检索结果-内蒙古大学图书馆

High Energy Physics event selection with gene expression programming

COMPUTER PHYSICS COMMUNICATIONS 2008年第6期178卷 409-419页

作者： Teodorescu, Liliana Sherwood, Daniel Brunel Univ London England

gene expression programming is a new evolutionary algorithm that overcomes many limitations of the more established genetic Algorithms and genetic programming. Its application to event selection in high energy physics data analysis is presented using as an example application the selection of K-S particles produced in e(+)e(-) interactions at 10 GeV and reconstructed in the decay mode K-S -> pi(+)pi(-). The algorithm was used for automatic identification of classification criteria for signallbackground separation. For the problem studied and for data samples with signal to background ratios between 0.25 and 5, the classification accuracy obtained with the criteria developed by the GEP algorithm was in the range of 92-95%. (C) 2007 Elsevier B.V. All rights reserved.

关键词： evolutionary algorithms gene expression programming event selection classification High Energy Physics

来源：评论

学校读者我要写书评

暂无评论

Short-term load forecasting of power systems by gene expression programming

引用

NEURAL COMPUTING & APPLICATIONS 2012年第2期21卷 377-389页

作者： Hosseini, Seyyed Soheil Sadat Gandomi, Amir Hossein Tafresh Univ Tafresh Iran

Short-term load forecasting is a popular topic in the electric power industry due to its essentiality in energy system planning and operation. Load forecasting is important in deregulated power systems since an improvement of a few percentages in the prediction accuracy will bring benefits worth of millions of dollars. In this study, a promising variant of genetic programming, namely gene expression programming (GEP), is utilized to improve the accuracy and enhance the robustness of load forecasting results. With the use of the GEP technique, accurate relationships were obtained to correlate the peak and total loads to average, maximum and lowest temperatures of day. The presented model is applied to forecast short-term load using the actual data from a North American electric utility. A multiple least squares regression analysis was performed using the same variables and same data sets to benchmark the GEP models. For more verification, a subsequent parametric study was also carried out. The observed agreement between the predicted and measured peak and total load values indicates that the proposed correlations are capable of effectively forecasting the short-term load. The GEP-based formulas are relatively short, simple and particularly valuable for providing an analysis tool accessible to practicing engineers.

关键词： Short-term load forecasting gene expression programming Formulation

来源：评论

学校读者我要写书评

暂无评论

Application of gene expression programming and sensitivity analyses in analyzing effective parameters in gastric cancer tumor size and location

引用

SOFT COMPUTING 2020年第13期24卷 9943-9964页

作者： Dorosti, Shadi Ghoushchi, Saeid Jafarzadeh Sobhrakhshankhah, Elham Ahmadi, Mohsen Sharifi, Abbas UUT Dept Ind Engn POB 57166-419 Orumiyeh Iran Urmia Univ Med Sci Imam Khomeini Hosp Dept Internal Med Orumiyeh Iran UUT Dept Mech Engn Orumiyeh Iran

Gastric cancer (GC) is the third reason for cancer-related deaths in the world. The late referral of patients to medical centers in an advanced stage can make the treatment procedure more difficult. Accurate diagnosis of risk factors in GC tumor size and tumor location can lead to taking preventive measures or determining a suitable treatment strategy. This study aims to present a general model to identify the correlation of different parameters in a GC tumor place and tumor size. The medical documents of GC patients consist of the dataset of this study. The effect of seven main parameters, namely age, smoking, Helicobacter pylori (H. pylori) infection, job, surgical background, sex, and nodal stage is investigated in GC tumor location and tumor size. By considering all the medical documents, data modeling is conducted using gene expression programming because of the high precision of model output. In the following, three different sensitivity analysis methods (Morris, Distributed Evaluation of Local Sensitivity Analysis (DELSA), and Sobol'-Jansen) are applied to determine the influential factors in the tumor size and location. Results show that in sequence, sex, age, and H. pylori records mostly affect tumor location;the nodal stage, smoking, and surgery record mostly affect tumor size. This method can help in identifying effective parameters and prevention of patients' death in all types of diseases, even for terminal illnesses.

关键词： Gastric cancer Sensitivity analysis gene expression programming Sobol'-Jansen Morris Distributed Evaluation of Local Sensitivity Analysis

来源：评论

学校读者我要写书评

暂无评论

A new predictive model for compressive strength of HPC using gene expression programming

引用

ADVANCES IN ENGINEERING SOFTWARE 2012年第1期45卷 105-114页

作者： Mousavi, Seyyed Mohammad Aminian, Pejman Gandomi, Amir Hossein Alavi, Amir Hossein Bolandi, Hamed Islamic Azad Univ Cent Tehran Branch Tehran Iran Islamic Azad Univ Sci & Res Branch Fac Humanities & Social Sci Dept Geog & Urban Planning Tehran Iran Islamic Azad Univ Dept Civil Engn Shahrood Branch Shahrood Iran Islamic Azad Univ Mashhad Branch Mashhad Iran Islamic Azad Univ Bandar Abbas Branch Dept Civil Engn Bandar Abbas Iran

In this study, gene expression programming (GEP) is utilized to derive a new model for the prediction of compressive strength of high performance concrete (HPC) mixes. The model is developed using a comprehensive database obtained from the literature. The validity of the proposed model is verified by applying it to estimate the compressive strength of a portion of test results that are not included in the analysis. Linear and nonlinear least squares regression analyses are performed to benchmark the GEP model. Contributions of the parameters affecting the compressive strength are evaluated through a sensitivity analysis. GEP is found to be an effective method for evaluating the compressive strength of HPC mixes. The prediction performance of the optimal GEP model is better than the regression models. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： High performance concrete gene expression programming Compressive strength Regression analysis Sensitivity analysis Prediction

