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  1.  32
    Artificial Neural Network for Predicting Animals Category.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic and Applied Research (IJAAR) 3 (2):18-24.
    Abstract: In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the category of an animal. There is a number of factors that influence the classification of animals. Such as the existence of hair/ feather, if the animal gives birth or spawns, it is airborne, aquatic, predator, toothed, backboned, venomous, has –fins, has-tail, cat-sized, and domestic. They were then used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was (...)
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  2.  21
    A Proposed Artificial Neural Network for Predicting Movies Rates Category.Ibrahim M. Nasser, Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Engineering Research (IJAER) 3 (2):21-25.
    We proposed an Artificial Neural Network (ANN) in this paper for predicting the rate category of movies. A dataset used obtained from UCI repository created for research purposes. Our ANN prediction model was developed and validated; validation results showed that the ANN model is able to 92.19% accurately predict the category of movies’ rate.
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  3.  13
    Predicting Tumor Category Using Artificial Neural Networks.Ibrahim M. Nasser & Samy S. Abu-Naser - 2019 - International Journal of Academic Health and Medical Research (IJAHMR) 3 (2):1-7.
    In this paper an Artificial Neural Network (ANN) model, for predicting the category of a tumor was developed and tested. Taking patients’ tests, a number of information gained that influence the classification of the tumor. Such information as age, sex, histologic-type, degree-of-diffe, status of bone, bone-marrow, lung, pleura, peritoneum, liver, brain, skin, neck, supraclavicular, axillar, mediastinum, and abdominal. They were used as input variables for the ANN model. A model based on the Multilayer Perceptron Topology was established and trained using (...)
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  4.  7
    Developing Artificial Neural Network for Predicting Mobile Phone Price Range.Ibrahim M. Nasser, Mohammed Al-Shawwa & Samy S. Abu-Naser - 2019 - International Journal of Academic Information Systems Research (IJAISR) 3 (2):1-6.
    In this paper an Artificial Neural Network (ANN) model, was developed and tested for predicting the price range of a mobile phone. We used a dataset that contains mobile phones information, and there was a number of factors that influence the classification of mobile phone price. Factors as battery power, CPU clock speed, has dual sim support or not, Front Camera mega pixels, has 4G or not, has Wi-Fi or not, etc…. 20 attributes were used as input variables for the (...)
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