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General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

Frontiers of Mechanical Engineering 2009, Volume 4, Issue 1,   Pages 15-24 doi: 10.1007/s11465-009-0015-z

Abstract: The typical time series models such as ARMA, AR, and MA are founded on the normality and stationarityThis paper proposes a general expression for linear and nonlinear auto-regressive time series modelsThe modeling and prediction accuracy of the GNAR model is superior to the classical time series models

Keywords： linear and nonlinear     autoregressive model     system identification     time series analysis    

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Employing electricity-consumption monitoring systems and integrative time-series analysis models: A case

Seiya MAKI, Shuichi ASHINA, Minoru FUJII, Tsuyoshi FUJITA, Norio YABE, Kenji UCHIDA, Gito GINTING, Rizaldi BOER, Remi CHANDRAN

Frontiers in Energy 2018, Volume 12, Issue 3,   Pages 426-439 doi: 10.1007/s11708-018-0560-4

Abstract: innovation in smart energy monitoring technologies, the identification of appropriate methods for detailed time-seriesanalysis, and the application of these technologies at urban and national scales.The real-time SEMS data and time-series clustering to explore similarities in electricity consumption

Keywords： electricity monitoring     electricity demand prediction     multiple-variable time-series modeling     time-seriescluster analysis     Indonesia    

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Analyzing construction safety through time series methods

Houchen CAO, Yang Miang GOH

Frontiers of Engineering Management 2019, Volume 6, Issue 2,   Pages 262-274 doi: 10.1007/s42524-019-0015-6

Abstract: Thus, this work describes how temporal analysis techniques can be applied to improve the safety managementVarious time series (TS) methods were adopted for identifying the leading indicators or predictors ofFive projects with complete and sufficient data for temporal analysis were selected from the data setThis study provides insights into how construction companies can utilize TS data analysis to identify

Keywords： time series     temporal     construction safety     leading indicators     accident prevention     forecasting    

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Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated

Frontiers of Medicine 2023, Volume 17, Issue 1,   Pages 68-74 doi: 10.1007/s11684-022-0955-9

Abstract: Most information used to evaluate diabetic statuses is collected at a special time-point, such as takingBy calculating the complexity of glucose time series index (CGI) with refined composite multi-scale entropyanalysis of the CGM data, the study showed for the first time that the complexity of glucose time series

Keywords： complexity of glucose time series     continuous glucose monitoring     impaired glucose regulation     insulin    

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Time-series prediction based on global fuzzy measure in social networks

Li-ming YANG,Wei ZHANG,Yun-fang CHEN

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 10,   Pages 805-816 doi: 10.1631/FITEE.1500025

Abstract: Social network analysis (SNA) is among the hottest topics of current research.

Keywords： Time-series network     Fuzzy network     Fuzzy Markov chain    

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Time Series Diagnosing Analysis for the Fatigue Crack of Large-scale and Heavyburden Supporting Shafts

Li Xuejun,Bin Guangfu,Wang Yuqing

Strategic Study of CAE 2006, Volume 8, Issue 4,   Pages 50-53

Abstract: vibration signal characteristic, the model of the vibration signal is established by the method of timeseries.Residual (σtime-frequency

Keywords： large-scale and heavyburden machine     supporting shaft     concealment part     fatigue crack     time series    

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Generalization and application in time series forecasting of the least square support vector machine

Xiang Xiaodong

Strategic Study of CAE 2008, Volume 10, Issue 11,   Pages 89-92

Abstract: According to the theory that the present data contains more future information than historical data in time-seriessupport vector machine,and develops algorithm of the extended prediction model.Prediction examples of two time-series

Keywords： least square support vector machine     generalization     time series     forecasting    

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Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos

LI Xiaodong, ZENG Guangming, HUANG Guohe, LI Jianbing, JIANG Ru

Frontiers of Environmental Science & Engineering 2007, Volume 1, Issue 3,   Pages 334-338 doi: 10.1007/s11783-007-0057-6

Abstract: The nonlinear dynamic characteristic of WWTP influent quantity time series was analyzed, with the assumptionthat the series was predictable.

Keywords： nonlinear     reconstruction     WWTP influent     characteristic     Reasonable forecasting    

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A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Basedon Multi-Factor Analysis and a Multi-Model Ensemble Article

Hui Liu, Rui Yang, Zhu Duan, Haiping Wu

Engineering 2021, Volume 7, Issue 12,   Pages 1751-1765 doi: 10.1016/j.eng.2020.10.023

Abstract: this paper, a new DO hybrid forecasting model is proposed that includes three stages: multi-factor analysisinto sub-series by means of the empirical wavelet transform (EWT) method.Then, five benchmark models are utilized to forecast the sub-series of EWT decomposition.The performance of the proposed model is verified by time-series data collected by the pacific islandsExample analysis demonstrates that: ① the proposed model can obtain excellent DO forecasting results;

Keywords： Dissolved oxygen concentrations forecasting     Time-series multi-step forecasting     Multi-factor analysis    

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Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 149-156 doi: 10.1007/s11465-010-0008-y

Abstract: At the same time, combined with spectrum analysis of the autoregressive model of quality parameters,

Keywords： statistical process control (SPC)     fuzzy adaptive resonance theory (ART)     histogram     control chart     timeseries analysis    

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Decomposition analysis of energy-related carbon dioxide emissions in the iron and steel industry in China

Wenqiang SUN, Jiuju CAI, Hai YU, Lei DAI

Frontiers of Environmental Science & Engineering 2012, Volume 6, Issue 2,   Pages 265-270 doi: 10.1007/s11783-011-0284-8

Abstract: The logarithmic mean divisia index (LMDI) technique was applied with period-wise analysis and time-seriesanalysis.

