Mokhtar Beldjehem

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The validation and verification (V&V) of hybrid fuzzyneuro (HFN) or hybrid neurofuzzy (HNF) systems becomes of increasing concern as these systems are fielded and embedded in the every day operations of medical diagnosis, pattern recognition, fuzzy control and other industries-particularly so when life-critical and environment-critical aspects are(More)
The validation and verification (V&V) of hybrid fuzzyneuro (HFN) or hybrid neurofuzzy (HNF) systems becomes of increasing concern as these systems are fielded and embedded in the every day operations of medical diagnosis, pattern recognition, fuzzy control and other industries particularly so when life-critical and environment-critical aspects are(More)
We propose herein a novel unified framework that uses a developed hybrid fuzzy-neuro system in order to evaluate the impact of inheritance aspects on the evolvability of a class library, and to study the relevance of using inheritance as indicator of class interface stability with respect to version change. To this goal, we propose a novel computational(More)
In this paper we present through the fennec tool : a fuzzy-neuro system, a new approach to combine fuzzy set theory and neural networks, it uses a new supervised learning mechanism based on the resolution of MIN-MAX fuzzy relational equations. The rennet system is implemented in C with application to biomedical diagnosis on proteins/biological inflammatory(More)
We propose a novel computational granular unified framework that is cognitively motivated for learning if-then fuzzy weighted rules by using a hybrid fuzzy-neuro possibilistic model appropriately crafted as a learning device of fuzzy rules from only raw input-output examples by integrating some useful concepts from the human cognition processes and adding(More)
We propose to accommodate herein our novel unified granular framework that uses a developed hybrid fuzzy-neuro relational system in order to tackle a complex medical diagnosis problem and to understand the influence of syndromes in relation to symptoms. To this goal, we propose to adapt our novel computational granular unified framework that is(More)
This paper describes a novel energy-aware multi-hop cluster-based fault-tolerant load balancing hierarchical routing protocol for a self-organizing wireless sensor network (WSN), which takes into account the broadcast nature of radio. The main idea is using hierarchical fuzzy soft clusters enabling non-exclusive overlapping clusters, thus allowing partial(More)