Resource Type

Journal Article 800

Year

2023 84

2022 74

2021 62

2020 51

2019 43

2018 43

2017 55

2016 36

2015 26

2014 29

2013 28

2012 20

2011 26

2010 32

2009 42

2008 37

2007 34

2006 16

2005 9

2004 5

open ︾

Keywords

prediction 20

performance 17

performance evaluation 11

Machine learning 7

seismic performance 7

different 5

machine learning 5

optimization 5

artificial neural network 4

earthquake prediction 4

life prediction 4

ANOVA 3

Artificial intelligence 3

electrochemical performance 3

reliability prediction 3

ANFIS 2

ANN 2

Anammox 2

Artificial neural network 2

open ︾

Search scope:

排序： Display mode:

Simultaneous removal of NO and chlorobenzene on VO/TiO granular catalyst: Kinetic study and performanceprediction

Frontiers of Environmental Science & Engineering 2021, Volume 15, Issue 4, doi: 10.1007/s11783-020-1363-5

Abstract:

• A V2O5/TiO2 granular catalyst for simultaneous removal of NO and chlorobenzene.

Keywords： NOx     Chlorobenzene     Simultaneous removal     Kinetic study     Performance prediction     V<    

HTML PDF Collect

A control scheme with performance prediction for a PV fed water pumping system

Ramesh K GOVINDARAJAN,Pankaj Raghav PARTHASARATHY,Saravana Ilango GANESAN

Frontiers in Energy 2014, Volume 8, Issue 4,   Pages 480-489 doi: 10.1007/s11708-014-0334-6

Abstract: This paper focuses on modeling and performance predetermination of a photovoltaic (PV) system with a

Keywords： photovoltaic system     boost converter     maximum power point tracking (MPPT)     DC permanent-magnet motor     centrifugal pump    

HTML PDF Collect

Optimization and performance prediction of a new near-zero emission coal utilization system with combined

GUAN Jian, WANG Qinhui, LI Xiaomin, LUO Zhongyang, CEN Kefa

Frontiers in Energy 2007, Volume 1, Issue 1,   Pages 113-119 doi: 10.1007/s11708-007-0013-y

Abstract: After taking into consideration the influence of the pressure and carbon conversion ratio on the performance

Keywords： influence     efficiency calculation     optimum     software FactSage     transport    

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: This paper presents the complete mathematical model and predicts the performance of switched reluctanceThe simulation is performed to choose the control parameters and study the performance of switched reluctance

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

HTML PDF Collect

Prediction of performance, combustion and emission characteristics of diesel-thermal cracked cashew nut

Arunachalam VELMURUGAN,Marimuthu LOGANATHAN,E. James GUNASEKARAN

Frontiers in Energy 2016, Volume 10, Issue 1,   Pages 114-124 doi: 10.1007/s11708-016-0394-x

Abstract: This paper explores the use of artificial neural networks (ANN) to predict performance, combustion andThus the developed ANN model is fairly powerful for predicting the performance, combustion and exhaust

Keywords： cashew nut shell liquid (CNSL)     artificial neural networks (ANN)     thermal cracking     mean square error (MSE)    

HTML PDF Collect

An efficient prediction framework for multi-parametric yield analysis under parameter variations Article

Xin LI,Jin SUN,Fu XIAO

Frontiers of Information Technology & Electronic Engineering 2016, Volume 17, Issue 12,   Pages 1344-1359 doi: 10.1631/FITEE.1601225

Abstract: Previous algorithms on parametric yield prediction are limited to predicting a single-parametric yieldIn this paper we suggest an efficient multi-parametric yield prediction framework, in which multipleperformance metrics are considered as simultaneous constraint conditions for parametric yield predictionyield prediction problem, and to generate an accurate yield estimate.limits, or a multi-parametric yield surface under all ranges of performance limits.

