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oblique load carrying capacity of batter pile groups using neural network, random forest regression and M5model tree

Tanvi SINGH, Mahesh PAL, V. K. ARORA

《结构与土木工程前沿（英文）》 2019年 第13卷 第3期   页码 674-685 doi: 10.1007/s11709-018-0505-3

摘要： M5 model tree, random forest regression (RF) and neural network (NN) based modelling approaches were used to predict oblique load carrying capacity of batter pile groups using 247 laboratory experiments with smooth and rough pile groups. Pile length ( ), angle of oblique load ( ), sand density ( ), number of batter piles ( ), and number of vertical piles ( ) as input and oblique load ( ) as output was used. Results suggest improved performance by RF regression for both pile groups. M5 model tree provides simple linear relation which can be used for the prediction of oblique load for field data also. Model developed using RF regression approach with smooth pile group data was found to be in good agreement for rough piles data. NN based approach was found performing equally well with both smooth and rough piles. Sensitivity analysis using all three modelling approaches suggest angle of oblique load ( ) and number of batter pile ( ) affect the oblique load capacity for both smooth and rough pile groups.

关键词： batter piles     oblique load test     neural network     M5 model tree     random forest regression     ANOVA    

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Estimation of flexible pavement structural capacity using machine learning techniques

Nader KARBALLAEEZADEH, Hosein GHASEMZADEH TEHRANI, Danial MOHAMMADZADEH SHADMEHRI, Shahaboddin SHAMSHIRBAND

《结构与土木工程前沿（英文）》 2020年 第14卷 第5期   页码 1083-1096 doi: 10.1007/s11709-020-0654-z

摘要： The most common index for representing structural condition of the pavement is the structural number. The current procedure for determining structural numbers involves utilizing falling weight deflectometer and ground-penetrating radar tests, recording pavement surface deflections, and analyzing recorded deflections by back-calculation manners. This procedure has two drawbacks: falling weight deflectometer and ground-penetrating radar are expensive tests; back-calculation ways has some inherent shortcomings compared to exact methods as they adopt a trial and error approach. In this study, three machine learning methods entitled Gaussian process regression, M5P model tree, and random forest used for the prediction of structural numbers in flexible pavements. Dataset of this paper is related to 759 flexible pavement sections at Semnan and Khuzestan provinces in Iran and includes “structural number” as output and “surface deflections and surface temperature” as inputs. The accuracy of results was examined based on three criteria of , , and . Among the methods employed in this paper, random forest is the most accurate as it yields the best values for above criteria ( =0.841, =0.592, and =0.760). The proposed method does not require to use ground penetrating radar test, which in turn reduce costs and work difficulty. Using machine learning methods instead of back-calculation improves the calculation process quality and accuracy.

关键词： transportation infrastructure     flexible pavement     structural number prediction     Gaussian process regression     M5P model tree     random forest    

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Fast and catalytic pyrolysis of xylan: Effects of temperature and M/HZSM-5 (M= Fe, Zn) catalysts on pyrolytic

Xifeng ZHU, Qiang LU, Wenzhi LI, Dong ZHANG,

《能源前沿（英文）》 2010年 第4卷 第3期   页码 424-429 doi: 10.1007/s11708-010-0015-z

摘要： Pyrolysis-gas chromatography/mass spectrometry (Py-GC/MS) was employed to achieve fast pyrolysis of xylan and on-line analysis of pyrolysis vapors. Tests were conducted to investigate the effects of temperature on pyrolytic products, and to reveal the effect of HZSM-5 and M/HZSM-5 (M= Fe, Zn) zeolites on pyrolysis vapors. The results showed that the total yield of pyrolytic products first increased and then decreased with the increase of temperature from 350°C to 900°C. The pyrolytic products were complex, and the most abundant products included hydroxyacetaldehyde, acetic acid, 1-hydroxy-2-propanone, 1-hydroxy-2-butanone and furfural. Catalytic cracking of pyrolysis vapors with HZSM-5 and M/HZSM-5 (M= Fe, Zn) catalysts significantly altered the product distribution. Oxygen-containing compounds were reduced considerably, and meanwhile, a lot of hydrocarbons, mainly toluene and xylenes, were formed. M/HZSM-5 catalysts were more effective than HZSM-5 in reducing the oxygen-containing compounds, and therefore, they helped to produce higher contents of hydrocarbons than HZSM-5.

