Resource Type

Journal Article 616

Year

2023 47

2022 47

2021 50

2020 49

2019 35

2018 33

2017 43

2016 27

2015 22

2014 11

2013 27

2012 16

2011 28

2010 21

2009 26

2008 19

2007 26

2006 22

2005 11

2004 3

open ︾

Keywords

development trend 23

prediction 20

Machine learning 6

different 6

machine learning 6

Artificial intelligence 4

artificial neural network 4

earthquake prediction 4

life prediction 4

simulation 4

ANFIS 3

ANOVA 3

concrete 3

neural network 3

performance evaluation 3

reliability prediction 3

2035 2

ANN 2

Accelerated aging test 2

open ︾

Search scope:

排序： Display mode:

Trend detection and stochastic simulation prediction of streamflow at Yingluoxia hydrological station

Chenglong ZHANG,Mo LI,Ping GUO

Frontiers of Agricultural Science and Engineering 2017, Volume 4, Issue 1,   Pages 81-96 doi: 10.15302/J-FASE-2016112

Abstract: Investigating long-term variation and prediction of streamflow are critical to regional water resourceUnder the continuous influence of climate change and human activity, the trends of hydrologic time seriesThe results indicated there was a significant long-term increasing trend.simulate these stochastic components with normal distribution, and thus a new ensemble hydrological time

Keywords： Monte Carlo     nonstationary     trend detection     streamflow prediction     decomposition and ensemble     Yingluoxia    

HTML PDF Collect

Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

Frontiers of Mechanical Engineering 2010, Volume 5, Issue 2,   Pages 171-175 doi: 10.1007/s11465-009-0091-0

Abstract: Trend prediction technology is the key technology to achieve condition-based maintenance of mechanicalTo ensure the normal operation of units and save maintenance costs, trend prediction technology is studiedThe main methods of the technology are given, the trend prediction method based on neural network isThe industrial site verification shows that the proposed trend prediction technology can reflect theoperating condition trend change of the water injection units and provide technical means to achieve

Keywords： water injection units     condition-based maintenance     trend prediction    

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: , prediction, and knowledge discovery.In this paper, we propose a new symbolic representation method for long time series based on trend features, called trend feature symbolic approximation (TFSA).Unlike some previous symbolic methods, it focuses on retaining most of the trend features and patternsA 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

Physics-Informed Deep Learning-Based Real-Time Structural Response Prediction Method

Ying Zhou,Shiqiao Meng,Yujie Lou,Qingzhao Kong,

Engineering doi: 10.1016/j.eng.2023.08.011

Abstract: High-precision and efficient structural response prediction is essential for intelligent disaster preventionTo improve the accuracy and efficiency of structural response prediction, this study proposes a novelphysics-informed deep-learning-based real-time structural response prediction method that can predict, by conducting a comparative experiment, the impact of the range of seismic wave amplitudes on the prediction

Keywords： Structural seismic response prediction     Physics information informed     Real-time prediction     Earthquake engineering    

HTML PDF Collect

Allocation of grassland, livestock and arable based on the spatial and temporal analysis for food demand in China

Huilong LIN, Ruichao LI, Yifan LIU, Jingrong ZHANG, Jizhou REN

Frontiers of Agricultural Science and Engineering 2017, Volume 4, Issue 1,   Pages 69-80 doi: 10.15302/J-FASE-2017140

Abstract: To explore the distribution of food demand and the projected trend in future food demand in China, thisBased on the food demand and trend in the development of grassland agriculture, the 31 provinces in China

Keywords： arable land equivalent unit (ALEU)     food equivalent unit (FEU)     food security     grassland agriculture     timetrend prediction    

HTML PDF Collect

Performance prediction of switched reluctance generator with time average and small signal models

Jyoti KOUJALAGI, B. UMAMAHESWARI, R. ARUMUGAM

Frontiers in Energy 2013, Volume 7, Issue 1,   Pages 56-68 doi: 10.1007/s11708-012-0216-8

Abstract: the complete mathematical model and predicts the performance of switched reluctance generator with timeNext, based on the switching behaviour, a time average model is obtained to measure the difference betweenthe excitation and generation time in each switching cycle.

Keywords： generator     reluctance     switching model     small signal model     time average model    

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: Finally, the trend of fuzzy network evolution is analyzed and predicted with a fuzzy Markov chain.

