利用人工神经网络开发“Basura优势点”概念的废物管理系统

Ronan Cadmiel C. Castro, Erwin dR. Magsakay, A. Geronimo, Cristopher Conato, Jamella Denise Cruz, Juan Rafael Alvaran, Vann Joseph Oblanca
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引用次数: 3

摘要

世界上最紧迫的问题之一是日益严重的固体废物污染。根据当前可持续发展的需求,研究人员开发了一种满足高效隔离的垃圾分选机,并引入了奖励制度的概念来激励人们将垃圾扔进机器。在本文中,研究人员创造了一种自动分离机器,该机器使用人工神经网络(ANN)作为机器学习的算法,并嵌入了“Basura Advantage Points”的概念。人工神经网络作为机器的大脑,将塑料瓶分类为一类,将其他废物分类为另一类。“Basura优势积分”是一个新颖的概念,当人们把垃圾扔进分拣机时,他们就可以获得积分,这些积分可以用来兑换政策制定者设定的奖励。调查结果显示这种机器很受大众欢迎。根据样品废料,机器的准确度在80%左右。从积极的反馈到成功的评估,这项研究突出了一个良好的模式,以减少不当的废物处置,并鼓励人们参与适当的废物分类。
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Development of Waste Management System using the Concept of ‘Basura Advantage Points’ through Artificial Neural Network
One of the most pressing problems of the world is the growing solid waste pollution. With current demands for sustainable development, the researchers developed a waste segregator machine that satisfies efficient segregation and introduces the concept of reward system to motivate people to throw their waste into the machine. In this paper, the researchers created an automatic segregating machine that uses Artificial Neural Network (ANN) as an algorithm for machine learning and embedded with the concept of “Basura Advantage Points”. The ANN acts as the brain of the machine for sorting out the plastic bottles as one category and other waste materials for the other category. The “Basura Advantage Points” is a novel concept wherein whenever people throw a garbage into the segregating machine, they can earn points which can then be used to redeem awards set by policy makers. Survey results show that the machine is appealing to the public. Based on the sample wastes, the accuracy of the machine is around 80 percent. From positive feedbacks to successful evaluation, the study highlighted a good model to decrease improper waste disposal and encourage people to participate in proper waste segregation.
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