Mohammed Algabri

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Navigation and obstacle avoidance in an unknown environment is proposed in this paper using hybrid neural network with fuzzy logic controller. The overall system is termed as Adaptive Neuro Fuzzy Inference System (ANFIS). ANFIS combines the benefits of fuzzy logic and neural networks for the purpose of achieving robotic navigation task. Simulation results(More)
In this paper, we proposed a system for automatic classification of speech. A speech signal contains three different regions voiced, unvoiced and silence. In the proposed system, Zero-Crossing rate and short term energy are used in a fuzzy logic control this classification. Arabic digits of the KSU database is used to test our proposed method. The proposed(More)
An autonomous mobile robot operating in an unstructured environment must be able to learn with dynamic changes to that environment. Learning navigation and control of mobile robot in an unstructured environment is one of the most challenging problems. Fuzzy logic control is a useful tool in the field of navigation of mobile robot. In this research, we(More)
One of the most recent research areas over the last two decades is the navigation of mobile robots in unknown environments. In this paper, real time navigation for Wheeled Mobile Robot (WMR) using fuzzy logic technique, wireless communication and MATLAB is investigated. Two fuzzy logic controllers (FLCs) with two inputs and two outputs are used to navigate(More)
Software cost estimation approximate judgment of the cost and time required to complete the project successfully. The cost estimation is usually measured in terms of effort. The Constructive Cost Model (COCOMO) is one of the most important model for software cost estimation. In this paper, soft computing techniques: genetic algorithm has been used for(More)
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