Resource Type

Journal Article 392

Conference Videos 6

Year

2023 25

2022 27

2021 32

2020 30

2019 28

2018 24

2017 27

2016 18

2015 15

2014 10

2013 17

2012 13

2011 19

2010 11

2009 11

2008 15

2007 22

2006 19

2005 6

2004 3

open ︾

Keywords

different 6

China 4

simulation 4

Accelerated aging test 2

Around corners 2

BIM 2

Boolean control networks 2

Computational complexity 2

Deep learning 2

LED lamp 2

Medium lifetime 2

Moving average error 2

Time delay 2

complexity 2

complexity science 2

construction time 2

demand response 2

performance evaluation 2

scheduling 2

open ︾

Search scope:

排序： Display mode:

Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlatedwith deteriorating glucose regulation

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 takingmonitoring” (CGM) can characterize glucose dynamics.By 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 seriesin subjects decreased gradually from normal glucose tolerance to impaired glucose regulation and then

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

HTML PDF Collect

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: Various time series (TS) methods were adopted for identifying the leading indicators or predictors of

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

HTML PDF Collect

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    

HTML PDF Collect

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. Most measurements of SNA methods are certainty oriented, while in reality, the uncertainties in relationships are widely spread to be overridden. In this paper, fuzzy concept is introduced to model the uncertainty, and a similarity metric is used to build a fuzzy relation model among individuals in the social network. The traditional social network is transformed into a fuzzy network by replacing the traditional relations with fuzzy relation and calculating the global fuzzy measure such as network density and centralization. Finally, the trend of fuzzy network evolution is analyzed and predicted with a fuzzy Markov chain. Experimental results demonstrate that the fuzzy network has more superiority than the traditional network in describing the network evolution process.

Keywords： Time-series network     Fuzzy network     Fuzzy Markov chain    

HTML PDF Collect

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-seriesThe 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-series    

HTML PDF Collect

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    

HTML PDF Collect

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    

HTML PDF Collect

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    

HTML PDF Collect

Anti-biofouling strategies for implantable biosensors of continuous glucose monitoring systems

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 12,   Pages 1866-1878 doi: 10.1007/s11705-023-2340-x

Abstract: Continuous glucose monitoring (CGM) systems play an increasingly vital role in the glycemic control of

Keywords： implantable glucose biosensor     anti-biofouling     continuous glucose monitoring     immune responses    

HTML PDF Collect

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    

HTML PDF Collect

decorated with polypyrrole and nickel-cobalt layered double hydroxide for high-performance nonenzymatic glucose

Frontiers of Chemical Science and Engineering 2023, Volume 17, Issue 10,   Pages 1593-1607 doi: 10.1007/s11705-023-2348-2

Abstract: With the synergistic effect of three heterogeneous components, the electrode achieves outstanding glucoseperformance, including a high sensitivity (851.4 µA·mmol−1·L·cm−2), a short response timeThese data are superior to those of some traditional glucose sensors using nonbiomass substrates.When determining the blood glucose level of a human serum, this electrode realizes a high recovery rateof 97.07%–98.89%, validating the potential for high-performance blood glucose sensing.

Keywords： cellulose nanofibril     aerogel     nickel-cobalt layered double hydroxide     polypyrrole     nonenzymatic glucose    

HTML PDF Collect

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    

HTML PDF Collect

Managing stakeholder dynamics and complexity in mega infrastructure projects

Geoffrey Qiping SHEN, Jin XUE

Frontiers of Engineering Management 2021, Volume 8, Issue 1,   Pages 148-150 doi: 10.1007/s42524-020-0149-6

HTML PDF Collect

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Based 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: Second, the series of DO, water temperature, salinity, and oxygen saturation are decomposed adaptivelyinto 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 islands

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

HTML PDF Collect

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    

HTML PDF Collect

Title Author Date Type Operation

Decreasing complexity of glucose time series derived from continuous glucose monitoring is correlatedwith deteriorating glucose regulation

Journal Article

Analyzing construction safety through time series methods

Houchen CAO, Yang Miang GOH

Journal Article

General expression for linear and nonlinear time series models

Ren HUANG, Feiyun XU, Ruwen CHEN

Journal Article

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

Li-ming YANG,Wei ZHANG,Yun-fang 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

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

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

Li Xuejun,Bin Guangfu,Wang Yuqing

Journal Article

Anti-biofouling strategies for implantable biosensors of continuous glucose monitoring systems

Journal Article

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

Journal Article

decorated with polypyrrole and nickel-cobalt layered double hydroxide for high-performance nonenzymatic glucose

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

Managing stakeholder dynamics and complexity in mega infrastructure projects

Geoffrey Qiping SHEN, Jin XUE

Journal Article

A Hybrid Neural Network Model for Marine Dissolved Oxygen Concentrations Time-Series Forecasting Based

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