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Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

《结构与土木工程前沿（英文）》 2017年 第11卷 第1期   页码 90-99 doi: 10.1007/s11709-016-0363-9

摘要： Evaluating the in situ concrete compressive strength by means of cores cut from hardened concrete is acknowledged as the most ordinary method, however, it is very difficult to predict the compressive strength of concrete since it is affected by many factors such as different mix designs, methods of mixing, curing conditions, compaction, etc. In this paper, considering the experimental results, three different models of multiple linear regression model (MLR), artificial neural network (ANN), and adaptive neuro-fuzzy inference system (ANFIS) are established, trained, and tested within the Matlab programming environment for predicting the 28 days compressive strength of concrete with 173 different mix designs. Finally, these three models are compared with each other and resulted in the fact that ANN and ANFIS models enables us to reliably evaluate the compressive strength of concrete with different mix designs, however, multiple linear regression model is not feasible enough in this area because of nonlinear relationship between the concrete mix parameters. Finally, the sensitivity analysis (SA) for two different sets of parameters on the concrete compressive strength prediction are carried out.

关键词： concrete     28 days compressive strength     multiple linear regression     artificial neural network     ANFIS     sensitivity analysis (SA)    

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SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

《结构与土木工程前沿（英文）》 2020年 第14卷 第1期   页码 185-198 doi: 10.1007/s11709-019-0591-x

摘要： The purpose of this study is the accurate prediction of undrained shear strength using Standard Penetration Test results and soil consistency indices, such as water content and Atterberg limits. With this study, along with the conventional methods of simple and multiple linear regression models, three machine learning algorithms, random forest, gradient boosting and stacked models, are developed for prediction of undrained shear strength. These models are employed on a relatively large data set from different projects around Turkey covering 230 observations. As an improvement over the available studies in literature, this study utilizes correct statistical analyses techniques on a relatively large database, such as using a train/test split on the data set to avoid overfitting of the developed models. Furthermore, the validity and consistency of the prediction results are ensured with the correct use of statistical measures like -value and cross-validation which were missing in previous studies. To compare the performances of the models developed in this study with the prior ones existing in literature, all models were applied on the test data set and their performances are evaluated in terms of the resulting root mean squared error ( ) values and coefficient of determination ( ). Accordingly, the models developed in this study demonstrate superior prediction capabilities compared to all of the prior studies. Moreover, to facilitate the use of machine learning algorithms for prediction purposes, entire source code prepared for this study and the collected data set are provided as supplements of this study.

关键词： undrained shear strength     linear regression     random forest     gradient boosting     machine learning     standard penetration test    

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A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

《能源前沿（英文）》 2016年 第10卷 第4期   页码 459-465 doi: 10.1007/s11708-016-0424-8

摘要： Considering the fact that customers of large commercial buildings have the characteristics of the higher density and randomness, this paper presented an air-conditioning cooling load prediction method based on weather forecast and internal occupancy density. The multiple linear feedback regression model was applied to predict, with precision, the air conditioning cooling load. Case analysis showed that the largest mean relative error of hourly and the daily predicting cooling load maximum were 18.1% and 5.14%, respectively.

关键词： commercial building     load prediction     multiple linear regression    

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Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

Juan WU, Jian ZHANG, Wenlin JIA, Huijun XIE, Bo ZHANG

《环境科学与工程前沿（英文）》 2009年 第3卷 第2期   页码 241-247 doi: 10.1007/s11783-009-0023-6

摘要： The effects of chemical oxygen demand (COD) concentration in the influent on nitrous oxide (N O) emissions, together with the relationships between N O and water quality parameters in free water surface constructed wetlands, were investigated with laboratory-scale systems. N O emission and purification performance of wastewater were very strongly dependent on COD concentration in the influent, and the total N O emission in the system with middle COD influent concentration was the least. The relationships between N O and the chemical and physical water quality variables were studied by using principal component scores in multiple linear regression analysis to predict N O flux. The multiple linear regression model against principal components indicated that different water parameters affected N O flux with different COD concentrations in the influent, but nitrate nitrogen affected N O flux in all systems.