Keywords： Yield prediction     Parameter variations     Multi-parametric yield     Performance modeling     Sparse representation    

HTML PDF Collect

Universal Method for the Prediction of Abrasive Waterjet Performance in Mining

Eugene Averin

Engineering 2017, Volume 3, Issue 6,   Pages 888-891 doi: 10.1016/j.eng.2017.12.004

Abstract:

Abrasive waterjets (AWJs) can be used in extreme mining conditions for hard rock destruction, due to their ability to effectively cut difficult-to-machine materials with an absence of dust formation. They can also be used for explosion, intrinsic, and fire safety. Every destructible material can be considered as either ductile or brittle in terms of its fracture mechanics. Thus, there is a need for a method to predict the efficiency of cutting with AWJs that is highly accurate irrespective of material. This problem can be solved using the energy conservation approach, which states the proportionality between the material removal volume and the kinetic energy of AWJs. This paper describes a method based on this approach, along with recommendations on reaching the most effective level of destruction. Recommendations are provided regarding rational ranges of values for the relation of abrasive flow rate to water flow rate, standoff distance, and size of abrasive particles. I also provide a parameter to establish the threshold conditions for a material’s destruction initiation based on the temporary-structural approach of fracture mechanics.

Keywords： Abrasive waterjet     Energy conservation approach     Depth of cut     Fracture mechanics     Threshold velocity     Mining    

HTML PDF Collect

Research on Active Handoff Mechanism in Micro-Mobility Protocols

Zhao Aqun

Strategic Study of CAE 2004, Volume 6, Issue 8,   Pages 50-56

Abstract: This mechanism takes advantage of mobility prediction technique to predict the next cell a mobile hostTo guarantee the implementation of active handoff mechanism, a mobility prediction algorithm is proposedThe performance of active handoff mechanism is evaluated through theoretical analysis and system simulationThe result shows that active handoff mechanism obtains considerable performance improvement with less

Keywords： micro-mobility protocols     active handoff mechanism     mobility prediction     performance evaluation    

HTML PDF Collect

Spatial prediction of soil contamination based on machine learning: a review

Frontiers of Environmental Science & Engineering 2023, Volume 17, Issue 8, doi: 10.1007/s11783-023-1693-1

Abstract:

● A review of machine learning (ML) for spatial prediction of soil

Keywords： Soil contamination     Machine learning     Prediction     Spatial distribution    

HTML PDF Collect

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Frontiers of Medicine 2022, Volume 16, Issue 3,   Pages 496-506 doi: 10.1007/s11684-021-0828-7

Abstract: The fracture risk of patients with diabetes is higher than those of patients without diabetes due to hyperglycemia, usage of diabetes drugs, changes in insulin levels, and excretion, and this risk begins as early as adolescence. Many factors including demographic data (such as age, height, weight, and gender), medical history (such as smoking, drinking, and menopause), and examination (such as bone mineral density, blood routine, and urine routine) may be related to bone metabolism in patients with diabetes. However, most of the existing methods are qualitative assessments and do not consider the interactions of the physiological factors of humans. In addition, the fracture risk of patients with diabetes and osteoporosis has not been further studied previously. In this paper, a hybrid model combining XGBoost with deep neural network is used to predict the fracture risk of patients with diabetes and osteoporosis, and investigate the effect of patients’ physiological factors on fracture risk. A total of 147 raw input features are considered in our model. The presented model is compared with several benchmarks based on various metrics to prove its effectiveness. Moreover, the top 18 influencing factors of fracture risks of patients with diabetes are determined.

Keywords： XGBoost     deep neural network     healthcare     risk prediction    

HTML PDF Collect

Position-varying surface roughness prediction method considering compensated acceleration in milling

Frontiers of Mechanical Engineering 2021, Volume 16, Issue 4,   Pages 855-867 doi: 10.1007/s11465-021-0649-z

Abstract: Machined surface roughness will affect parts’ service performance.Aiming at surface roughness prediction in the machining process, this paper proposes a position-varyingsurface roughness prediction method based on compensated acceleration by using regression analysis.i>R-square proving the effectiveness of the filtering features, is selected as the input of the predictionMoreover, the prediction curve matches and agrees well with the actual surface state, which verifies

Keywords： surface roughness prediction     compensated acceleration     milling     thin-walled workpiece    

HTML PDF Collect

Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Frontiers of Structural and Civil Engineering doi: 10.1007/s11709-023-0961-2

