Neural Networks and Rules-based Systems used to Find Rational and Scientific Correlations between being Here and Now with Afterlife Conditions
February 17, 2026
Neural Networks and Rules-based Systems used to Find Rational and
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Ad hoc networks consist of independent self structured nodes. Nodes use a wireless medium for exchange their message or data, therefore two nodes can converse directly if and only if they are within each other’s broadcast range. Swarm intelligence submits to complex behaviors that occur from very effortless individual activities and exchanges, which is frequently experienced in nature, especially amongst social insects such as ants. Although each individual (an ant) has little intelligence and simply follows basic rules using local information gained from the surroundings, for instance ant’s pheromone track arranging and following activities, globally optimized activities, such as discovering a shortest route, appear when they work together as a group. In this regard in our earlier work we proposed a biologically inspired metaphor based routing in mobile ad hoc networks that referred as Swarm Adaptive Hybrid Routing (SAHR). . With the motivation gained from SAHR, here in this paper we propose a energy efficient swarm adaptive hybrid routing topology (ESAHR). The goal is to improve transmission performance along with energy conservation that used for packet transmission In this paper we use our earlier proposed algorithm that inspired from Swarm Intelligence to obtain these characteristics. In an extensive set of simulation tests, we evaluate our routing algorithm with state-of-the-art algorithm, and demonstrate that it gets better performance over a wide range of diverse scenarios and for a number of different assessment measures. In particular, we show that it scales better in energy conservation with the number of nodes in the network.
Mr. B. M. G. Prasad. 2012. \u201cESAHR: Energy Efficient Swarm Adaptive Hybrid Routing Topology for Mobile Ad hoc Networks\u201d. Global Journal of Computer Science and Technology - E: Network, Web & Security GJCST-E Volume 12 (GJCST Volume 12 Issue E15): .
Crossref Journal DOI 10.17406/gjcst
Print ISSN 0975-4350
e-ISSN 0975-4172
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Neural Networks and Rules-based Systems used to Find Rational and
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Ad hoc networks consist of independent self structured nodes. Nodes use a wireless medium for exchange their message or data, therefore two nodes can converse directly if and only if they are within each other’s broadcast range. Swarm intelligence submits to complex behaviors that occur from very effortless individual activities and exchanges, which is frequently experienced in nature, especially amongst social insects such as ants. Although each individual (an ant) has little intelligence and simply follows basic rules using local information gained from the surroundings, for instance ant’s pheromone track arranging and following activities, globally optimized activities, such as discovering a shortest route, appear when they work together as a group. In this regard in our earlier work we proposed a biologically inspired metaphor based routing in mobile ad hoc networks that referred as Swarm Adaptive Hybrid Routing (SAHR). . With the motivation gained from SAHR, here in this paper we propose a energy efficient swarm adaptive hybrid routing topology (ESAHR). The goal is to improve transmission performance along with energy conservation that used for packet transmission In this paper we use our earlier proposed algorithm that inspired from Swarm Intelligence to obtain these characteristics. In an extensive set of simulation tests, we evaluate our routing algorithm with state-of-the-art algorithm, and demonstrate that it gets better performance over a wide range of diverse scenarios and for a number of different assessment measures. In particular, we show that it scales better in energy conservation with the number of nodes in the network.
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