Results 91 to 100 of about 3,753 (202)

Proposal of a Geometric Calibration Method Using Sparse Recovery to Remove Linear Array Push-Broom Sensor Bias

open access: yesSensors, 2019
The rational function model (RFM) is widely used in the most advanced Earth observation satellites, replacing the rigorous imaging model. The RFM method achieves the desired calibration performance when image distortion is caused by long-period errors ...
Jun Chen   +3 more
doaj   +1 more source

Association between Relative Fat Mass and Cardiovascular Disease in Middle-aged and Elderly Population: a Cross-sectional and Longitudinal Study Based on CHARLS [PDF]

open access: yesZhongguo quanke yixue
Background In recent years, an association has been found between the relative fat mass (RFM) and cardiovascular disease (CVD) . However, nationwide cohort studies on RFM and the risk of CVD in the Chinese population are scant.
CHEN Huilong, LIAO Yunchu, LIU Yuwei, KONG Zhenghui, HUANG Xinghui, XU Jiahui, QI Na, WANG Yuanping, LIANG Wenjian
doaj   +1 more source

Perbandingan Hasil Segmentasi Pelanggan dengan RFM Scoring dan RFM Based K-Means Clustering [PDF]

open access: yes
Analisis yang umum digunakan dalam pengelompokan pelanggan adalah analisis model Recency, Frequency, Monetary (RFM). Model ini memaparkan pelanggan berdasarkan interval waktu kunjungan terakhir pelanggan, frekuensi kunjungan, dan besaran nilai yang ...
Muliabanta, Natanael Hadi
core  

Association between relative fat mass and gallstones: a cross-sectional study based on NHANES 2017–2020

open access: yesFrontiers in Nutrition
BackgroundGallstones are a common gastrointestinal disease worldwide, associated with significant public health burdens. Obesity and fat distribution are recognized as major risk factors for gallstone formation, yet traditional anthropometric indices ...
Chaofeng Gao   +3 more
doaj   +1 more source

Customer segmentation using RFM analysis

open access: yes, 2020
This paper is a research on the segmentation of customers. The clustering of customers is done based on the variables recency, frequency and monetary value. Such a clustering is called an RFM-model.
van Burg, J.M. (author)
core  

New Approach: Customer Segmentation using RFM Model and Demand Classification

open access: yes
This research introduces an integrated data mining framework that combines RFM (Recency, Frequency, Monetary) analysis with demand pattern classification—encompassing Smooth, Erratic, Intermittent, and Lumpy categories—to refine customer segmentation ...
Muhammad Fermi Pasha   +2 more
core   +1 more source

A Comparison of the Performance of Bias-Corrected RSMs and RFMs for the Geo-Positioning of High-Resolution Satellite Stereo Imagery

open access: yesRemote Sensing, 2015
High-resolution stereo satellite imagery is widely used in environmental monitoring, topographic mapping, and urban three-dimensional (3D) reconstruction.
Zhonghua Hong   +5 more
doaj   +1 more source

ANALISIS REKOMENDASI PRODUK BERDASARKAN SEGMENTASI PELANGGAN DENGAN MODEL RFM MENGGUNAKAN ALGORITMA DBSCAN DAN FP-GROWTH [PDF]

open access: yes, 2022
DEWI ANJAINAH (2022) : ANALISIS REKOMENDASI PRODUK BERDASARKAN SEGMENTASI PELANGGAN DENGAN MODEL RFM MENGGUNAKAN ALGORITMA DBSCAN DAN FP-GROWTH Swalayan 212 Mart merupakan bisnis ritel berlandaskan koperasi syariah yang sudah menerapkan strategi ...
DEWI ANJAINAH, -
core  

Modification of RFM model with Runs of shopping recency

open access: yes, 2010
碩士現代企業資料庫中,往往擁有龐大的顧客交易資料以及顧客基本資料。為了從資料庫中瞭解顧客行為,目前業界最常使用的是簡單捕捉顧客行為模式的RFM模型,並利用RFM模型找出對企業貢獻度高的顧客,進而進行顧客關係管理。本研究以RFM模型為基礎,將消費頻率的分布情形與變動權重的概念導入,引用「連」(Run)的概念,將一般評估顧客指標的RFM模型加以修正。本文以廣義伽瑪分配模擬出顧客的交易時間,透過線性判別分析比較Hughes和Stone指標,以及本研究所提出的新指標法(S ...
陳慈慧; Chen, Tzu-hui
core  

RFM user value tags and XGBoost algorithm for analyzing electricity customer demand data

open access: yesSystems and Soft Computing
With the increasing demand for electricity, predicting user electricity demand has become an essential task. The electricity demand characteristics of users in the electricity market are different, so it is necessary to classify and predict users. Aiming
Zhu Tang, Yang Jiao, Mingmin Yuan
doaj   +1 more source

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