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Operations Research, Systems Engineering and Industrial Engineering Commons™
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- Backpropagation (2)
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Articles 1 - 4 of 4
Full-Text Articles in Operations Research, Systems Engineering and Industrial Engineering
Work Measurement Decision Diagram Development And Application At Nasa's Kennedy Space Center, Susan L. Murray, Amanda M. Mitskevich, Joseph J. Pignatiello Jr., Timothy S. Barth, William W. Swart
Work Measurement Decision Diagram Development And Application At Nasa's Kennedy Space Center, Susan L. Murray, Amanda M. Mitskevich, Joseph J. Pignatiello Jr., Timothy S. Barth, William W. Swart
Engineering Management and Systems Engineering Faculty Research & Creative Works
This paper presents a decision flow diagram developed at NASA's Kennedy Space Center for the selection of the appropriate work measurement methodologies for Space Shuttle processing.
A Hierarchial Neural Network Implementation For Forecasting, B. Fulkerson, M. A. Ozbayoglu, Cihan H. Dagli
A Hierarchial Neural Network Implementation For Forecasting, B. Fulkerson, M. A. Ozbayoglu, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
In this paper, a hierarchical neural network architecture for forecasting time series is presented. The architecture is composed of two hierarchical levels using a maximum likelihood competitive learning algorithm. The first level of the system has three experts each using backpropagation and a gating network to partition the input space in order to map the input vectors to the output vectors. The second level of the hierarchical network has an expert using fuzzy ART for producing the correct trend coming from the first level. The experiments show that the resulting network is capable of forecasting the changes in the input …
A Comparison Of Fam And Cmac For Nonlinear Control, Arit Thammano, Cihan H. Dagli
A Comparison Of Fam And Cmac For Nonlinear Control, Arit Thammano, Cihan H. Dagli
Engineering Management and Systems Engineering Faculty Research & Creative Works
This article compares a neural network-based controller, both local and global networks, with fuzzy associative memories (FAM) on a nonlinear problem. CMAC and FAM are chosen as representatives of local generalization networks. CMAC controller is trained off-line, therefore, it can response to the incoming input immediately. CMAC can interpolate its memory and give a reasonable control signal even the input has not been trained on. Backpropagation is picked as a representative of global generalization networks. All three systems are studied on a simple simulated control problem. This preliminary research will be adapted later to control the laser cutting machine. A …
The Integration Of Simulation And Reality For Education Enhancement And Training, Clarence Rasquinha, Stephen A. Raper
The Integration Of Simulation And Reality For Education Enhancement And Training, Clarence Rasquinha, Stephen A. Raper
Engineering Management and Systems Engineering Faculty Research & Creative Works
Quite often, when engineers are exposed to a manufacturing environment on the job for the first time, they undergo a baptism by fire. The environment forces them to deal with situations that integrate many different bodies of knowledge. Reliance on concepts acquired in the academic environment is crucial to their success. Unfortunately, lacking in most academic environments, is any experience through which some or all of these concepts are integrated. In a continuing effort to enhance educational practices in Manufucturing/Systems Engineering programs and perhaps improve the preparedness of a young engineer, the CITE (Computer Integrated Technological Enterprise) tool offers educators …