Fresy Nugroho, Muhammad Faisal, Fachrudin Hunaini
There is still a challenge for efficient watering, considering the exact time and exact watering intervals are unknown. The advances in fuzzy technology and microcontroller technology offer valuable solutions. By using this technology, automatic watering plant based on Humidity and Temperature sensor. However, the application of fuzzy technology requires the optimal determination of membership function. The optimal membership function previously developed using the genetic algorithm. Since the genetic algorithm is time-consuming, many researchers develop optimal membership function using Particles Swarm Optimisation. The modified Particles Swarm Optimisation provides a better solution. Eventually, Autonomous Groups Particles Swarm Optimisation invention offers an optimal solution to search for several mathematical problems. The basic concept of Autonomous Groups Particles Swarm Optimisation algorithm influenced by individuals dissimilarity in bugs swarming or bird flocking. In typical colonies, each insect or bird is not similar in terms of perception and capability, but they all do their commitment as members of the colonies. The Autonomous Groups Particles Swarm Optimisation algorithm discovery has tested for 23 mathematical test functions, but not to the real world. Therefore, the possibility of searching for optimal solutions needs to implement to the real world. In this study, the optimisation applies to fuzzy membership function, so that the automatic plant watering can be more optimal and efficient. Preliminary studies show that optimisation using AGPSO for Gaussian membership function provide a positive result. © Published under licence by IOP Publishing Ltd.
Universitas Islam Negeri Maulana Malik Ibrahim, Malang, Indonesia; Universitas Widyagama, Malang, Indonesia
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