Human flight performance data were investigated using non-linear time series analysis methods to determine deterministic chaotic behavior in the data. Using a sequence of steps of non-linear methods, four flight performance data were used to investigate for the existence of deterministic chaotic behavior. Results revealed that flight performance data may exhibit chaotic behavior. Results also showed a consistent low determinism value in all the data examined which is the defining characteristic of chaotic behavior. It was also found that the data originated from non-stationary process. The Maximal Lyapunov Exponent (MLE) value which indicate chaotic behavior exist in the data revealed that most of the data examined possessed some traces of deterministic chaotic behavior evident by the low Maximal Lyapunov Exponent value.
","abstract_html":"<p>Human flight performance data were investigated using non-linear time series analysis methods to determine deterministic chaotic behavior in the data. Using a sequence of steps of non-linear methods, four flight performance data were used to investigate for the existence of deterministic chaotic behavior. Results revealed that flight performance data may exhibit chaotic behavior. Results also showed a consistent low determinism value in all the data examined which is the defining characteristic of chaotic behavior. It was also found that the data originated from non-stationary process. The Maximal Lyapunov Exponent (MLE) value which indicate chaotic behavior exist in the data revealed that most of the data examined possessed some traces of deterministic chaotic behavior evident by the low Maximal Lyapunov Exponent value.</p>","abstract_has_math":false,"creators":["Amanfu, Lionel Blankson"],"institution":null,"degree_name":"Master of Science in Human Factors & Systems","degree_level":"Thesis - Open Access","degree_discipline":"Human Factors and Systems","degree_department":null,"school":null,"contributors":["Dahai Liu","Albert J. Boquet","Seenith Sivasundaram"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2008,"date_issued":"2008-07-01T07:00:00Z","date_published":"2008-07-01T07:00:00Z","updated_at":"2026-07-27T19:25:37Z","subjects":["determinism","chaotic behavior","flight performance","chaos theory","nonlinear","Applied Behavior Analysis"],"languages":[],"rights":[],"rights_urls":[],"identifier_entries":[]},"links":{"outbound_url":"https://commons.erau.edu/db-theses/5","outbound_label":"Repository record","outbound_source":"dc:identifier"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor","label":"Contributor","values":["Dahai Liu","Albert J. Boquet","Seenith Sivasundaram"]},{"key":"dc:creator","label":"Author","values":["Amanfu, Lionel Blankson"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"thesis:degree_discipline","label":"Discipline","values":["Human Factors and Systems"]},{"key":"thesis:degree_level","label":"Degree Level","values":["Thesis - Open Access"]},{"key":"thesis:degree_name","label":"Degree Name","values":["Master of Science in Human Factors & Systems"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["determinism","chaotic behavior","flight performance","chaos theory","nonlinear","Applied Behavior Analysis"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier","label":"Identifier","values":["https://commons.erau.edu/db-theses/5"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description.abstract","label":"Abstract","values":["Human flight performance data were investigated using non-linear time series analysis methods to determine deterministic chaotic behavior in the data. Using a sequence of steps of non-linear methods, four flight performance data were used to investigate for the existence of deterministic chaotic behavior. Results revealed that flight performance data may exhibit chaotic behavior. Results also showed a consistent low determinism value in all the data examined which is the defining characteristic of chaotic behavior. It was also found that the data originated from non-stationary process. The Maximal Lyapunov Exponent (MLE) value which indicate chaotic behavior exist in the data revealed that most of the data examined possessed some traces of deterministic chaotic behavior evident by the low Maximal Lyapunov Exponent value.
"]},{"key":"dc:title","label":"Title","values":["An Investigation of Determinism and Chaotic Behavior in Flight Performance Data: A Chaos Theory and Nonlinear Time Series Analysis Approach"]}]}],"canonical_facts":{"dc:contributor":["Dahai Liu","Albert J. Boquet","Seenith Sivasundaram"],"dc:creator":["Amanfu, Lionel Blankson"],"dc:description.abstract":["Human flight performance data were investigated using non-linear time series analysis methods to determine deterministic chaotic behavior in the data. Using a sequence of steps of non-linear methods, four flight performance data were used to investigate for the existence of deterministic chaotic behavior. Results revealed that flight performance data may exhibit chaotic behavior. Results also showed a consistent low determinism value in all the data examined which is the defining characteristic of chaotic behavior. It was also found that the data originated from non-stationary process. The Maximal Lyapunov Exponent (MLE) value which indicate chaotic behavior exist in the data revealed that most of the data examined possessed some traces of deterministic chaotic behavior evident by the low Maximal Lyapunov Exponent value.
"],"dc:identifier":["https://commons.erau.edu/db-theses/5"],"dc:subject":["determinism","chaotic behavior","flight performance","chaos theory","nonlinear","Applied Behavior Analysis"],"dc:title":["An Investigation of Determinism and Chaotic Behavior in Flight Performance Data: A Chaos Theory and Nonlinear Time Series Analysis Approach"],"thesis:degree_discipline":["Human Factors and Systems"],"thesis:degree_level":["Thesis - Open Access"],"thesis:degree_name":["Master of Science in Human Factors & Systems"]},"updated_at":"2026-07-27T19:25:37Z"}