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Full-Text Articles in Physical Sciences and Mathematics
Sensitivity Analysis Of Basins Of Attraction For Gradient-Based Optimization Methods, Gillian King
Sensitivity Analysis Of Basins Of Attraction For Gradient-Based Optimization Methods, Gillian King
Honors Projects
This project is an analysis of the effectiveness of five distinct optimization methods in their ability in producing clear images of the basins of attraction, which is the set of initial points that approach the same minimum for a given function. Basin images are similar to contour plots, except that they depict the distinct regions of points--in unique colors--that approach the same minimum. Though distinct in goal, contour plots are useful to basin research in that idealized basin images can be inferred from the steepness levels and location of extrema they depict. Effectiveness of the method changes slightly depending on …
Sensitivity Analysis Of Basins Of Attraction For Nelder-Mead, Sonia K. Shah
Sensitivity Analysis Of Basins Of Attraction For Nelder-Mead, Sonia K. Shah
Honors Projects
The Nelder-Mead optimization method is a numerical method used to find the minimum of an objective function in a multidimensional space. In this paper, we use this method to study functions - specifically functions with three-dimensional graphs - and create images of the basin of attraction of the function. Three different methods are used to create these images named the systematic point method, randomized centroid method, and systemized centroid method. This paper applies these methods to different functions. The first function has two minima with an equivalent function value. The second function has one global minimum and one local minimum. …
Improving Energy Efficiency Through Compiler Optimizations, Jack Beckitt-Marshall
Improving Energy Efficiency Through Compiler Optimizations, Jack Beckitt-Marshall
Honors Projects
Abstract--- Energy efficiency is becoming increasingly important for computation, especially in the context of the current climate crisis. The aim of this experiment was to see if the compiler could reduce energy usage without rewriting programs themselves. The experimental setup consisted of compiling programs using the Clang compiler using a set of compiler flags, and then measuring energy usage and execution time on an AMD Ryzen processor. Three experiments were performed: a random exploration of compiler flags, utilization of SIMD, as well as benchmarking real world applications. It was found that the compiler was able to reduce execution time, especially …
Gem-Pso: Particle Swarm Optimization Guided By Enhanced Memory, Kevin Fakai Chen
Gem-Pso: Particle Swarm Optimization Guided By Enhanced Memory, Kevin Fakai Chen
Honors Projects
Particle Swarm Optimization (PSO) is a widely-used nature-inspired optimization technique in which a swarm of virtual particles work together with limited communication to find a global minimum or optimum. PSO has has been successfully applied to a wide variety of practical problems, such as optimization in engineering fields, hybridization with other nature-inspired algorithms, or even general optimization problems. However, PSO suffers from a phenomenon known as premature convergence, in which the algorithm's particles all converge on a local optimum instead of the global optimum, and cannot improve their solution any further. We seek to improve upon the standard Particle Swarm …