Keywords： carbon dioxide (CO2) emissions     decomposition analysis     logarithmic mean divisia index (LMDI) technique     time-series analysis    

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Performance analysis of series/parallel and dual side LCC compensation topologies of inductive power

P. Srinivasa Rao NAYAK, Dharavath KISHAN

Frontiers in Energy 2020, Volume 14, Issue 1,   Pages 166-179 doi: 10.1007/s11708-018-0549-z

Abstract: This paper analyzes series/parallel (S/P) and dual side inductor-capacitor-capacitor (LCC) compensation

Keywords： series/parallel compensation     electric vehicle (EV)     dual side LCC compensation     inductive power transfer    

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Prediction and cause investigation of ozone based on a double-stage attention mechanism recurrent neural network

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 2, doi: 10.1007/s11783-023-1621-4

Abstract:

● Used a double-stage attention mechanism model to predict ozone.

Keywords： Ozone prediction     Deep learning     Time series     Attention     Volatile organic compounds    

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Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

Frontiers of Information Technology & Electronic Engineering 2015, Volume 16, Issue 9,   Pages 744-758 doi: 10.1631/FITEE.1400376

Abstract: The symbolic representation of time series has attracted much research interest recently.The high dimensionality typical of the data is challenging, especially as the time series becomes longerIn this paper, we propose a new symbolic representation method for long time series based on trend featuresThe method uses a two-step mechanism to segment long time series rapidly.A time series is represented by trend symbols, which are also suitable for use in knowledge discovery

Keywords： Long time series     Segmentation     Trend features     Symbolic     Knowledge discovery    

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Vectorial Eigenmode Analysis of Optical Waveguides Based on the Variable Transformed Series Expansion

Xiao Jinbiao,Sun Xiaohan,Zhang Mingde,Ding Dong

Strategic Study of CAE 2001, Volume 3, Issue 11,   Pages 49-53

Abstract: supported by the buried rectangular and rib optical waveguides are obtained using variable transformed series

Keywords： variable transformed series expansion method     optical waveguides     vectorial eigenmode analysis    

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Title Author Date Type Operation

General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

Journal Article

Employing electricity-consumption monitoring systems and integrative time-series analysis models: A case

Seiya MAKI, Shuichi ASHINA, Minoru FUJII, Tsuyoshi FUJITA, Norio YABE, Kenji UCHIDA, Gito GINTING, Rizaldi BOER, Remi CHANDRAN

Journal Article

Analyzing construction safety through time series methods

Houchen CAO, Yang Miang GOH

Journal Article

Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlated

Journal Article

Time-series prediction based on global fuzzy measure in social networks

Li-ming YANG,Wei ZHANG,Yun-fang CHEN

Journal Article

Time Series Diagnosing Analysis for the Fatigue Crack of Large-scale and Heavyburden Supporting Shafts

Li Xuejun,Bin Guangfu,Wang Yuqing

Journal Article

Generalization and application in time series forecasting of the least square support vector machine

Xiang Xiaodong

Journal Article

Short-term prediction of the influent quantity time series of wastewater treatment plant based on a chaos

LI Xiaodong, ZENG Guangming, HUANG Guohe, LI Jianbing, JIANG Ru

Journal Article

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Basedon Multi-Factor Analysis and a Multi-Model Ensemble

Hui Liu, Rui Yang, Zhu Duan, Haiping Wu

Journal Article

Statistical process control with intelligence using fuzzy ART neural networks

Min WANG, Tao ZAN, Renyuan FEI,

Journal Article

Decomposition analysis of energy-related carbon dioxide emissions in the iron and steel industry in China

Wenqiang SUN, Jiuju CAI, Hai YU, Lei DAI

Journal Article

Performance analysis of series/parallel and dual side LCC compensation topologies of inductive power

P. Srinivasa Rao NAYAK, Dharavath KISHAN

Journal Article

Prediction and cause investigation of ozone based on a double-stage attention mechanism recurrent neural network

Journal Article

Symbolic representation based on trend features for knowledge discovery in long time series

Hong YIN,Shu-qiang YANG,Xiao-qian ZHU,Shao-dong MA,Lu-min ZHANG

Journal Article

Vectorial Eigenmode Analysis of Optical Waveguides Based on the Variable Transformed Series Expansion

Xiao Jinbiao,Sun Xiaohan,Zhang Mingde,Ding Dong

Journal Article