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University of Missouri--Rolla
The development of hybrid intelligent systems for technical analysis based equivolume charting
Abstract
dc:description.abstract"This dissertation proposes the development of a hybrid intelligent system applied to technical analysis based equivolume charting for stock trading. A Neuro-Fuzzy based Genetic Algorithms (NF-GA) system of the Volume Adjusted Moving Average (VAMA) membership functions is introduced to evaluate the effectiveness of using a hybrid intelligent system that integrates neural networks, fuzzy logic, and genetic algorithms techniques for increasing the efficiency of technical analysis based equivolume charting for trading stocks"--Introduction, page 1.
Degree
thesis:*- Name thesis:degree_name
- Ph. D. in Engineering Management
- Grantor
- University of Missouri--Rolla
- Year dc:date.available
- 2016
Author and committee
dc:creator, dc:contributor.*- Author dc:creator
-
- Chavarnakul, Thira
Subjects
dc:subject × 1Identifiers
dc:identifier.*- Repository record dc:identifier
- https://scholarsmine.mst.edu/doctoral_dissertations/1882
- OAI identifier oai:identifier
- oai:scholarsmine.mst.edu:doctoral_dissertations-2884