The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. ex. Some numerals are expressed as "XNUMX".
Copyrights notice
The original paper is in English. Non-English content has been machine-translated and may contain typographical errors or mistranslations. Copyrights notice
본 논문에서는 마이크로셀의 파동 전파 손실에 대한 신경망 모델링에 사용되는 현장 측정 및 3차원 지리 데이터로부터 관련 매개변수 값을 추출하는 알고리즘을 제시합니다. 알고리즘은 계산기하학의 이론을 바탕으로 3차원 입면도와 벡터지도에서 특징값을 추출합니다. 이러한 매개변수를 입력으로 훈련한 신경망은 파동 전파 손실의 함수에 근접하며 높은 정확도로 예측을 생성할 수 있습니다. 서울시에서 운영되는 실제 PCS 셀 사이트에서 COST-231 방법에 비해 우리 접근 방식의 우수한 성능을 보여주는 몇 가지 실험 결과가 제시됩니다.
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부
Seomin YANG, Hyukjoon LEE, "Feature Extraction for Neural Network Wave Propagation Loss Models from Field Measurements and Digital Elevation Map" in IEICE TRANSACTIONS on Electronics,
vol. E82-C, no. 7, pp. 1260-1266, July 1999, doi: .
Abstract: This paper presents algorithms for extracting the values of relevant parameters from field measurements and 3-dimensional geographical data to be used in neural network modeling of wave propagation loss in microcells. The algorithms extract the feature values from 3-dimensional elevation maps and vector maps based on the theory in Computational Geometry. The neural networks trained on these parameters as their input approximate the function of wave propagation loss and can produce predictions with high accuracy. Some experimental results which show the superior performance of our approach over COST-231 method in actual PCS cell sites operating in the city of Seoul are presented.
URL: https://global.ieice.org/en_transactions/electronics/10.1587/e82-c_7_1260/_p
부
@ARTICLE{e82-c_7_1260,
author={Seomin YANG, Hyukjoon LEE, },
journal={IEICE TRANSACTIONS on Electronics},
title={Feature Extraction for Neural Network Wave Propagation Loss Models from Field Measurements and Digital Elevation Map},
year={1999},
volume={E82-C},
number={7},
pages={1260-1266},
abstract={This paper presents algorithms for extracting the values of relevant parameters from field measurements and 3-dimensional geographical data to be used in neural network modeling of wave propagation loss in microcells. The algorithms extract the feature values from 3-dimensional elevation maps and vector maps based on the theory in Computational Geometry. The neural networks trained on these parameters as their input approximate the function of wave propagation loss and can produce predictions with high accuracy. Some experimental results which show the superior performance of our approach over COST-231 method in actual PCS cell sites operating in the city of Seoul are presented.},
keywords={},
doi={},
ISSN={},
month={July},}
부
TY - JOUR
TI - Feature Extraction for Neural Network Wave Propagation Loss Models from Field Measurements and Digital Elevation Map
T2 - IEICE TRANSACTIONS on Electronics
SP - 1260
EP - 1266
AU - Seomin YANG
AU - Hyukjoon LEE
PY - 1999
DO -
JO - IEICE TRANSACTIONS on Electronics
SN -
VL - E82-C
IS - 7
JA - IEICE TRANSACTIONS on Electronics
Y1 - July 1999
AB - This paper presents algorithms for extracting the values of relevant parameters from field measurements and 3-dimensional geographical data to be used in neural network modeling of wave propagation loss in microcells. The algorithms extract the feature values from 3-dimensional elevation maps and vector maps based on the theory in Computational Geometry. The neural networks trained on these parameters as their input approximate the function of wave propagation loss and can produce predictions with high accuracy. Some experimental results which show the superior performance of our approach over COST-231 method in actual PCS cell sites operating in the city of Seoul are presented.
ER -