Open AccessDesign Passive Optical Network Using Multiclass Classification Neural Network
Author(s) -
Firman Pratama Dewantara,
Sholeh Hadi Pramono,
Rahmadwati
Publication year - 2021
Publication title -
international journal of computer applications technology and research
Language(s) - English
Resource type - Journals
ISSN - 2319-8656
DOI - 10.7753/ijcatr1006.1005
Subject(s) - computer science , backpropagation , splitter , artificial neural network , passive optical network , the internet , network planning and design , quality of service , network architecture , computer network , service (business) , quality (philosophy) , telecommunications , artificial intelligence , world wide web , wavelength division multiplexing , wavelength , philosophy , physics , geometry , mathematics , optoelectronics , economy , epistemology , economics
To require the order of last mile and the increasing demands of high quality of internet, the network architecture of FTTH (Fiber to the Home) has been chosen by numerous ISP (Internet Service Provider). Poor planning does not only increase the infrastructure costs, but it also increases maintenance costs. In this study, the authors focus on the design of passive optical network by using multiclass classification [9] in backpropagation neural network to shorten the FTTH network planning based on passive optical network design to determine final splitter type which refers to the feasibility of QoS (Quality of Service) and Cost Efficiency. Dataset in this study utilizes GIS (Geographic Information System) report with 33 sub-districts in Malang Regency in 2019 data layer. As a result, after 7300 epoch, the accuracy training was 99.99% and the splitter classification accuracy was 98.76%.