<![CDATA[This research provides a thorough analysis of the algorithms used in the Low Energy Adaptive Clustering Hierarchy (LEACH) protocol for Wireless Sensor Networks (WSNs) to apply Fuzzy Logic, Adaptive Neuro-Fuzzy Inference System (ANFIS), and Harris Hawks Optimisation-Particle Swarm Optimisation (HHOPSO). The primary aim of this paper is to compare and measure these methods by how they save energy, prolong the network’s lifetime and choose the best cluster heads. We look at major indicators such as First Node Death (FND) and the number of rounds when 80% and 50% of nodes are still working, by testing 100 simulated network nodes. The HHOPSO is shown to do a better job at keeping node batteries alive and, at length the network in operation than both Fuzzy Logic and ANFIS. Moreover, ANFIS is more effective than Fuzzy Logic, because it can learn better from data. It is found that HHOPSO helps LEACH become more efficient and effective, contributing new information about how to manage energy and network performance in Wireless Sensor Networks. The document shows the effectiveness of advanced algorithms in keeping sensor networks running longer and offers ideas on how to evaluate them in various network settings.]]>
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