关键词： xylan     fast pyrolysis     catalytic pyrolysis     Py-GC/MS     HZSM-5    

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Heuristic solution using decision tree model for enhanced XML schema matching of bridge structural calculation

Sang I. PARK, Sang-Ho LEE

《结构与土木工程前沿（英文）》 2020年 第14卷 第6期   页码 1403-1417 doi: 10.1007/s11709-020-0666-8

摘要： Research on the quality of data in a structural calculation document (SCD) is lacking, although the SCD of a bridge is used as an essential reference during the entire lifecycle of the facility. XML Schema matching enables qualitative improvement of the stored data. This study aimed to enhance the applicability of XML Schema matching, which improves the speed and quality of information stored in bridge SCDs. First, the authors proposed a method of reducing the computing time for the schema matching of bridge SCDs. The computing speed of schema matching was increased by 13 to 1800 times by reducing the checking process of the correlations. Second, the authors developed a heuristic solution for selecting the optimal weight factors used in the matching process to maintain a high accuracy by introducing a decision tree. The decision tree model was built using the content elements stored in the SCD, design companies, bridge types, and weight factors as input variables, and the matching accuracy as the target variable. The inverse-calculation method was applied to extract the weight factors from the decision tree model for high-accuracy schema matching results.

关键词： structural calculation document     bridge structure     XML Schema matching     weight factor     data mining     decision tree model    

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An innovative model for predicting the displacement and rotation of column-tree moment connection under

Mohammad Ali NAGHSH, Aydin SHISHEGARAN, Behnam KARAMI, Timon RABCZUK, Arshia SHISHEGARAN, Hamed TAGHAVIZADEH, Mehdi MORADI

《结构与土木工程前沿（英文）》 2021年 第15卷 第1期   页码 194-212 doi: 10.1007/s11709-020-0688-2

摘要： In this study, we carried out nonlinear finite element simulations to predict the performance of a column-tree moment connection (CTMC) under fire and static loads. We also conducted a detailed parameter study based on five input variables, including the applied temperature, number of flange bolts, number of web bolts, length of the beam, and applied static loads. The first variable is changed among seven levels, whereas the other variables are changed among three levels. Employing the Taguchi method for variables 2–5 and their levels, 9 samples were designed for the parameter study, where each sample was exposed to 7 different temperatures yielding 63 outputs. The related variables for each output are imported for the training and testing of different surrogate models. These surrogate models include a multiple linear regression (MLR), multiple Ln equation regression (MLnER), an adaptive network-based fuzzy inference system (ANFIS), and gene expression programming (GEP). 44 samples were used for training randomly while the remaining samples were employed for testing. We show that GEP outperforms MLR, MLnER, and ANFIS. The results indicate that the rotation and deflection of the CTMC depend on the temperature. In addition, the fire resistance increases with a decrease in the beam length; thus, a shorter beam can increase the fire resistance of the building. The numbers of flanges and web bolts slightly affect the rotation and displacement of the CTMCs at temperatures of above 400°C.

关键词： column-tree moment connection     Finite element model     parametric study     fire     regression models     gene expression programming    

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Four-protein model for predicting prognostic risk of lung cancer

《医学前沿（英文）》 2022年 第16卷 第4期   页码 618-626 doi: 10.1007/s11684-021-0867-0

摘要： Patients with lung cancer at the same stage may have markedly different overall outcome and a lack of specific biomarker to predict lung cancer outcome. Heat-shock protein 90 β (HSP90β) is overexpressed in various tumor cells. In this study, the ELISA results of HSP90β combined with CEA, CA125, and CYFRA21-1 were used to construct a recursive partitioning decision tree model to establish a four-protein diagnostic model and predict the survival of patients with lung cancer. Survival analysis showed that the recursive partitioning decision tree could distinguish the prognosis between high- and low-risk groups. Results suggested that the joint detection of HSP90β, CEA, CA125, and CYFRA21-1 in the peripheral blood of patients with lung cancer is plausible for early diagnosis and prognosis prediction of lung cancer.

关键词： lung cancer     HSP90β     decision tree model     prognosis    

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Development of machine learning multi-city model for municipal solid waste generation prediction

《环境科学与工程前沿（英文）》 2022年 第16卷 第9期 doi: 10.1007/s11783-022-1551-6

摘要：

● A database of municipal solid waste (MSW) generation in China was established.