关键词： free water surface constructed wetland     nitrous oxide emission     water quality parameter     principal component analysis     multiple linear regression    

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Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang River Basin, north-west China

Fan ZHANG, Mo LI, Shanshan GUO, Chenglong ZHANG, Ping GUO

《农业科学与工程前沿（英文）》 2018年 第5卷 第2期   页码 177-187 doi: 10.15302/J-FASE-2017177

摘要： To improve the accuracy of runoff forecasting, an uncertain multiple linear regression (UMLR) model is presented in this study. The proposed model avoids the transfer of random error generated in the independent variable to the dependent variable, as this affects prediction accuracy. On this basis, an inexact two-stage stochastic programming (ITSP) model is used for crop planting structure optimization (CPSO) with the inputs that are interval flow values under different probabilities obtained from the UMLR model. The developed system, in which the UMLR model for runoff forecasting and the ITSP model for crop planting structure optimization are integrated, is applied to a real case study. The aim of the developed system is to optimize crops planting area with limited available water resources base on the downstream runoff forecasting in order to obtain the maximum system benefit in the future. The solution obtained can demonstrate the feasibility and suitability of the developed system, and help decision makers to identify reasonable crop planting structure under multiple uncertainties.

关键词： crop planting structure optimization     inexact two-stage stochastic programming     runoff forecasting     Shiyang River Basin     uncertain multiple linear regression    

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Influence of accelerated curing on the compressive strength of polymer-modified concrete

Izhar AHMAD; Kashif Ali KHAN; Tahir AHMAD; Muhammad ALAM; Muhammad Tariq BASHIR

《结构与土木工程前沿（英文）》 2022年 第16卷 第5期   页码 589-599 doi: 10.1007/s11709-022-0789-1

摘要： In recent building practice, rapid construction is one of the principal requisites. Furthermore, in designing concrete structures, compressive strength is the most significant of all parameters. While 3-d and 7-d compressive strength reflects the strengths at early phases, the ultimate strength is paramount. An effort has been made in this study to develop mathematical models for predicting compressive strength of concrete incorporating ethylene vinyl acetate (EVA) at the later phases. Kolmogorov-Smirnov (KS) goodness-of-fit test was used to examine distribution of the data. The compressive strength of EVA-modified concrete was studied by incorporating various concentrations of EVA as an admixture and by testing at ages of 28, 56, 90, 120, 210, and 365 d. An accelerated compressive strength at 3.5 hours was considered as a reference strength on the basis of which all the specified strengths were predicted by means of linear regression fit. Based on the results of KS goodness-of-fit test, it was concluded that KS test statistics value (D) in each case was lower than the critical value 0.521 for a significance level of 0.05, which demonstrated that the data was normally distributed. Based on the results of compressive strength test, it was concluded that the strength of EVA-modified specimens increased at all ages and the optimum dosage of EVA was achieved at 16% concentration. Furthermore, it was concluded that predicted compressive strength values lies within a 6% difference from the actual strength values for all the mixes, which indicates the practicability of the regression equations. This research work may help in understanding the role of EVA as a viable material in polymer-based cement composites.

关键词： compressive strength prediction     polymer-modified concrete     linear regression fit     early age strength     ethylene vinyl acetate    

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Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

《能源前沿（英文）》 2013年 第7卷 第1期   页码 103-110 doi: 10.1007/s11708-012-0220-z

摘要： The energy consumption of office buildings in China has been growing significantly in recent years. Obviously, there are significant relationships between building envelope and the energy consumption of office buildings. The 8 key building envelope influencing factors were found in this paper to evaluate their effects on the energy consumption of the air-conditioning system. The typical combinations of the key influencing factors were performed in Trnsy simulation. Then on the basis of the simulated results, the multiple regression models were developed respectively for the four climates of China—hot summer and warm winter, hot summer and cold winter, cold, and severely cold. According to the analysis of regression coefficients, the appropriate building envelope design schemes were discussed in different climates. At last, the regression model evaluations consisting of the simulation evaluations and the actual case evaluations were performed to verify the feasibility and accuracy of the regression models. The error rates are within±5% in the simulation evaluations and within±15% in the actual case evaluations. It is believed that the regression models developed in this paper can be used to estimate the energy consumption of office buildings in different climates when various building envelope designs are considered.

