Resource Type

Journal Article 992

Conference Videos 25

Year

2024 42

2023 111

2022 96

2021 93

2020 85

2019 65

2018 59

2017 66

2016 35

2015 37

2014 27

2013 21

2012 21

2011 28

2010 24

2009 29

2008 27

2007 34

2006 17

2005 22

open ︾

Keywords

neural network 34

artificial neural network 22

Deep learning 13

convolutional neural network 12

Neural network 11

optimization 11

Artificial intelligence 10

genetic algorithm 10

network 10

neural networks 7

Machine learning 6

artificial neural network (ANN) 6

finite element method 6

shape memory alloy 6

concrete 5

development strategy 5

machine learning 5

China 4

control 4

open ︾

Search scope:

排序: Display mode:

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 2, doi: 10.1007/s11783-023-1622-3

Abstract:

● A novel deep learning framework for short-term water demand forecasting

Keywords: Short-term water demand forecasting     Long-short term memory neural network     Convolutional Neural Network    

A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 7, doi: 10.1007/s11783-023-1688-y

Abstract:

● A novel VMD-IGOA-LSTM model has proposed for the prediction of water quality.

Keywords: Water quality prediction     Grasshopper optimization algorithm     Variational mode decomposition     Long short-termmemory neural network    

LDformer: a parallel neural network model for long-term power forecasting

田冉,李新梅,马忠彧,刘颜星,王晶霞,王楚

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1287-1301 doi: 10.1631/FITEE.2200540

Abstract: Accurate long-term power forecasting is important in the decision-making operation of the power gridHowever, most time-series forecasting models do not perform well in dealing with long-time-series predictionFirst, we combine Informer with long short-term memory (LSTM) to obtain deep representation abilitiesLDformer outperforms the state-of-the-art methods for most of the cases when handling the different long-time-series

Keywords: Long-term power forecasting     Long short-term memory (LSTM)     UniDrop     Self-attention mechanism    

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

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: Based on this, a short-term forecasting chaos neural network model of WWTP influent quantity was built

Keywords: nonlinear     reconstruction     WWTP influent     characteristic     Reasonable forecasting    

Gradient boosting dendritic network for ultra-short-term PV power prediction

Frontiers in Energy doi: 10.1007/s11708-024-0915-y

Abstract: achieve effective intraday dispatch of photovoltaic (PV) power generation systems, a reliable ultra-short-termBased on a gradient boosting strategy and a dendritic network, this paper proposes a novel ensemble predictionmodel, named gradient boosting dendritic network (GBDD) model which can reduce the forecast error by

Keywords: photovoltaic (PV) power prediction     dendrite network     gradient boosting strategy    

Short-term Load Forecasting Using Neural Network

Luo Mei

Strategic Study of CAE 2007, Volume 9, Issue 5,   Pages 77-80

Abstract: three BP ANN models,  namely SDBP, LMBP and BRBP Model,  are established to carry out the short-termminimizing the optimized function,  an optimized L-M algorithm, which can accelerate the training of neuralnetwork and improve the stability of the convergence,  should be applied to forecast to reduce

Keywords: short-term load forecasting(STLF)     ANN     Levenberg-Marquardt     Bayesian regularization     optimized algorithms    

Exploring nonlinear spatiotemporal effects for personalized next point-of-interest recommendation

孙曦,吕志民

Frontiers of Information Technology & Electronic Engineering 2023, Volume 24, Issue 9,   Pages 1273-1286 doi: 10.1631/FITEE.2200304

Abstract: State-of-the-art studies linearly discretize the user’s spatiotemporal information and then use recurrent neuralnetwork (RNN) based models for modeling.We use the long short-term memory (LSTM) model with an attention mechanism as the basic framework and

Keywords: Point-of-interest recommendation     Spatiotemporal effects     Long short-term memory (LSTM)     Attention mechanism    

Intelligent Forecasting Mode and Approach of Mid and Long Term Intelligent Hydrological Forecasting

Chen Shouyu,Guo Yu,Wang Dagang

Strategic Study of CAE 2006, Volume 8, Issue 7,   Pages 30-35

Abstract:

Intelligent calculating tools such as fuzzy optimization approaches, BP neural network and geneticapproaches, and then, in this paper, the author organically synthesizes fuzzy optimal selection, BP neuralnetwork and genetic algorithm and establishes intelligent forecasting mode and method.When illustrating the method by an application to forecast mid and long term hydrological process ofnetwork to train link-weights, and finally, uses gained link-weight values to verify forecasting.