Keywords： Time-series network     Fuzzy network     Fuzzy Markov chain    

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 assumption

Keywords： nonlinear     reconstruction     WWTP influent     characteristic     Reasonable forecasting    

HTML PDF Collect

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

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

Regional seismic-damage prediction of buildings under mainshock–aftershock sequence

Xinzheng LU, Qingle CHENG, Zhen XU, Chen XIONG

Frontiers of Engineering Management 2021, Volume 8, Issue 1,   Pages 122-134 doi: 10.1007/s42524-019-0072-x

Abstract: Thus, the accurate and efficient prediction of aftershock-induced damage to buildings on a regional scaleunder a mainshock–aftershock (MS–AS) sequence is proposed in this study based on city-scale nonlinear time-history

Keywords： regional seismic damage prediction     city-scale nonlinear time-history analysis     mainshock–aftershock sequence    

HTML PDF Collect

Short-term prediction of influent flow rate and ammonia concentration in municipal wastewater treatment

Shuai MA, Siyu ZENG, Xin DONG, Jining CHEN, Gustaf OLSSON

Frontiers of Environmental Science & Engineering 2014, Volume 8, Issue 1,   Pages 128-136 doi: 10.1007/s11783-013-0598-9

Abstract: The prediction of the influent load is of great importance for the improvement of the control systemreconstruction; 2) typical cycle identification using power spectrum density analysis; 3) fitting and predictionTo give meaningful information for feedforward control systems, predictions in different time scalesof the rainfalls, a linear fitting model is derived to estimate the relationship between flow rate trendaccuracy is not distinct with increasing of the prediction time scales; 3) the periodicity influence

Keywords： influent load prediction     wavelet de-noising     power spectrum density     autoregressive model     time-frequency    

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-seriesAn electricity demand prediction model is developed for each device using the Auto-Regression eXogenousThe real-time SEMS data and time-series clustering to explore similarities in electricity consumptionThe resulting energy-prediction models can be used for low-carbon planning.

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

HTML PDF Collect

Tracking of safety hazards and real-time-prediction model of safety risks on construction sites

Wu Weiwei,Patrick T. I. LAM,Li Qiming,Michael C. H. YAM,David A. S. CHEW

Strategic Study of CAE 2010, Volume 12, Issue 3,   Pages 68-72

Abstract: ="text-align: justify;">This paper aims to explore the tracking approach of safety hazards and real-time-predictionConsequently, a schematic model of tracking safety hazards and real-time prediction of safety risks isThis study would provide a possible research approach on method for tracking safety hazards and real-timeprediction of safety risks, while serving as a foundation for further study by drawing researchers'

Keywords： construction sites     safety risks     real-time prediction     precursor signals     signal detection theory    

HTML PDF Collect

Innovation and Trend of Gears-Technology

Liang Guiming

Strategic Study of CAE 2000, Volume 2, Issue 3,   Pages 1-6

Abstract:

The trend of innovation of gears in the coming 50 years will be seeking miniaturization, puification

Keywords： gears     innovation     trend    

HTML PDF Collect

Dynamic time prediction for electric vehicle charging based on charging pattern recognition Research Article

Chunxi LI, Yingying FU, Xiangke CUI, Quanbo GE

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 2,   Pages 299-313 doi: 10.1631/FITEE.2200212

Abstract: Due to the complex structure of the battery pack and various s, the traditional prediction method oftenthe basis of fully considering the different electric vehicle battery management system (BMS) s, a predictionbasis of an improved simplified particle swarm optimization (ISPSO) algorithm, a high-performance predictionFinally, the data run by the actual engineering system are verified for the proposed prediction algorithmdifferent vehicles, identify the charging characteristics of different electric vehicles, and achieve high prediction

Keywords： Charging mode     Charging time     Random forest     Long short-term memory (LSTM)     Simplified particle swarm    

HTML PDF Collect

Title Author Date Type Operation

Trend detection and stochastic simulation prediction of streamflow at Yingluoxia hydrological station

Chenglong ZHANG,Mo LI,Ping GUO

Journal Article

Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

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

Physics-Informed Deep Learning-Based Real-Time Structural Response Prediction Method

Ying Zhou,Shiqiao Meng,Yujie Lou,Qingzhao Kong,

Journal Article

Allocation of grassland, livestock and arable based on the spatial and temporal analysis for food demand in China

Huilong LIN, Ruichao LI, Yifan LIU, Jingrong ZHANG, Jizhou REN

Journal Article

Performance prediction of switched reluctance generator with time average and small signal models

Jyoti KOUJALAGI, B. UMAMAHESWARI, R. ARUMUGAM

Journal Article

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

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

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

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

Journal Article

Regional seismic-damage prediction of buildings under mainshock–aftershock sequence

Xinzheng LU, Qingle CHENG, Zhen XU, Chen XIONG

Journal Article

Short-term prediction of influent flow rate and ammonia concentration in municipal wastewater treatment

Shuai MA, Siyu ZENG, Xin DONG, Jining CHEN, Gustaf OLSSON

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

Tracking of safety hazards and real-time-prediction model of safety risks on construction sites

Wu Weiwei,Patrick T. I. LAM,Li Qiming,Michael C. H. YAM,David A. S. CHEW

Journal Article

Innovation and Trend of Gears-Technology

Liang Guiming

Journal Article

Dynamic time prediction for electric vehicle charging based on charging pattern recognition

Chunxi LI, Yingying FU, Xiangke CUI, Quanbo GE

Journal Article