Artificial Intelligence Technique Based Effective Disaster Recovery Framework to Provide Longer Time Connectivity in Mobile Ad-hoc Networks
Artificial Intelligence; Geographical Information System; Greedy Randomized Adaptive; Neural Network; Search Procedure
Communication plays a vital role for effective management and for the execution of disaster response and emergency recovery efforts must be able to exchange information with each other from anywhere, at any time to successfully fulfill their missions. Therefore, it is important to configure emergency communications networks in disaster conditions using ad-hoc networks. This proposed framework collects the information and communication before or after a disaster. The aim of this research work is to propose a possible practical communication model by using ad-hoc network configuration technologies using Greedy Randomized Adaptive Search Procedure (GRASP) with the proposed algorithm. The development of this research work is to improve information exchange and facilitate coordination among emergency services and disaster field offices, state/level entities and private industry. This is accomplished by the integration of existing information systems, implementation of new efficient technologies and interconnection of established networks with artificial based techniques. IJCESEN.
International Journal of Computational and Experimental Science and Engineering, Vol-11, No. 1, pp. 87-96.
https://doi.org/10.22399/ijcesen.713 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85214976082&doi=10.22399%2fijcesen.713&partnerID=40&md5=e23b3179d305ca888c943bf92416d063
Robert N.R., Department of Computer Science, Christ University, Bangalore, 560029, India; Cecil Donald A., Department of Computer Science, Christ University, Bangalore, 560029, India; Suresh K., Department of Computer Science, Christ University, Bangalore, 560029, India