关键词： Municipal solid waste     Machine learning     Multi-cities     Gradient boost regression tree    

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Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

Ahmet SAYAR,Süleyman EKEN,Okan ÖZTÜRK

《信息与电子工程前沿（英文）》 2015年 第16卷 第2期   页码 98-108 doi: 10.1631/FITEE.1400165

摘要： We present a study to show the possibility of using two well-known space partitioning and indexing techniques, kd trees and quad trees, in declustering applications to increase input/output (I/O) parallelization and reduce spatial data processing times. This parallelization enables time-consuming computational geometry algorithms to be applied efficiently to big spatial data rendering and querying. The key challenge is how to balance the spatial processing load across a large number of worker nodes, given significant performance heterogeneity in nodes and processing skews in the workload.

关键词： Kd tree     Quad tree     Space partitioning     Spatial indexing     Range queries     Query optimization    

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Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

《机械工程前沿（英文）》 2021年 第16卷 第4期   页码 814-828 doi: 10.1007/s11465-021-0650-6

摘要： The fault diagnosis of bearings is crucial in ensuring the reliability of rotating machinery. Deep neural networks have provided unprecedented opportunities to condition monitoring from a new perspective due to the powerful ability in learning fault-related knowledge. However, the inexplicability and low generalization ability of fault diagnosis models still bar them from the application. To address this issue, this paper explores a decision-tree-structured neural network, that is, the deep convolutional tree-inspired network (DCTN), for the hierarchical fault diagnosis of bearings. The proposed model effectively integrates the advantages of convolutional neural network (CNN) and decision tree methods by rebuilding the output decision layer of CNN according to the hierarchical structural characteristics of the decision tree, which is by no means a simple combination of the two models. The proposed DCTN model has unique advantages in 1) the hierarchical structure that can support more accuracy and comprehensive fault diagnosis, 2) the better interpretability of the model output with hierarchical decision making, and 3) more powerful generalization capabilities for the samples across fault severities. The multiclass fault diagnosis case and cross-severity fault diagnosis case are executed on a multicondition aeronautical bearing test rig. Experimental results can fully demonstrate the feasibility and superiority of the proposed method.

关键词： bearing     cross-severity fault diagnosis     hierarchical fault diagnosis     convolutional neural network     decision tree    

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Catalytic hydrogenation of insoluble organic matter of CS/Acetone from coal over mesoporous HZSM-5 supported

《化学科学与工程前沿（英文）》 2022年 第16卷 第10期   页码 1505-1513 doi: 10.1007/s11705-022-2164-0

摘要： Four supported catalysts, nickel and ruthenium on a HZSM-5 support, were prepared by equal volume impregnation and in-situ decomposition of carbonyl nickel. The properties of catalysts were investigated by catalytic hydro-conversion of 2,2′-dinaphthyl ether as the model compound and extraction residue of Naomaohu lignite as the sample under an initial H2 pressure of 5 MPa and temperature at 150 °C. According to the catalytic hydro-conversion results of the model compound, Ni−Ru/HZSM-5 exhibited the best catalytic performance. It not only activated H2 into H···H, but also further heterolytically split H···H into immobile H‒ attached on the acidic centers of Ni−Ru/HZSM-5 and relatively mobile H+. Catalytic hydro-conversion of the extraction residue from Naomaohu lignite was further examined over the optimized catalyst, Ni−Ru/HZSM-5. Detailed molecular compositions of products from the extraction residue with and without hydrogenation were characterized by Fourier transform infrared spectroscopy and gas chromatography/mass spectrometry. The analytical results showed that the oxygen-containing functional groups in products of hydrogenated extraction residue were obviously reduced after the catalytic treatment. The relative content of oxygenates in the product with catalytic treatment was 18.57% lower than that in the product without catalytic treatment.