关键词： regression model     energy consumption     building envelope     office building     different climates    

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Estimation of photolysis half-lives of dyes in a continuous-flow system with the aid of quantitative structure-property relationship

Davoud BEIKNEJAD,Mohammad Javad CHAICHI

《环境科学与工程前沿（英文）》 2014年 第8卷 第5期   页码 683-692 doi: 10.1007/s11783-014-0680-y

摘要： In this paper the photolysis half-lives of the model dyes in water solutions and under ultraviolet (UV) radiation were determined by using a continuous-flow spectrophotometric method. A quantitative structure-property relationship (QSPR) study was carried out using 21 descriptors based on different chemometric tools including stepwise multiple linear regression (MLR) and partial least squares (PLS) for the prediction of the photolysis half-life ( ) of dyes. For the selection of test set compounds, a K-means clustering technique was used to classify the entire data set, so that all clusters were properly represented in both training and test sets. The QSPR results obtained with these models show that in MLR-derived model, photolysis half-lives of dyes depended strongly on energy of the highest occupied molecular orbital ( ), largest electron density of an atom in the molecule ( ) and lipophilicity (log ). While in the model derived from PLS, besides aforementioned and descriptors, the molecular surface area ( ), molecular weight ( ), electronegativity ( ), energy of the second highest occupied molecular orbital ( ) and dipole moment ( ) had dominant effects on logt values of dyes. These were applicable for all classes of studied dyes (including monoazo, disazo, oxazine, sulfonephthaleins and derivatives of fluorescein). The results were also assessed for their consistency with findings from other similar studies.

关键词： dye     photolysis half-life     quantitative structure-property relationship     continuous-flow     stepwise multiple linear regression     partial least squares    

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Option-like properties in the distribution of hedge fund returns

Katharina DENK, Ben DJERROUD, Luis SECO, Mohammad SHAKOURIFAR, Rudi ZAGST

《工程管理前沿（英文）》 2020年 第7卷 第2期   页码 275-286 doi: 10.1007/s42524-020-0095-3

摘要： Hedge funds have recently become popular because of their low correlation with traditional investments and their ability to generate positive returns with a relatively low volatility. However, a close look at those high-performing hedge funds raises the questions on whether their performance is truly superior and whether the high management fees are justified. Incurring no alpha costs, passive hedge fund replication strategies raise the question on whether they can similarly perform by improving efficiency at reduced costs. Therefore, this study investigates two different model approaches for the equity long/short strategy, where weighted segmented linear regression models are employed and combined with two-state Markov switching models. The main finding proves a short put option structure, i.e., short equity market volatility, with the put structure present in all market states. We obtain an evidence that the hedge fund managers decrease their short-volatility profile during turbulent markets.

关键词： hedge funds     hedge fund index     segmented linear regression models     regime-switching models     mimicking portfolios     single factor-based hedge fund replication     equity long–short strategy    

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Design and analysis of linear oscillating motor for linear pump application-magnetic field, dynamics

Zongxia JIAO,Tianyi WANG,Liang YAN

《机械工程前沿（英文）》 2016年 第11卷 第4期   页码 351-362 doi: 10.1007/s11465-016-0407-9

摘要：

A linear oscillating motor is an electromagnetic actuator that can achieve short-stroke reciprocating movement directly without auxiliary transmission mechanisms. It has been widely used in linear pump applications as the source of power and motion. However, because of the demand of high power density in a linear actuation system, the performance of linear oscillating motors has been the focus of studies and deserves further research for high power density. In this paper, a general framework of linear oscillating motor design and optimization is addressed in detail, including the electromagnetic, dynamics, and thermal aspects. First, the electromagnetic and dynamics characteristics are modeled to reveal the principle for optimization. Then, optimization and analysis on magnetic structure, resonant system, and thermal features are conducted, which provide the foundation for prototype development. Finally, experimental results are provided for validation. As a whole, this process offers complete guidance for high power density linear oscillating motors in linear pump applications.

