Publication:
Risk Assessment Of Mined Areas Using Fuzzy Inference

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dc.contributor.authorSalem S. M. Khalifaen_US
dc.contributor.authorKamarudin Saadanen_US
dc.contributor.authorNorita Md. Norwawien_US
dc.date.accessioned2024-05-28T03:53:48Z
dc.date.available2024-05-28T03:53:48Z
dc.date.issued2015
dc.date.submitted--
dc.descriptionVolume: 6 No 2 (page: 37-51)en_US
dc.description.abstractDuring the World War I ,II over fifty countries in the world today have been inherited a legacy of antipersonnel landmines and unexploded ordnance (UXO) which represents a major threat to lives, and hinders reconstruction and development efforts. Landmines have specific properties that make it harder to detect .Therefore; these properties lead landmine detectors to become more complex. Many examples can be found to address the increasing complexity of Landmines detection; unfortunately, these new techniques are high of cost and need experts to deal with it. Many developing countries face financial difficulties to get advanced technologies for detection landmines such as Robotic systems, this due to their high cost, use and maintenance difficulties which makes them unaffordable to these countries. The safety of operators, transportability, ease of maintenance and operation are the most factors that must take into consideration to improve the applicability and effectiveness of landmines tracking systems.The aim of the study is to proposed architecture of Intelligent Wireless Landmines Tracking System (IWLTS) with new decision model based on fuzzy logic. To find an affordable, light and easy to use alternative which meet users’ needs to protect and warn them from the risk of landmines during practice their lives, we suggested the design and development of Fuzzy Inference Model for IWLTS using Smart Phone. Fuzzy model require three step which are definitions of Linguistic Variable and fuzzy sets, determine fuzzy rules and the process of Fuzzy Inference. Designed Fuzzy Inference Model gives both: Landmine risk value in percentage and alert to avoid that risk.en_US
dc.identifier.doi10.5121/ijaia.2015.6203
dc.identifier.epage51
dc.identifier.issn0975-900X
dc.identifier.issue2
dc.identifier.spage37
dc.identifier.urihttps://aircconline.com/ijaia/V6N2/6215ijaia03.pdf
dc.identifier.urihttps://oarep.usim.edu.my/handle/123456789/5205
dc.identifier.volume6
dc.language.isoen_USen_US
dc.publisherAcademy & Industry Research Collaboration Centeren_US
dc.relation.ispartofInternational Journal of Artificial Intelligence & Applicationsen_US
dc.subjectFuzzy logic, Membership Function, Fuzzy Rule, Fuzzy Inference System, Matlab, Landmines, Risk Assessmenten_US
dc.titleRisk Assessment Of Mined Areas Using Fuzzy Inferenceen_US
dc.typeArticleen_US
dspace.entity.typePublication

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