A hybrid intelligent system for data analysis and visualization

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dc.contributor.authorWang, Shir Li
dc.date.accessioned2014-11-11T01:17:45Z
dc.date.available2014-11-11T01:17:45Z
dc.date.issued2007
dc.descriptionMasteren_US
dc.description.abstractIn this research, a hybrid system consisting of the multilayer perceptron (MLP) neural network and the circle-segments method for data analysis and visualization is designed and developed. Acting as a black box, the MLP network normally gives a prediction without providing a facility for users to visualize the solution. As such, this research proposes to hybrid the circle-segments method with the MLP network, whereby the circle-segments method is used in two different ways, i.e., to provide visual correlation between the input-output data samples to users and, thus, to allow users to eliminate insignificant inputs from the input data set. The effectiveness of the proposed MLP-circle segments system is evaluated using a number of benchmark and real case studies. For process modelling and prediction problems, the case studies investigated include the Friedman#1 benchmark problem, wire electrical discharge machining (EDM) process, disk drive read control system, and PID controller tuning. For data classification problems, the case studies investigated include the Iris, and Wine benchmark problems, as well as a real medical problem pertaining to acute stroke diagnosis. In process modelling and prediction problems, the performances of the hybrid system are compared with those from the response surface methodology (RSM). The proposed system achieves an improvement of at least 11% in term of accuracy as compared with the results from the RSM. In data classification problems, the results are compared with those from MLP coupled with the principal component analysis (PCA) as well as MLP without any feature selection method. It is found that the accuracy of proposed system is as good as, if not better than, MLP coupled with the PCA and MLP without any feature selection method. Based on the results obtained, the proposed MLP-circle segments system demonstrates better prediction and visualization abilities, thus justifying its potentials as a useful and effective system for data analysis and visualization. The proposed MLP-circle segments system is useful in data analysis and visualization, especially in the domain of process modelling and prediction, as well as data classification problems.en_US
dc.identifier.urihttp://hdl.handle.net/123456789/375
dc.language.isoenen_US
dc.subjectComputer Scienceen_US
dc.subjectHybrid intelligent systemen_US
dc.subjectData analysisen_US
dc.titleA hybrid intelligent system for data analysis and visualizationen_US
dc.typeThesisen_US
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