Optimization of Multilayer Design for FTTH Networks Based on Geographical Information

Romaithi, Kaltham Al; Ouali, Anis; Poon, Kin Fai; Kong, Peng‐Yong; Lee, Beum-Seuk

doi:10.1109/ieem45057.2020.9309831

Cited by 3 publications

(1 citation statement)

References 8 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The use of a neural network is better than using a decision tree [7]. Dataset is adapted from Kaltham Al Romaithi in 2020 entitled "Optimization of Multilayer Design for FTTH Networks Based on Geographical Information" [8]. We utilizes QGIS with OSM (Open Street Map) as basic map to provide road and demand data which processed using geoAI/ grass, also using k-means to provide clustered demand and route line.…”

Section: Introductionmentioning

confidence: 99%

Design Passive Optical Network Using Multiclass Classification Neural Network

Dewantara¹,

Pramono²,

Rahmadwati³

2021

IJCATR

View full text Add to dashboard Cite

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%.

show abstract

Section: Introductionmentioning

confidence: 99%