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Full-Text Articles in Engineering
Falconet: Force-Feedback Approach For Learning From Coaching And Observation Using Natural And Experiential Training, Gary Stein
Electronic Theses and Dissertations
Building an intelligent agent model from scratch is a difficult task. Thus, it would be preferable to have an automated process perform this task. There have been many manual and automatic techniques, however, each of these has various issues with obtaining, organizing, or making use of the data. Additionally, it can be difficult to get perfect data or, once the data is obtained, impractical to get a human subject to explain why some action was performed. Because of these problems, machine learning from observation emerged to produce agent models based on observational data. Learning from observation uses unobtrusive and purely …
Meshless Hemodynamics Modeling And Evolutionary Shape Optimization Of Bypass Grafts Anastomoses, Zaher El Zahab
Meshless Hemodynamics Modeling And Evolutionary Shape Optimization Of Bypass Grafts Anastomoses, Zaher El Zahab
Electronic Theses and Dissertations
Objectives: The main objective of the current dissertation is to establish a formal shape optimization procedure for a given bypass grafts end-to-side distal anastomosis (ETSDA). The motivation behind this dissertation is that most of the previous ETSDA shape optimization research activities cited in the literature relied on direct optimization approaches that do not guaranty accurate optimization results. Three different ETSDA models are considered herein: The conventional, the Miller cuff, and the hood models. Materials and Methods: The ETSDA shape optimization is driven by three computational objects: a localized collocation meshless method (LCMM) solver, an automated geometry pre-processor, and a genetic-algorithm-based …
An Adaptive Multiobjective Evolutionary Approach To Optimize Artmap Neural Networks, Assem Kaylani
An Adaptive Multiobjective Evolutionary Approach To Optimize Artmap Neural Networks, Assem Kaylani
Electronic Theses and Dissertations
This dissertation deals with the evolutionary optimization of ART neural network architectures. ART (adaptive resonance theory) was introduced by a Grossberg in 1976. In the last 20 years (1987-2007) a number of ART neural network architectures were introduced into the literature (Fuzzy ARTMAP (1992), Gaussian ARTMAP (1996 and 1997) and Ellipsoidal ARTMAP (2001)). In this dissertation, we focus on the evolutionary optimization of ART neural network architectures with the intent of optimizing the size and the generalization performance of the ART neural network. A number of researchers have focused on the evolutionary optimization of neural networks, but no research has …
Genetically Engineered Adaptive Resonance Theory (Art) Neural Network Architectures, Ahmad Al-Daraiseh
Genetically Engineered Adaptive Resonance Theory (Art) Neural Network Architectures, Ahmad Al-Daraiseh
Electronic Theses and Dissertations
Fuzzy ARTMAP (FAM) is currently considered to be one of the premier neural network architectures in solving classification problems. One of the limitations of Fuzzy ARTMAP that has been extensively reported in the literature is the category proliferation problem. That is Fuzzy ARTMAP has the tendency of increasing its network size, as it is confronted with more and more data, especially if the data is of noisy and/or overlapping nature. To remedy this problem a number of researchers have designed modifications to the training phase of Fuzzy ARTMAP that had the beneficial effect of reducing this phenomenon. In this thesis …
Planning And Scheduling For Large-Scaledistributed Systems, Han Yu
Planning And Scheduling For Large-Scaledistributed Systems, Han Yu
Electronic Theses and Dissertations
Many applications require computing resources well beyond those available on any single system. Simulations of atomic and subatomic systems with application to material science, computations related to study of natural sciences, and computer-aided design are examples of applications that can benefit from the resource-rich environment provided by a large collection of autonomous systems interconnected by high-speed networks. To transform such a collection of systems into a user's virtual machine, we have to develop new algorithms for coordination, planning, scheduling, resource discovery, and other functions that can be automated. Then we can develop societal services based upon these algorithms, which hide …