Keywords: fuzzy optimal selection     BP neural network     genetic algorithm     intelligent forecasting mode     mid and longterm intelligent hydrological forecasting    

NIPAD: a non-invasive power-based anomaly detection scheme for programmable logic controllers Article

Yu-jun XIAO, Wen-yuan XU, Zhen-hua JIA, Zhuo-ran MA, Dong-lian QI

Frontiers of Information Technology & Electronic Engineering 2017, Volume 18, Issue 4,   Pages 519-534 doi: 10.1631/FITEE.1601540

Abstract: power measurements, we extract a discriminative feature set from the power trace, and then train a longshort-term memory (LSTM) neural network with the features of normal samples to predict the next time

Keywords: Industrial control system     Programmable logic controller     Side-channel     Anomaly detection     Long short-termmemory neural networks    

Anlotinib as third- or further-line therapy for short-term relapsed small-cell lung cancer: subgroup

Frontiers of Medicine 2022, Volume 16, Issue 5,   Pages 766-772 doi: 10.1007/s11684-021-0916-8

Abstract: investigate the efficacy and safety of anlotinib as third- or further-line therapy in patients with short-termPatients with short-term relapsed SCLC (disease progression within 3 months after completing ≥ two linesFor patients with short-term relapsed SCLC, third- or further-line anlotinib treatment was associated

Keywords: anlotinib     chemotherapy     short-term relapsed     small-cell lung cancer    

Frontier of continuous structural health monitoring system for short & medium span bridges and condition

Ayaho MIYAMOTO, Risto KIVILUOMA, Akito YABE

Frontiers of Structural and Civil Engineering 2019, Volume 13, Issue 3,   Pages 569-604 doi: 10.1007/s11709-018-0498-y

Abstract: It is becoming an important social problem to make maintenance and rehabilitation of existing short andmedium span(10-20 m) bridges because there are a huge amount of short and medium span bridges in servicestructural health monitoring systems are described to review and analyse the potential of utilizing the longterm health monitoring in safety assessment and management issues for short and medium span bridge.The second is a long term health monitoring method by using the public buses as part of a public transit

Keywords: condition assessment     short & medium span bridge     structural health monitoring(SHM)     long-term data collection    

Response of bacterial communities to short-term pyrene exposure in red soil

Jingjing PENG, Hong LI, Jianqiang SU, Qiufang ZHANG, Junpeng RUI, Chao CAI

Frontiers of Environmental Science & Engineering 2013, Volume 7, Issue 4,   Pages 559-567 doi: 10.1007/s11783-013-0501-8

Abstract: However, long-term exposure studies did not detect any significant effects of pyrene on soil microorganismIn this study, short-term microcosm experiments were conducted to identify the immediate effect of pyreneShort-term exposure to pyrene resulted in dominance of Proteobacteria in soil, followed by Acidobacteria

Keywords: pyrene     bacterial communities     terminal restriction fragment length polymorphism     short-term exposure     rank-abundance    

Enhanced LSTM Model for Daily Runoff Prediction in the Upper Huai River Basin, China Article

Yuanyuan Man, Qinli Yang, Junming Shao, Guoqing Wang, Linlong Bai, Yunhong Xue

Engineering 2023, Volume 24, Issue 5,   Pages 230-239 doi: 10.1016/j.eng.2021.12.022

Abstract: To address this issue, this study proposes an enhanced long short-term memory (LSTM) model for runoffWater Balance Model (AWBM), Sacramento, SimHyd and Tank Model) and the data-driven models (artificial neuralnetwork (ANN), support vector regression (SVR), and gated recurrent units (GRU)).

Keywords: Runoff prediction     Long short-term memory     Upper Huai River Basin     Extreme runoff     Loss function    

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: Overcharging is an important safety issue in the charging process of electric vehicle power batteries, and can easily lead to accelerated battery aging and serious safety accidents. It is necessary to accurately predict the vehicle's to effectively prevent the battery from overcharging. Due to the complex structure of the battery pack and various s, the traditional prediction method often encounters modeling difficulties and low accuracy. In response to the above problems, data drivers and machine learning theories are applied. On the basis of fully considering the different electric vehicle battery management system (BMS) s, a prediction method with recognition is proposed. First, an intelligent algorithm based on dynamic weighted density peak clustering (DWDPC) and fusion is proposed to classify vehicle s. Then, on the basis of an improved simplified particle swarm optimization (ISPSO) algorithm, a high-performance prediction method is constructed by fully integrating and a strong tracking filter. Finally, the data run by the actual engineering system are verified for the proposed prediction algorithm. Experimental results show that the new method can effectively distinguish the s of different vehicles, identify the charging characteristics of different electric vehicles, and achieve high prediction accuracy.