关键词： linear oscillating motor     linear pump     magnetic field     motor optimization    

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Comparison between linear and non-linear forms of pseudo-first-order and pseudo-second-order adsorption

Junxiong LIN , Lan WANG ,

《环境科学与工程前沿（英文）》 2009年 第3卷 第3期   页码 320-324 doi: 10.1007/s11783-009-0030-7

摘要： The best-fit equations of linear and non-linear forms of the two widely used kinetic models, namely pseudo-first-order and pseudo-second-order equations, were compared in this study. The experimental kinetics of methylene blue adsorption on activated carbon was used for this research. Both the correlation coefficient () and the normalized standard deviation Δ(%) were employed as error analysis methods to determine the best-fitting equations. The results show that the non-linear forms of pseudo-first-order and pseudo-second-order models were more suitable than the linear forms for fitting the experimental data. The experimental kinetics may have been distorted by linearization of the linear kinetic equations, and thus, the non-linear forms of kinetic equations should be primarily used to obtain the adsorption parameters. In addition, the Δ(%) method for error analysis may be better to determine the best-fitting model in this case.

关键词： adsorption     pseudo-first order     pseudo-second order     kinetic model     linear method     non-linear method    

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使用数据驱动模型优化抗体纯化策略 Article

刘松崧, Lazaros G. Papageorgiou

《工程（英文）》 2019年 第5卷 第6期   页码 1077-1092 doi: 10.1016/j.eng.2019.10.011

摘要：

本工作致力于抗体片段纯化过程的多尺度优化。优化了生产过程中的色谱决策，包括色谱柱的数量及其大小，每批的循环数以及操作流速。使用基于微型实验数据的制造规模模拟数据集，建立了以负载质量、流速和柱床高度为输入的色谱通量数据驱动模型。与其他方法相比，分段线性回归建模方法具有简单、预测精度高的优点。提出了两种混合整数非线性规划（MINLP）模型，结合数据驱动模型，以最小化每克抗体纯化过程的总成本。然后，使用线性化技术和多参数分解将这些MINLP模型重新构造为混合整数线性规划（MILP）模型。研究了两个具有不同色谱柱尺寸替代品的工业相关案例，以证明所提出模型的适用性。

关键词： 抗体纯化     多尺度优化     抗原结合片段     混合整数规划     数据驱动模型     分段线性回归    

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海洋二号扫描微波辐射计冷空定标和地球物理参数反演研究

周武,林明森,李延民,王振占,黄磊

《中国工程科学》 2013年 第15卷 第7期   页码 75-80

摘要：

本文研究了海洋二号（HY-2A）扫描微波辐射计冷空定标方法和数据反演算法。针对HY-2A扫描微波辐射计对地观测和定标扫描的设计原理和观测几何，基于微波辐射计的对地观测数据修正进入冷空反射器的地球信号，建立地面观测亮温的冷空反射器权重系数矩阵修正冷空观测信号；基于海面温度、海面风速、水汽含量和云液态含量的微波辐射计辐射传输模型，计算HY-2A扫描微波辐射计不同条件下的各频率极化方式下的理论亮温，建立线性回归模型，拟合不同地球物理参数的反演系数，采用多元线性回归算法反演HY-2A微波扫描辐射计地球物理参数，对比国外成熟微波辐射计数据，得到产品精度。

关键词： 扫描微波辐射计     多元线性回归     星星交叉     冷空定标    

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Dynamic response surface methodology using Lasso regression for organic pharmaceutical synthesis

《化学科学与工程前沿（英文）》 2022年 第16卷 第2期   页码 221-236 doi: 10.1007/s11705-021-2061-y

摘要： To study the dynamic behavior of a process, time-resolved data are collected at different time instants during each of a series of experiments, which are usually designed with the design of experiments or the design of dynamic experiments methodologies. For utilizing such time-resolved data to model the dynamic behavior, dynamic response surface methodology (DRSM), a data-driven modeling method, has been proposed. Two approaches can be adopted in the estimation of the model parameters: stepwise regression, used in several of previous publications, and Lasso regression, which is newly incorporated in this paper for the estimation of DRSM models. Here, we show that both approaches yield similarly accurate models, while the computational time of Lasso is on average two magnitude smaller. Two case studies are performed to show the advantages of the proposed method. In the first case study, where the concentrations of different species are modeled directly, DRSM method provides more accurate models compared to the models in the literature. The second case study, where the reaction extents are modeled instead of the species concentrations, illustrates the versatility of the DRSM methodology. Therefore, DRSM with Lasso regression can provide faster and more accurate data-driven models for a variety of organic synthesis datasets.

