Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
Neural Networks and Rules-based Systems used to Find Rational and
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CSTNWSQ93X7
Abhilash Kumar Reddy Manchu
Vehicular ad hoc networks playing significant role in development of intelligent transport system and rise in demand for accessing fascinated applications such as entertainment and advertisements in vehicles via internet leverages to build efficient routing mechanisms. Due to rapid vehicles flow in Vanets, network often subjected to link breaks and creates delay in communication which affects overall network performance, hence to address these serious issue earlier approaches focused on parameters like rate estimation, feedback and link-expiration-time but being different from earlier our Instant Look up and Immediate Action(ILU-IA) technique uses adaptive learning thru past knowledge. ILU-IA identifies immediate neighbour (Free-Hit-Node) efficiently at point of link failure using Case- Based-Learning and Q-learning techniques. Simulation analysis shows that proposed approach performance improved in terms of throughput with negligible delay also reduces network overhead.
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Abhilash Kumar Reddy Manchu. 2017. \u201cFREE HIT A Novel History based Reinforcement Approach for Fast Path Construction in Vehicular Ad hoc Networks\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 17 (GJCST Volume 17 Issue E4): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
The methods for personal identification and authentication are no exception.
The methods for personal identification and authentication are no exception.
Total Score: 102
Country: Unknown
Subject: Global Journal of Computer Science and Technology - E: Network, Web & Security
Authors: Abhilash Kumar Reddy Manchu, A.Rama Mohan Reddy (PhD/Dr. count: 0)
View Count (all-time): 275
Total Views (Real + Logic): 6185
Total Downloads (simulated): 1632
Publish Date: 2017 09, Wed
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Vehicular ad hoc networks playing significant role in development of intelligent transport system and rise in demand for accessing fascinated applications such as entertainment and advertisements in vehicles via internet leverages to build efficient routing mechanisms. Due to rapid vehicles flow in Vanets, network often subjected to link breaks and creates delay in communication which affects overall network performance, hence to address these serious issue earlier approaches focused on parameters like rate estimation, feedback and link-expiration-time but being different from earlier our Instant Look up and Immediate Action(ILU-IA) technique uses adaptive learning thru past knowledge. ILU-IA identifies immediate neighbour (Free-Hit-Node) efficiently at point of link failure using Case- Based-Learning and Q-learning techniques. Simulation analysis shows that proposed approach performance improved in terms of throughput with negligible delay also reduces network overhead.
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