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Elsevier电子期刊(67)

在“Elsevier电子期刊”中，命中：67条，耗时：小于0.01 秒

在所有数据库中总计命中：67条

1.Fuzzy time series forecasting based on optimal partitions of intervals and optimal weighting vectors

作者：Shyi-Ming Chen ; ^{smchen@mail.ntust.edu.tw} ; Bui Dang Ha Phuong

关键词：Fuzzy time series forecasting ; Two-factors second-order fuzzy logical relationships ; Two-factors second-order fuzzy-trend logical relationship groups ; Particle swarm optimization

刊名：Knowledge-Based Systems

出版年：2017

2.A visibility graph power averaging aggregation operator: A methodology based on network analysis

作者：Wen Jiang ; ^{jiangwen@nwpu.edu.cn} ; ^{jiangwenpaper@hotmail.com} ; Boya Wei ; Jun Zhan ; Chunhe Xie ; Deyun Zhou

关键词：Power Average operator ; Visibility graph ; Networks ; Visibility Graph Averaging operator ; TAIEX

刊名：Computers & Industrial Engineering

出版年：2016

3.The relationship between economic conditions and postpartum depression in Taiwan: a nationwide population-based study

关键词：CPI ; consumer price index ; GDP ; gross domestic product ; ICD-9-CM ; International Classification of Diseases ; 9th Revision ; Clinical Modification ; PPD ; postpartum depression ; TAIEX ; Taiwan Stock Exchange Capitalization Weighted Stock Index ; NHIRD ; National Health Insurance Research Database

刊名：Journal of Affective Disorders

出版年：2016

4.Fuzzy time series forecasting based on fuzzy logical relationships and similarity measures

作者：Shou-Hsiung Cheng^a ; ^b ; ^{shcheng@ctu.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; Shyi-Ming Chen^c ; Wen-Shan Jian^c

关键词：Fuzzy logical relationships ; Fuzzy time series ; K-means clustering algorithm ; Particle swarm optimization ; Similarity measures

刊名：Information Sciences

出版年：2016

5.Combining ARFIMA models and fuzzy time series for the forecast of long memory time series

作者：Hossein Javedani Sadaei^a ; ^{h.javedani@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Rasul Enayatifar^a ; ^{r.enayatifar@gmail.com" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Frederico Gadelha Guimarã ; es^b ; ^{fredericoguimaraes@ufmg.br" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Maqsood Mahmud^c ; ^{maqsood@mcst.edu.sa" class="auth_mail" title="E-mail the corresponding author} ; Zakarya A. Alzamil^d ; ^{zakarya@ksu.edu.sa" class="auth_mail" title="E-mail the corresponding author}

关键词：ARFIMA ; Fuzzy time series ; Long memory time series ; Forecasting ; Stock market ; Exchange rate

刊名：Neurocomputing

出版年：2016

6.A multi-granularity combined prediction model based on fuzzy trend forecasting and particle swarm techniques

作者：Weihui Deng ; ^{dengweihui@cigit.ac.cn" class="auth_mail" title="E-mail the corresponding author}Author Vitae ; Guoyin WangAuthor Vitae ; Xuerui ZhangAuthor Vitae ; Ji XuAuthor Vitae ; Guangdi LiAuthor Vitae

关键词：Fuzzy time series ; Multi-granularity combined prediction model ; Fuzzy trend forecasting ; Granular space ; Particle swarm techniques

刊名：Neurocomputing

出版年：2016

7.An intelligent pattern recognition model for supporting investment decisions in stock market

作者：Tai-liang Chen^a ; ^{97007@mail.wzu.edu.tw" class="auth_mail" title="E-mail the corresponding author} ; ^{too.cool.chen@gmail.com" class="auth_mail" title="E-mail the corresponding author} ; Feng-yu Chen^b

关键词：Stock market forecasting ; Perceptually important point (PIP) identification matching ; Template matching technique ; Chart pattern ; Technical indicator

刊名：Information Sciences

出版年：2016

8.A hybrid fuzzy time series model based on ANFIS and integrated nonlinear feature selection method for forecasting stock

作者：Chung-Ho Su^aAuthor Vitae ; Ching-Hsue Cheng^b ; ^{chcheng@yuntech.edu.tw" class="auth_mail" title="E-mail the corresponding author}Author Vitae

关键词：Fuzzy time series ; Integrated nonlinear feature selection method ; Adaptive Neuro Fuzzy Inference System ; Adaptive expectation model ; Stock forecasting ; Profit evaluation

刊名：Neurocomputing

出版年：2016

9.A novel time-series model based on empirical mode decomposition for forecasting TAIEX

作者：Ching-Hsue Cheng ; Liang-Ying Wei

关键词：Support vector regression (SVR) ; Empirical mode decomposition (EMD) ; TAIEX forecasting

刊名：Economic Modelling

出版年：January, 2014

10.TAIEX forecasting based on fuzzy time series, particle swarm optimization techniques and support vector machines

作者：Shyi-Ming Chen ; Pei-Yuan Kao

关键词：Fuzzy sets ; Fuzzy time series ; Particle swarm optimization ; Support vector machines ; TAIEX

刊名：Information Sciences

出版年：2013

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