关键词： data-driven modeling     pharmaceutical organic synthesis     Lasso regression     dynamic response surface methodology    

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Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based

《结构与土木工程前沿（英文）》 2021年 第15卷 第5期   页码 1181-1198 doi: 10.1007/s11709-021-0744-6

摘要： In the recent era, piled raft foundation (PRF) has been considered an emergent technology for offshore and onshore structures. In previous studies, there is a lack of illustration regarding the load sharing and interaction behavior which are considered the main intents in the present study. Finite element (FE) models are prepared with various design variables in a double-layer soil system, and the load sharing and interaction factors of piled rafts are estimated. The obtained results are then checked statistically with nonlinear multiple regression (NMR) and artificial neural network (ANN) modeling, and some prediction models are proposed. ANN models are prepared with Levenberg–Marquardt (LM) algorithm for load sharing and interaction factors through backpropagation technique. The factor of safety (FS) of PRF is also estimated using the proposed NMR and ANN models, which can be used for developing the design strategy of PRF.

关键词： interaction     load sharing ratio     piled raft     nonlinear regression     artificial neural network    

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标题 作者 时间 类型 操作

Multiple linear regression, artificial neural network, and fuzzy logic prediction of 28 days compressive

Faezehossadat KHADEMI,Mahmoud AKBARI,Sayed Mohammadmehdi JAMAL,Mehdi NIKOO

期刊论文

SPT based determination of undrained shear strength: Regression models and machine learning

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

期刊论文

A method to predict cooling load of large commercial buildings based on weather forecast and internal occupancy

Junbao JIA,Jincheng XING,Jihong LING,Ren PENG

期刊论文

Relationships of nitrous oxide fluxes with water quality parameters in free water surface constructed wetlands

Juan WU, Jian ZHANG, Wenlin JIA, Huijun XIE, Bo ZHANG

期刊论文

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang River Basin, north-west China

Fan ZHANG, Mo LI, Shanshan GUO, Chenglong ZHANG, Ping GUO

期刊论文

Influence of accelerated curing on the compressive strength of polymer-modified concrete

Izhar AHMAD; Kashif Ali KHAN; Tahir AHMAD; Muhammad ALAM; Muhammad Tariq BASHIR

期刊论文

Multiple regression models for energy consumption of office buildings in different climates in China

Siyu ZHOU, Neng ZHU

期刊论文

Estimation of photolysis half-lives of dyes in a continuous-flow system with the aid of quantitative structure-property relationship

Davoud BEIKNEJAD,Mohammad Javad CHAICHI

期刊论文

Option-like properties in the distribution of hedge fund returns

Katharina DENK, Ben DJERROUD, Luis SECO, Mohammad SHAKOURIFAR, Rudi ZAGST

期刊论文

Design and analysis of linear oscillating motor for linear pump application-magnetic field, dynamics

Zongxia JIAO,Tianyi WANG,Liang YAN

期刊论文

Comparison between linear and non-linear forms of pseudo-first-order and pseudo-second-order adsorption

Junxiong LIN , Lan WANG ,

期刊论文

使用数据驱动模型优化抗体纯化策略

刘松崧, Lazaros G. Papageorgiou

期刊论文

海洋二号扫描微波辐射计冷空定标和地球物理参数反演研究

周武,林明森,李延民,王振占,黄磊

期刊论文

Dynamic response surface methodology using Lasso regression for organic pharmaceutical synthesis

期刊论文

Interaction behavior and load sharing pattern of piled raft using nonlinear regression and LM algorithm-based

期刊论文