Fuzzy Cognitive Maps (FCMs) are a widely used, neuro-fuzzy based qualitative approach for the modeling of dynamic systems, which allow for both static and dynamic analyses. They are capable of modeling complex systems with nonlinearities and unknown physical behaviour. FCMs describe a given system by means of concepts connected by quantified cause-effect relationships. This dissertation contributes to the subject of computer-driven generation of FCMs that can be used to perform an accurate dynamic analysis of the modeled system. The dynamic analysis provides insights into the degree of presence, and dependencies between the concepts in successive iterations of the simulation of a given FCM model. Such simulation studies could be used to analyze what-if scenarios in the context of decision support and to perform time series predictions. Two research directions within the framework of FCM development, which concern the learning of FCMs from historical data and an aggregation of FCMs that were proposed by multiple experts, are investigated. Several new automated computational methods for data-driven learning and aggregation of FCMs are introduced and empirically evaluated. These methods utilize real-coded genetic algorithms (RCGA)-based optimization. This choice of the optimization vehicle was motivated by their well-documented efficiency in searching large and continuous search spaces, which are inherent to our problem. Experimental evaluation demonstrates that the proposed RCGA-based learning method outperforms modern existing approaches when the dynamic analysis is considered. A novel divide and conquer-based learning strategy to improve scalability of the RCGA approach, is also proposed. This strategy is shown to be competitive or even better than solutions based on the parallelization of the underlying genetic algorithm. The RCGA-based learning method is further extended to provide improved FCMs when the number of connections of the map is known a priori. Experimental evaluation shows that the density-based learning method outperforms the generic RCGA-based approach when using a relatively accurate density estimate, and that both methods are equivalent when the estimate is inaccurate. In addition, a novel method for the aggregation of multiple input FCMs, is proposed. When compared to existing aggregation approaches, this method provides solutions that are more accurate when dynamic analysis is the objective. / Software Engineering and Intelligent Systems

According to recent assessment data, there is an urgent need to improve students' knowledge of science. It has been suggested that the infusion of reading activities including concept mapping, questioning and interactive read-alouds can help students in learning science concepts. Little or no research has combined these methods to examine its effect on learning. The purpose of this study was to examine and compare concept mapping and questioning on students' organization and retention of science knowledge when used with interactive informational read-alouds of science trade books. This study included 58 third grade students from four homogenous classes who were assigned to either a concept mapping group (experimental group) or a questioning with writing group (comparison group). With the same teacher, the school science specialist, the students completed an eight day unit regarding "soil formation" comprised of read-alouds, discussions and reading comprehension activities. (There were no hands-on, laboratory experiments.) Students were assessed on different types of knowledge. Data were analyzed using a mixed model ANOVA design to determine both within-factors (repeated measure), to show growth, and between-factors, to determine the difference between the two groups. The concept mapping group (experimental group) performed significantly higher than the questioning with writing group (comparison) on (a) relational vocabulary assessment (measuring relational knowledge); (b) multiple-choice assessment (measuring students' ability to identify key ideas); and (c) writing assessment (measuring students' relational thinking, students' ability to retain and recall key information and students' ability to use domain knowledge). The concept mapping group maintained these gains in a delayed assessment. The groups did not differ on individual word knowledge as measured by a matching assessment. Recommendations are provided for teachers and researchers including using concept mapping in teaching science concepts to elementary students in conjunction with science text reading, as well as incorporating technology with computer-generated concept maps using Inspiration software.

Typescript. / Thesis (Ph. D.)--University of Hawaii at Manoa, 1986. / Bibliography: leaves 370-375. / Photocopy. / xiv, 375 leaves bound maps 29 cm

Thesis (Ph.D.)--Tufts University, 1999. / Adviser: Holly A. Taylor. Submitted to the Dept. of Psychology. Includes bibliographical references (leaves 59-61). Access restricted to members of the Tufts University community. Also available via the World Wide Web;

Thesis (Ph.D.) -- University of Adelaide, Dept. of English, 2000. / Bibliography: leaves 242-255.

Thesis (Ph.D.) -- University of Rhode Island, 2007 / Typescript. Includes bibliographical references (leaves 73-82).

Thesis (Ph. D.)--Computing, Georgia Institute of Technology, 2008. / Committee Chair: Dellaert, Frank; Committee Member: Balch, Tucker; Committee Member: Christensen, Henrik; Committee Member: Kuipers, Benjamin; Committee Member: Rehg, Jim.

Thesis (M. Sc.)--Carleton University, 2003. / Includes bibliographical references (p. 91-96). Also available in electronic format on the Internet.

Thesis (M.F.A.)--Rochester Institute of Technology, 1982. / Typescript. Includes bibliographical references (leaf 28).

Thesis (M.S.)--Wisconsin. / Includes bibliographical references (leaves 123-128).