关键词： HZSM-5     Ni-based catalyst     catalytic hydrogenation     coal     model compound    

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Core designing of a new type of TVS-2M FAs: neutronics and thermal-hydraulics design basis limits

Saeed GHAEMI, Farshad FAGHIHI

《能源前沿（英文）》 2021年 第15卷 第1期   页码 256-278 doi: 10.1007/s11708-018-0583-x

摘要： One of the most important aims of this study is to improve the core of the current VVER reactors to achieve more burn-up (or more cycle length) and more intrinsic safety. It is an independent study on the Russian new proposed FAs, called TVS-2M, which would be applied for the future advanced VVERs. Some important aspects of neutronics as well as thermal hydraulics investigations (and analysis) of the new type of Fas are conducted, and results are compared with the standards PWR CDBL. The TVS-2M FA contains gadolinium-oxide which is mixed with UO (for different Gd densities and U-235 enrichments which are given herein), but the core does not contain BARs. The new type TVS-2M Fas are modeled by the SARCS software package to find the PMAXS format for three states of CZP and HZP as well as HFP, and then the whole core is simulated by the PARCS code to investigate transient conditions. In addition, the WIMS-D5 code is suggested for steady core modeling including TVS-2M FAs and/or TVS FAs. Many neutronics aspects such as the first cycle length (first cycle burn up in terms of MW d/kgU), the critical concentration of boric acid at the BOC as well as the cycle length, the axial, and radial power peaking factors, differential and integral worthy of the most reactive CPS-CRs, reactivity coefficients of the fuel, moderator, boric acid, and the under-moderation estimation of the core are conducted and benchmarked with the PWR CDBL. Specifically, the burn-up calculations indicate that the 45.6 d increase of the first cycle length (which corresponds to 1.18 MW d/kgU increase of burn-up) is the best improving aim of the new FA type called TVS-2M. Moreover, thermal-hydraulics core design criteria such as MDNBR (based on W3 correlation) and the maximum of fuel and clad temperatures (radially and axially), are investigated, and discussed based on the CDBL.

关键词： TVS-2M FAs     core design basis limits     VVER-1000     analysis     mixture of uranium-gadolinium oxides fuels     thermal-hydraulics     PARCS     WIMS-D5    

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Oxidation-extraction desulfurization of model oil over Zr-ZSM-5/SBA-15 and kinetic study

Chuanzhu LU,Hui FU,Huipeng LI,Hua ZHAO,Tianfeng CAI

《化学科学与工程前沿（英文）》 2014年 第8卷 第2期   页码 203-211 doi: 10.1007/s11705-014-1420-3

摘要： ZSM-5/SBA-15 composite molecular sieves were synthesized using post-synthesis method and characterized by X-ray diffraction and N adsorption-desorption. The oxidative-extration desulfurization of model oil was investigated by using hydrogen peroxide as the oxidant, tetrabutyl ammonium bromide as phase transfer catalyst, dimethyl sulfoxide as extractant, and Zr-ZSM-5/SBA-15, Ag-ZSM-5/SBA-15, Ce-ZSM-5/SBA-15 as catalyst. Under the optimal conditions, the desulfurization rate decreases in the order: Zr-ZSM-5/SBA-15>Ce-ZSM-5/SBA-15>Ag-ZSM-5/SBA-15. The highest desulfurization rate is 84.53% under the catalysis of Zr-ZSM-5/SBA-15. Kinetics analysis shows that the reaction is pseudo-first-order with the activation energy of 44.23 kJ/mol.

关键词： composite molecular sieve     oxidation desulfuration     extraction     kinetic    

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Online gasoline blending with EPA Complex Model for predicting emissions

Stefan JANAQI, Mériam CHÈBRE, Guillaume PITOLLAT

《工程管理前沿（英文）》 2018年 第5卷 第2期   页码 214-226 doi: 10.15302/J-FEM-2017022

摘要： The empirical Complex Model developed by the US Environmental Protection Agency (EPA) is used by refiners to predict the toxic emissions of reformulated gasoline with respect to gasoline properties. The difficulty in implementing this model in the blending process stems from the implicit definition of Complex Model through a series of disjunctions assembled by the EPA in the form of spreadsheets. A major breakthrough in the refinery-based Complex Model implementation occurred in 2008 and 2010 through the use of generalized disjunctive and mixed-integer nonlinear programming (MINLP). Nevertheless, the execution time of these MINLP models remains prohibitively long to control emissions with our online gasoline blender. The first objective of this study is to present a new model that decreases the execution time of our online controller. The second objective is to consider toxic thresholds as hard constraints to be verified and search for blends that verify them. Our approach introduces a new way to write the Complex Model without any binary or integer variables. Sigmoid functions are used herein to approximate step functions until the measurement precision for each blend property is reached. By knowing this level of precision, we are able to propose an extremely good and differentiable approximation of the Complex Model. Next, a differentiable objective function is introduced to penalize emission values higher than the threshold emissions. Our optimization module has been implemented and tested with real data. The execution time never exceeded 1 s, which allows the online regulation of emissions the same way as other traditional properties of blended gasoline.

