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Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang

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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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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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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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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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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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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A novel approach for remanufacturing process planning considering uncertain and fuzzy information

《机械工程前沿（英文）》 2021年 第16卷 第3期   页码 546-558 doi: 10.1007/s11465-021-0639-1

摘要： Remanufacturing, as one of the optimal disposals of end-of-life products, can bring tremendous economic and ecological benefits. Remanufacturing process planning is facing an immense challenge due to uncertainties and fuzziness of recoverable products in damage conditions and remanufacturing quality requirements. Although researchers have studied the influence of uncertainties on remanufacturing process planning, very few of them comprehensively studied the interactions among damage conditions and quality requirements that involve uncertain, fuzzy information. Hence, this challenge in the context of uncertain, fuzzy information is undertaken in this paper, and a method for remanufacturing process planning is presented to maximize remanufacturing efficiency and minimize cost. In particular, the characteristics of uncertainties and fuzziness involved in the remanufacturing processes are explicitly analyzed. An optimization model is then developed to minimize remanufacturing time and cost. The solution is provided through an improved Takagi–Sugeno fuzzy neural network (T-S FNN) method. The effectiveness of the proposed approach is exemplified and elucidated by a case study. Results show that the training speed and accuracy of the improved T-S FNN method are 23.5% and 82.5% higher on average than those of the original method, respectively.

关键词： remanufacturing     uncertain and fuzzy information     process planning     T-S FNN    

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An uncertain energy planning model under carbon taxes

Hongkuan ZANG, Yi XU, Wei LI, Guohe HUANG, Dan LIU

《环境科学与工程前沿（英文）》 2012年 第6卷 第4期   页码 549-558 doi: 10.1007/s11783-012-0414-y

摘要： In this study, an interval fuzzy mixed-integer energy planning model (IFMI-EPM) is developed under considering the carbon tax policy. The developed IFMI-EPM incorporates techniques of interval-parameter programming, fuzzy planning and mixed-integer programming within a general energy planning model. The IFMI-EPM can not only be used for quantitatively analyzing a variety of policy scenarios that are associated with different levels of carbon tax policy, but also tackle uncertainties expressed as discrete intervals and fuzzy sets in energy and environment systems. Considering low, medium and high carbon tax rates, the model is applied to an ideal energy and environment system. The results indicate that reasonable solutions have been generated. They can be used for generating decision alternatives and thus help decision makers identify desired carbon tax policy.

关键词： energy     carbon tax     planning     uncertainty     fuzzy    

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Models of thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture

WEI Wenjian, DING Guoliang, HU Haitao, WANG Kaijian

《能源前沿（英文）》 2008年 第2卷 第2期   页码 227-234 doi: 10.1007/s11708-008-0020-7

摘要： The thermodynamic properties of a refrigerant-oil mixture are the foundation to predict the performance of air-conditioning and refrigeration systems and to evaluate the influence of oil on heat transfer and pressure drop. Models of the thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture were provided based on the analysis of state-of-the-art correlations. New models were developed by modifying the coefficients in existing correlations with multiple regression method according to experimental data. The maximum deviation of the predicted values of these models to the experimental data is within 5%. These models can be used for R410A/POE VG68 to obtain accurate and reliable thermodynamic and transport parameters to evaluate the influence of POE VG68 on the performance of an R410A air-conditioning and refrigeration system.

关键词： multiple regression     foundation     thermodynamic     influence     air-conditioning    

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Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing

Juan LIU, Fei QIAO, Yumin MA, Weichang KONG

《工程管理前沿（英文）》 2018年 第5卷 第4期   页码 507-514 doi: 10.15302/J-FEM-2018045

摘要：

The NP-hard scheduling problems of semiconductor manufacturing systems (SMSs) are further complicated by stochastic uncertainties. Reactive scheduling is a common dynamic scheduling approach where the scheduling scheme is refreshed in response to real-time uncertainties. The scheduling scheme is overly sensitive to the emergence of uncertainties because the optimization of performance (such as minimum make-span) and the system robustness cannot be achieved simultaneously by conventional reactive scheduling methods. To improve the robustness of the scheduling scheme, we propose a novel slack-based robust scheduling rule (SR) based on the analysis of robustness measurement for SMS with uncertain processing time. The decision in the SR is made in real time given the robustness. The proposed SR is verified under different scenarios, and the results are compared with the existing heuristic rules. Simulation results show that the proposed SR can effectively improve the robustness of the scheduling scheme with a slight performance loss.

