Medhat H A Awadalla

Work place: Electrical and Computer Engineering Department, SQU, Oman



Research Interests: Computer systems and computational processes, Robotics, Network Architecture, Data Structures and Algorithms


Medhat Awadalla is an Assistant Professor with Electrical and Computer Engineering department, SQU, Oman. He is on leave from Helwan University, Egypt. He has received his PhD from Cardiff University 2005, MSc and BSc from Helwan University, Egypt in 1996 and 1991 respectively. His research interset includes real time sytems, sensor network and mobile robots.

Author Articles
Spiking Neural Network and Bull Genetic Algorithm for Active Vibration Control

By Medhat H A Awadalla

DOI:, Pub. Date: 8 Feb. 2018

Systems with flexible structures display vibration as a characteristic property. However, when exposed to disturbing forces, then the component and/or structural nature of such systems are damaged. Therefore, this paper proposes two heuristics approaches to reduce the unwanted structural response delivered due to the external excitation; namely, bull genetic algorithm and spiking neural network. The bull genetic algorithm is based on a new selection property inherited from the bull concept. On the other hand, spiking neural network possess more than one synaptic terminal between each neural network layer and each synaptic terminal is modelled with a different period of delay. Extensive simulations have been conducted using simulated platform of a flexible beam vibration. To validate the proposed approaches, we performed a qualitative comparison with other related approaches such as traditional genetic algorithm, general regression neural network, bees algorithm, and adaptive neuro-fuzzy inference system. Based on the obtained results, it is found that the proposed approaches have outperformed other approaches, while bull genetic algorithm has a 5.2% performance improvement over spiking neural network.

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