关键词： emissions     reformulated gasoline     online control     global optimization    

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基于修正模拟退火算法及溢出面积模型的固定边界布图规划 Article

De-xuan ZOU,Gai-ge WANG,Gai PAN,Hong-wei QI

《信息与电子工程前沿（英文）》 2016年 第17卷 第11期   页码 1228-1244 doi: 10.1631/FITEE.1500386

摘要： 另外，B*-tree是一种有效的布图规划表示法，它被用来执行MSA的扰动操作。

关键词： 固定边界布图规划；修正的模拟退火算法；全局搜索；溢出面积模型；B*-tree表示法    

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中国油用牡丹工程的战略思考

李育材

《中国工程科学》 2014年 第16卷 第10期   页码 58-63

摘要：

作为一种原产于我国的多年生小灌木，油用牡丹具有抗性强、适应范围广、产量高和油质好等特点。大力发展油用牡丹对促进我国油料生产、保障粮油安全、改善生态环境、增加农民收入、帮助贫困地区农民脱贫致富等都具有十分重要的意义。本文介绍了发展油用牡丹的重要意义，并通过分析油用牡丹发展中现存的问题，提出了对我国油用牡丹工程发展的建议与思考。

关键词： 油用牡丹     木本油料     工程     战略思考    

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标题 作者 时间 类型 操作

oblique load carrying capacity of batter pile groups using neural network, random forest regression and M5model tree

Tanvi SINGH, Mahesh PAL, V. K. ARORA

期刊论文

Estimation of flexible pavement structural capacity using machine learning techniques

Nader KARBALLAEEZADEH, Hosein GHASEMZADEH TEHRANI, Danial MOHAMMADZADEH SHADMEHRI, Shahaboddin SHAMSHIRBAND

期刊论文

Fast and catalytic pyrolysis of xylan: Effects of temperature and M/HZSM-5 (M= Fe, Zn) catalysts on pyrolytic

Xifeng ZHU, Qiang LU, Wenzhi LI, Dong ZHANG,

期刊论文

Heuristic solution using decision tree model for enhanced XML schema matching of bridge structural calculation

Sang I. PARK, Sang-Ho LEE

期刊论文

An innovative model for predicting the displacement and rotation of column-tree moment connection under

Mohammad Ali NAGHSH, Aydin SHISHEGARAN, Behnam KARAMI, Timon RABCZUK, Arshia SHISHEGARAN, Hamed TAGHAVIZADEH, Mehdi MORADI

期刊论文

Four-protein model for predicting prognostic risk of lung cancer

期刊论文

Development of machine learning multi-city model for municipal solid waste generation prediction

期刊论文

Kd-tree and quad-tree decompositions for declustering of 2D range queries over uncertain space

Ahmet SAYAR,Süleyman EKEN,Okan ÖZTÜRK

期刊论文

Deep convolutional tree-inspired network: a decision-tree-structured neural network for hierarchical

期刊论文

Catalytic hydrogenation of insoluble organic matter of CS/Acetone from coal over mesoporous HZSM-5 supported

期刊论文

Core designing of a new type of TVS-2M FAs: neutronics and thermal-hydraulics design basis limits

Saeed GHAEMI, Farshad FAGHIHI

期刊论文

Oxidation-extraction desulfurization of model oil over Zr-ZSM-5/SBA-15 and kinetic study

Chuanzhu LU,Hui FU,Huipeng LI,Hua ZHAO,Tianfeng CAI

期刊论文

Online gasoline blending with EPA Complex Model for predicting emissions

Stefan JANAQI, Mériam CHÈBRE, Guillaume PITOLLAT

期刊论文

基于修正模拟退火算法及溢出面积模型的固定边界布图规划

De-xuan ZOU,Gai-ge WANG,Gai PAN,Hong-wei QI

期刊论文

中国油用牡丹工程的战略思考

李育材

期刊论文