关键词： semiconductor manufacturing system     uncertain processing time     dynamic scheduling     slack-based robust scheduling rule    

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Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

《医学前沿（英文）》 2020年 第14卷 第4期   页码 498-505 doi: 10.1007/s11684-020-0791-8

摘要： Disorders of sex development (DSD) are a group of rare complex clinical syndromes with multiple etiologies. Distinguishing the various causes of DSD is quite difficult in clinical practice, even for senior general physicians because of the similar and atypical clinical manifestations of these conditions. In addition, DSD are difficult to diagnose because most primary doctors receive insufficient training for DSD. Delayed diagnoses and misdiagnoses are common for patients with DSD and lead to poor treatment and prognoses. On the basis of the principles and algorithms of dynamic uncertain causality graph (DUCG), a diagnosis model for DSD was jointly constructed by experts on DSD and engineers of artificial intelligence. “Chaining” inference algorithm and weighted logic operation mechanism were applied to guarantee the accuracy and efficiency of diagnostic reasoning under incomplete situations and uncertain information. Verification was performed using 153 selected clinical cases involving nine common DSD-related diseases and three causes other than DSD as the differential diagnosis. The model had an accuracy of 94.1%, which was significantly higher than that of interns and third-year residents. In conclusion, the DUCG model has broad application prospects as a computer-aided diagnostic tool for DSD-related diseases.

关键词： disorders of sex development (DSD)     intelligent diagnosis     dynamic uncertain causality graph    

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Presentation of machine learning methods to determine the most important factors affecting road traffic accidents on rural roads

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

《结构与土木工程前沿（英文）》 2022年 第16卷 第5期   页码 657-666 doi: 10.1007/s11709-022-0827-z

摘要： The purpose of this research was to develop statistical and intelligent models for predicting the severity of road traffic accidents (RTAs) on rural roads. Multiple Logistic Regression (MLR) was used to predict the likelihood of RTAs. For more accurate prediction, Multi-Layer Perceptron (MLP) and Radius Basis Function (RBF) neural networks were applied. Results indicated that in MLR, the model obtained from the backward method with the correct percent of 84.7% and R2 value of 0.893 was the best method for predicting the likelihood of RTAs. Also, MLR showed that the variables of not paying attention to the front not paying attention to the frontroad ahead, followed byand then vehicle-motorcycle/bike accidents were the greatest problems. Among the models, MLP had a better performance, so that the prediction accuracy of MLR, MLP, and RBF were 84.7%, 96.7%, and 92.1%, respectively. MLP model, due to higher accuracy, showed that the variable of reason of accident had the highest effect on the prediction of accidents, and considering MLR results, the variables of not paying attention to the front and then vehicle-motorcycle/bike accidents had the most influence on the occurrence of accidents. Therefore, motorcyclists and cyclists are more prone to accidents, and appropriate solutions should be adopted to enhance their safety.

关键词： safety     rural accidents     multiple logistic regression     artificial neural networks    

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cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain

Keqiang LI, Feng GAO, Shengbo Eben LI, Yang ZHENG, Hongbo GAO

《机械工程前沿（英文）》 2018年 第13卷 第3期   页码 354-367 doi: 10.1007/s11465-018-0486-x

摘要：

This study presents a distributed H-infinity control method for uncertain platoons with dimensionally and structurally unknown interaction topologies provided that the associated topological eigenvalues are bounded by a predesigned range. With an inverse model to compensate for nonlinear powertrain dynamics, vehicles in a platoon are modeled by third-order uncertain systems with bounded disturbances. On the basis of the eigenvalue decomposition of topological matrices, we convert the platoon system to a norm-bounded uncertain part and a diagonally structured certain part by applying linear transformation. We then use a common Lyapunov method to design a distributed H-infinity controller. Numerically, two linear matrix inequalities corresponding to the minimum and maximum eigenvalues should be solved. The resulting controller can tolerate interaction topologies with eigenvalues located in a certain range. The proposed method can also ensure robustness performance and disturbance attenuation ability for the closed-loop platoon system. Hardware-in-the-loop tests are performed to validate the effectiveness of our method.

关键词： automated vehicles     platoon     distributed control     robustness    

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标题 作者 时间 类型 操作

Integrated uncertain models for runoff forecasting and crop planting structure optimization of the Shiyang

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

期刊论文

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

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

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

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

Walid Khalid MBARAK, Esma Nur CINICIOGLU, Ozer CINICIOGLU

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

A novel approach for remanufacturing process planning considering uncertain and fuzzy information

期刊论文

An uncertain energy planning model under carbon taxes

Hongkuan ZANG, Yi XU, Wei LI, Guohe HUANG, Dan LIU

期刊论文

Models of thermodynamic and transport properties of POE VG68 and R410A/POE VG68 mixture

WEI Wenjian, DING Guoliang, HU Haitao, WANG Kaijian

期刊论文

Novel slack-based robust scheduling rule for a semiconductor manufacturing system with uncertain processing

Juan LIU, Fei QIAO, Yumin MA, Weichang KONG

期刊论文

Efficacy of intelligent diagnosis with a dynamic uncertain causality graph model for rare disorders of

Dongping Ning, Zhan Zhang, Kun Qiu, Lin Lu, Qin Zhang, Yan Zhu, Renzhi Wang

期刊论文

Presentation of machine learning methods to determine the most important factors affecting road traffic accidents on rural roads

Hamid MIRZAHOSSEIN; Milad SASHURPOUR; Seyed Mohsen HOSSEINIAN; Vahid Najafi Moghaddam GILANI

期刊论文

cooperation of connected vehicle systems with eigenvalue-bounded interaction topologies in the presence of uncertain

Keqiang LI, Feng GAO, Shengbo Eben LI, Yang ZHENG, Hongbo GAO

期刊论文