Utilizing modular neural network for prediction of possible emergencies locations within point of interest of Hajj pilgrimage

• Main Authors: Abubakar, Adamu, Haruna, Chiroma, Abdullah, Khan, Fatihu, Mukhtar, Dauda, Ali Baba, Mahmood, Nadeem, Shah, Asadullah, Maitama, Jaafar Zubairu, Herawan, Tutut
• Format: Article
• Language: English
• Published: Canadian Center of Science and Education 2016
• Subjects: QA76 Computer software
• Online Access: http://irep.iium.edu.my/46886/1/Modular.pdf; http://irep.iium.edu.my/46886/; http://www.ccsenet.org/journal/index.php/mas
• Institution: Universiti Islam Antarabangsa Malaysia

This paper utilize modular neural network for prediction of possible emergencies locations during hajj pilgrimage. Available location, localization and positioning determination systems become increasingly important for use in day-to-day activities. These systems dwells on various scientific tools which ensure that the systems will provide accurate response to the needed service at the right time. Unfortunately, some tools were faced with drawbacks, either their use was not appropriate or they do not give reliable results, or the results obtained in certain scenario might not be apply to other scenarios. For this reasons, we utilize modular neural network tool to examine the analysis of determining possible emergencies locations within point of Interest of Hajj Pilgrimage in Meccah Saudi Arabia. The prediction results are generated by the use of longitude, latitude and distances as the dataset. Modular neural network takes longitude and latitude as inputs and predict distances within pilgrim’s possible point of interest. The learning systems were trained on the collected data. Experimental investigation demonstrated that modular network produce higher prediction accuracy compaired to other tools. This finding would contribute to the design of add-on applications which will deem to provide location based services for possible emergencies locations.