Abstract: Deep excavations in dense urban areas have caused damage to nearby existing structures in numerous past construction cases. Proper assessment is crucial in the initial design stages. This study develops equations to predict the existing pile bending moment and deflection produced by adjacent braced excavations. Influential parameters (i.e., the excavation geometry, diaphragm wall thickness, pile geometry, strength and small-strain stiffness of the soil, and soft clay thickness) were considered and employed in the developed equations. It is practically unfeasible to obtain measurement data; hence, artificial data for the bending moment and deflection of existing piles were produced from well-calibrated numerical analyses of hypothetical cases, using the three-dimensional finite element method. The developed equations were established through a multiple linear regression analysis of the artificial data, using the transformation technique. In addition, the three-dimensional nature of the excavation work was characterized by considering the excavation corner effect, using the plane strain ratio parameter. The estimation results of the developed equations can provide satisfactory pile bending moment and deflection data and are more accurate than those found in previous studies.

Keywords： pile responses     excavation     prediction     deflection     bending moments    

HTML PDF Collect

Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

Frontiers in Energy 2016, Volume 10, Issue 4,   Pages 479-488 doi: 10.1007/s11708-016-0425-7

Abstract: In this paper a novel method for reliability prediction and validation of nuclear power units in serviceThe accuracy of the reliability prediction can be evaluated according to the comparison between the predictedFurthermore, the reliability prediction method is validated using the nuclear power units in North American

Keywords： nuclear power units in service     reliability     reliability prediction     equivalent availability factors    

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 the

Keywords： water injection units     condition-based maintenance     trend prediction    

HTML PDF Collect

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Frontiers of Structural and Civil Engineering   Pages 994-1010 doi: 10.1007/s11709-023-0942-5

Abstract: Developing prediction models to support drivers in performing rectifications in advance can effectivelysubsequently, they are preprocessed and used to establish GRU-based multivariate multistep-ahead direct predictionTo verify the performance of the proposed framework, a case study of a large pipe-jacking project inIn addition, the effects of the activation function and input time-step length on the prediction performance

Keywords： dynamic prediction     moving trajectory     pipe jacking     GRU     deep learning    

HTML PDF Collect

Title Author Date Type Operation

Simultaneous removal of NO and chlorobenzene on VO/TiO granular catalyst: Kinetic study and performanceprediction

Journal Article

A control scheme with performance prediction for a PV fed water pumping system

Ramesh K GOVINDARAJAN,Pankaj Raghav PARTHASARATHY,Saravana Ilango GANESAN

Journal Article

Optimization and performance prediction of a new near-zero emission coal utilization system with combined

GUAN Jian, WANG Qinhui, LI Xiaomin, LUO Zhongyang, CEN Kefa

Journal Article

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

Jyoti KOUJALAGI, B. UMAMAHESWARI, R. ARUMUGAM

Journal Article

Prediction of performance, combustion and emission characteristics of diesel-thermal cracked cashew nut

Arunachalam VELMURUGAN,Marimuthu LOGANATHAN,E. James GUNASEKARAN

Journal Article

An efficient prediction framework for multi-parametric yield analysis under parameter variations

Xin LI,Jin SUN,Fu XIAO

Journal Article

Universal Method for the Prediction of Abrasive Waterjet Performance in Mining

Eugene Averin

Journal Article

Research on Active Handoff Mechanism in Micro-Mobility Protocols

Zhao Aqun

Journal Article

Spatial prediction of soil contamination based on machine learning: a review

Journal Article

Hybrid deep learning model for risk prediction of fracture in patients with diabetes and osteoporosis

Journal Article

Position-varying surface roughness prediction method considering compensated acceleration in milling

Journal Article

Improved prediction of pile bending moment and deflection due to adjacent braced excavation

Journal Article

Reliability prediction and its validation for nuclear power units in service

Jinyuan SHI,Yong WANG

Journal Article

Trend prediction technology of condition maintenance for large water injection units

Xiaoli XU, Sanpeng DENG

Journal Article

Dynamic prediction of moving trajectory in pipe jacking: GRU-based deep learning framework

Journal Article