Walter D. Potter

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-In this paper we present a genetic algorithm-based optimization technique for edge detection. The problem of edge detection is formulated as one of choosing a minimum cost edge configuration. The edge configurations are viewed as two-dimensional chromosomes with fitness values inversely proportional to their costs. The design of the crossover and the(More)
Genetic Algorithms are heuristic search schemes based on a model of Darwinian evolution. Although not guaranteed to find the optimal solution, genetic algorithms have been shown to be effective at finding near optimal and, in some cases, optimal solutions to combinatorially explosive problems. Finding a maximal length snake, a list of vertices satisfying(More)
The snake-in-the-box problem is a difficult problem in mathematics and computer science that was first described by Kautz in the late 1950’s (Kautz 1958). Snake-in-the-box codes have many applications in electrical engineering, coding theory, and computer network topologies. Generally, the longer the snake for a given dimension, the more useful it is in(More)
Genetic algorithms have demonstrated considerable success in providing good solutions to many NP-Hard optimization problems. For such problems, exact algorithms that always find the optimal solution are only useful for small toy problems, so heuristic algorithms such as the genetic algorithm must be used in practice. In this paper, we apply the genetic(More)
We present a method for searching for achordal open paths (snakes) in n-dimensional hypercube graphs (the box). Our technique first obtains a set of exemplary snakes using an evolutionary algorithm. These snakes are then analyzed to define a pruning model that constrains the search space. A depth-first search of the constrained solution space has(More)
This paper describes a method for mapping a sequence of notes to a set of guitar fretboard positions (tablature). The method uses a Genetic Algorithm (GA) to find playable tablature through the use of a fitness function that assesses the playability of a given set of fretboard positions. Tests of the algorithm on a variety of compositions demonstrate an(More)
Aflatoxin contamination in peanut crops is a problem of significant health and financial importance. Predicting aflatoxin levels prior to crop harvest is useful for minimizing the impact of a contaminated crop and is the goal of our research. Backpropagation neural networks have been used to model problems of this type, however development of networks poses(More)
An overview is given of past present data-modeling trends, and future directions are identified. The three traditional and commonly used data models that gained wide acceptance in the late 1960s and early 1970s and are used extensively today, namely the relational, hierarchical, and network models, are reviewed. Semantic data models that attempt to enhance(More)