Intelligent geospatial decision support system for Malaysian marine geospatial data infrastructure
dc.contributor.author | Hamid-Mosaku, Isa Adekunle | |
dc.date.accessioned | 2023-04-19T03:07:59Z | |
dc.date.available | 2023-04-19T03:07:59Z | |
dc.date.issued | 2014-08 | |
dc.description | Thesis (Ph.D (Hidrografi)) | |
dc.description.abstract | Marine resources for different uses and activities are characterised by multi-dimensional concepts, criteria, multi-participants, and multiple-use conflicts. In addition, the fuzzy nature in the marine environment has attendant features that increase the complexity of the environment, thus, necessitating the quest for multiple alternative solutions and adequate evaluation, particularly within the context of Marine Geospatial Data Infrastructure (MGDI). However, in the literature of MGDI, there has yet to be a concerted research effort and framework towards holistic consideration of decision making prospects using multi-criteria evaluation (MCE) and intelligent algorithms for effective and informed decision beyond the classical methods. This research, therefore, aims to develop and validate an intelligent decision support system for Malaysian MGDI. An integrated framework built on mixed method research design serves as the mode of inquiry. Initially, the quantitative methodology, comprising of Dynamic Analytic Network Process (DANP) model, comprehensive evaluation index system (CEIS), MCE extensions, geographic information system’s spatial interaction modelling (SIM), and hydrographic data acquisition sub-system was implemented. Within this framework, a case study validation was employed for the qualitative aspect to predict the most viable geospatial extents within Malaysian waters for exploitation of deep sea marine fishery. Quantitative findings showed that the model has an elucidated CEIS with a DANP network model of 7 criteria, 28 sub-criteria, and 145 performance indicators, with 5 alternatives. In the MCE, computed priority values for Analytic Hierarchy Process (AHP) and Fuzzy AHP are different though their rankings are the same. In addition, the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Fuzzy TOPSIS results from the MCE extensions showed that they were similarly ranked for the Exclusive Economic Zone (EEZ) (200 nm) area as predicted by the DANP model. Furthermore, re-arrangement of the priorities in sensitivity analysis enhanced the final judgment for the criteria being evaluated; and for the SIM. Qualitatively, the validation of the DANP through the prediction has cumulated a computed value of 76.39 nm (141.47 Km) where this would be the most viable and economical deep sea fishery exploitation location in Malaysian waters and within the EEZ. In this study, MGDI decision and MgdiEureka are newly formulated terminologies to depict decisions in the realms of MGDI initiatives and the developed applications. The framework would serve as an improved marine geospatial planning for various stakeholders prior to decision making | |
dc.description.sponsorship | Faculty of Geoinformation and Real Estate | |
dc.identifier.uri | http://openscience.utm.my/handle/123456789/260 | |
dc.language.iso | en | |
dc.publisher | Universiti Teknologi Malaysia | |
dc.subject | Geospatial data—Computer processing | |
dc.title | Intelligent geospatial decision support system for Malaysian marine geospatial data infrastructure | |
dc.type | Thesis | |
dc.type | Dataset |
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