardo Humada-Tello
Automation Of Productive Machinery. Bases For An Innovative Business Model, Carlos Guillermo Hernández-Cenzano, Angel Contreras-Cruz, Eduardo Humada-Tello
Engineering and Technology Management Faculty Publications and Presentations
Nowadays, some laboratories perform elastic properties tests for concrete or rock cores using equipment manufactured 50 years ago. The original data collection procedure uses analog and manual recordings, which can cause inaccuracies in the measurements taken during these trials The process is tedious and updated since each trial's measurement data is recorded manually. In this context, this study systematizes the process and proposes an automated data acquisition and recording system for this type of equipment, followed by a case study presenting a rock compression test.
‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody
‘I Know It When I See It’– Developing Quality Schedules Considering Subjective Or Unspecified Criteria, Douglas L. Moody
Publications and Research
Most timetabling problems have a given objective function to measure the quality of a solution. However, users may have a “I know it when I see it” recognition of a quality schedule, without specifying the complete basis for their judgment. In this situation, the objective function cannot be exclusively used as a solution quality measurement. This work presents an AI based approach to aid in categorizing the solution’s quality when the users have not explicitly defined all factors used in their criteria.