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

distal pancreatectomy versus conventional laparoscopic distal pancreatectomy: a comparative study for short-term

Eric C. H. Lai,Chung Ngai Tang

Frontiers of Medicine 2015, Volume 9, Issue 3,   Pages 356-360 doi: 10.1007/s11684-015-0404-0

Abstract:

Robotic system has been increasingly used in pancreatectomy. However, the effectiveness of this method remains uncertain. This study compared the surgical outcomes between robot-assisted laparoscopic distal pancreatectomy and conventional laparoscopic distal pancreatectomy. During a 15-year period, 35 patients underwent minimally invasive approach of distal pancreatectomy in our center. Seventeen of these patients had robot-assisted laparoscopic approach, and the remaining 18 had conventional laparoscopic approach. Their operative parameters and perioperative outcomes were analyzed retrospectively in a prospective database. The mean operating time in the robotic group (221.4 min) was significantly longer than that in the laparoscopic group (173.6 min) (P = 0.026). Both robotic and conventional laparoscopic groups presented no significant difference in spleen-preservation rate (52.9% vs. 38.9%) (P = 0.505), operative blood loss (100.3 ml vs. 268.3 ml) (P = 0.29), overall morbidity rate (47.1% vs. 38.9%) (P = 0.73), and post-operative hospital stay (11.4 days vs. 14.2 days) (P = 0.46). Both groups also showed no perioperative mortality. Similar outcomes were observed in robotic distal pancreatectomy and conventional laparoscopic approach. However, robotic approach tended to have the advantages of less blood loss and shorter hospital stay. Further studies are necessary to determine the clinical position of robotic distal pancreatectomy.

Keywords: distal pancreatectomy     pancreatic neoplasm     robotic surgery    

Title Author Date Type Operation

A hybrid Wavelet-CNN-LSTM deep learning model for short-term urban water demand forecasting

Journal Article

A novel hybrid model for water quality prediction based on VMD and IGOA optimized for LSTM

Journal Article

LDformer: a parallel neural network model for long-term power forecasting

田冉,李新梅,马忠彧,刘颜星,王晶霞,王楚

Journal Article

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

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

Journal Article

Gradient boosting dendritic network for ultra-short-term PV power prediction

Journal Article

Short-term Load Forecasting Using Neural Network

Luo Mei

Journal Article

Exploring nonlinear spatiotemporal effects for personalized next point-of-interest recommendation

孙曦,吕志民

Journal Article

Intelligent Forecasting Mode and Approach of Mid and Long Term Intelligent Hydrological Forecasting

Chen Shouyu,Guo Yu,Wang Dagang

Journal Article

NIPAD: a non-invasive power-based anomaly detection scheme for programmable logic controllers

Yu-jun XIAO, Wen-yuan XU, Zhen-hua JIA, Zhuo-ran MA, Dong-lian QI

Journal Article

Anlotinib as third- or further-line therapy for short-term relapsed small-cell lung cancer: subgroup

Journal Article

Frontier of continuous structural health monitoring system for short & medium span bridges and condition

Ayaho MIYAMOTO, Risto KIVILUOMA, Akito YABE

Journal Article

Response of bacterial communities to short-term pyrene exposure in red soil

Jingjing PENG, Hong LI, Jianqiang SU, Qiufang ZHANG, Junpeng RUI, Chao CAI

Journal Article

Enhanced LSTM Model for Daily Runoff Prediction in the Upper Huai River Basin, China

Yuanyuan Man, Qinli Yang, Junming Shao, Guoqing Wang, Linlong Bai, Yunhong Xue

Journal Article

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

Chunxi LI, Yingying FU, Xiangke CUI, Quanbo GE

Journal Article

distal pancreatectomy versus conventional laparoscopic distal pancreatectomy: a comparative study for short-term

Eric C. H. Lai,Chung Ngai Tang

Journal Article