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_theses_dir/AN_reasoning_with_SWARL.md

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+---
+title: Ontologies and Reasoning
+layout: default
+description: "This project focuses on how SWARL rules can support inferencing of new knowledge and improve decision-making situations."
+topic: 'Enhancing Ontological Reasoning with SWRL Rules: A Semantic Approach' 
+keywords: 
+ - Ontology
+ - SWARL rule
+ - Inference
+ - Desicion-making
+supervisor: 'JAmeneh Naghdi Pour'
+contact: '[email protected]'
+degree: 'B.Sc.'
+description_link: ''
+---
+
+
+## Enhancing Ontological Reasoning with SWRL Rules: A Semantic Approach
+
+*Supervisor: {{page.supervisor}} ({{page.contact}})*
+
+#### Project Description 
+In the realm of fault diagnosis for complex machines, the ability to reason over explicit knowledge is crucial for identifying the main part of the machine that causes the failures. Ontologies serve as a powerful framework for integrating and representing this knowledge from various sources. In this project, we aim to enhance reasoning capabilities by implementing SWRL (Semantic Web Rule Language) rules within an ontology framework to facilitate effective fault diagnosis.
+
+#### Task
+This project will involve researching existing SWARL rules for reasoning over the fault diagnosis ontology. We will formulate comprehensive SWRL rules to augment reasoning processes, enabling the inference of new information from existing knowledge. The focus will be on how these rules can be formulated to improve knowledge representation and enhance the inference of causes related to machine failures. We will analyze the impact of these SWRL rules on query performance and accuracy through experiments on real-world scenarios, providing insights into their practical applications in the field of fault diagnosis.
+#### Research question
+How can SWRL rules be effectively implemented within ontologies to enhance reasoning capabilities for fault diagnosis in complex machines?
+