Energy efficient data fusion approach using squirrel search optimization and recurrent neural network

نویسندگان

چکیده

Sensor networks have helped wireless communication systems. Over the last decade, researchers focused on energy efficiency in sensor networks. Energy-efficient routing remains unsolved. Because energyconstrained sensors limited computing capabilities, extending their lifespan is difficult. This work offers a simple, energy-efficient data fusion technique employing zonal node information. Using witness-based technique, evaluated network lifetime, consumption, overhead, end-to-end delay, and delivery ratio. Energyefficient optimizes utilization using squirrel search optimization recurrent neural network. The method allows system to recognize with excessive dissipation relocate more node. proposed model was compared against artificial network-particle swarm (ANN-PSO), cuckoo algorithm-back propagation (COABPNN), Elman network-whale algorithm (ENN-WOA), extreme learning machine-particle (ELM-PSO). achieved 94.50% 26.63% 93.85% ratio, 10.50 ms 282 J usage.

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ژورنال

عنوان ژورنال: Indonesian Journal of Electrical Engineering and Computer Science

سال: 2023

ISSN: ['2502-4752', '2502-4760']

DOI: https://doi.org/10.11591/ijeecs.v31.i1.pp480-490