来源：评论

学校读者我要写书评

暂无评论

Optimization of the Length of Silicon Nanowires Prepared from MACE Method Using gene expression programming and genetic Algorithm

引用

SILICON 2022年第13期14卷 7633-7642页

作者： Zeraati, Malihe Abbasi, Hossein Safinejad, Moosareza Kazemzadeh, Parya Chauhan, Narendra Pal Singh Sargazi, Ghasem Shahid Bahonar Univ Kerman Dept Mat Engn Kerman 761694111 Iran Azad Univ Tangestan Ahram Dept Comp Engn Tangestan Bushehr Iran Shahid Bahonar Univ Kerman Dept Elect Engn RF MEMS & Micro Bionano Elect MBNE Lab Kerman Iran Lorestan Univ Dept Chem Korramabad Iran Bhupal Nobles Univ Fac Sci Dept Chem Udaipur 313002 Rajasthan India Bam Univ Med Sci Noncommunicable Dis Res Ctr Bam Iran

Metal-assisted chemical etching (MACE) of silicon is used in this study to fabricate silicon nanowire arrays (SiNWs) of different length. This method was modeled using gene expression programming (GEP), and GEP was optimized using genetic algorithms (GA). The length of SiNWs has been predicted as a function of parameters like Ag nucleation on Si and etching solution parameters. The SiNWs in the experimental test have a minimum length of 1 mu m. According to FE-SEM images, SiNWs are uniformly shaped. It could be used to fabricate electrode materials for micro-supercapacitor.

关键词： Silicon nanowire Metal-assisted chemical etching gene expression programming genetic algorithm Optimization

来源：评论

学校读者我要写书评

暂无评论

An improvement on fuzzy seismic fragility analysis using gene expression programming

引用

STRUCTURAL ENGINEERING AND MECHANICS 2022年第5期83卷 577-591页

作者： Ebrahimi, Elaheh Abdollahzadeh, Gholamreza Jahani, Ehsan Babol Noshirvani Univ Technol Fac Civil Engn Babol Iran Univ Mazandaran Dept Civil Engn Babolsar Iran

This paper develops a comparatively time-efficient methodology for performing seismic fragility analysis of the reinforced concrete (RC) buildings in the presence of uncertainty sources. It aims to appraise the effectiveness of any variation in the material's mechanical properties as epistemic uncertainty, and the record-to-record variation as aleatory uncertainty in structural response. In this respect, the fuzzy set theory, a well-known alpha-cut approach, and the genetic Algorithm (GA) assess the median of collapse fragility curves as a fuzzy response. GA is requisite for searching the maxima and minima of the objective function (median fragility herein) in each membership degree, alpha. As this is a complicated and time-consuming process, the authors propose utilizing the gene expression programming-based (GEP-based) equation for reducing the computational analysis time of the case study building significantly. The results indicate that the proposed structural analysis algorithm on the derived GEP model is able to compute the fuzzy median fragility about 33.3% faster, with errors less than 1%.

关键词： fuzzy set theory gene expression programming genetic algorithm seismic fragility curve uncertainty

来源：评论

学校读者我要写书评

暂无评论

Statistical downscaling of watershed precipitation using gene expression programming (GEP)

引用

ENVIRONMENTAL MODELLING & SOFTWARE 2011年第12期26卷 1639-1646页

作者： Hashmi, Muhammad Z. Shamseldin, Asaad Y. Melville, Bruce W. Univ Auckland Dept Civil & Environm Engn Sch Engn Auckland 1010 New Zealand

Investigation of hydrological impacts of climate change at the regional scale requires the use of a downscaling technique. Significant progress has already been made in the development of new statistical downscaling techniques. Statistical downscaling techniques involve the development of relationships between the large scale climatic parameters and local variables. When the local parameter is precipitation, these relationships are often very complex and may not be handled efficiently using linear regression. For this reason, a number of non-linear regression techniques and the use of Artificial Neural Networks (ANNs) was introduced. But due to the complexity and issues related to finding a global solution using ANN-based techniques, the genetic programming (GP) based techniques have surfaced as a potential better alternative. Compared to ANNs, GP based techniques can provide simpler and more efficient solutions but they have been rarely used for precipitation downscaling. This paper presents the results of statistical downscaling of precipitation data from the Clutha Watershed in New Zealand using a non-linear regression model developed by the authors using gene expression programming (GEP), a variant of GP. The results show that GEP-based downscaling models can offer very simple and efficient solutions in the case of precipitation downscaling. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Statistical downscaling gene expression programming Data-driven Watershed Precipitation

来源：评论

学校读者我要写书评

暂无评论

Processing Parameters Optimization of Draw Frame for Rotor Spun Yarn Strength Using gene expression programming (GEP)

引用

FIBERS AND POLYMERS 2011年第7期12卷 970-975页

作者： Moghassem, A. R. Fallahpour, A. R. Islamic Azad Univ Dept Text Engn Qaemshahr Branch Qaemshahr Iran Islamic Azad Univ Firoozkooh Branch Dept Management Firoozkooh Iran

Breaking strength is one of the most important mechanical property of a yarn as it is the main parameter for quality control. This property depends on many different factors namely, raw material factors, process variables and machine parameters. Since, there is a high degree of interaction between yarn properties and influencing factors therefore, optimal processing conditions can not be determined easily. This article proposes prediction approach for the determination of the breaking strength of the yam using gene expression programming (GEP) and optimization technique using MATLAB software. A nonlinear mathematical function was derived on the basis of draw frame variables that were distance between back and middle rolls, delivery speed and break draft by GEP. Afterward, optimal conditions were found in such a way that breaking strength to be maximized. Study showed that, optimal processing parameters including distance between back and middle rolls, break draft and delivery speed were respectively, 10.70 mm, 1.90 and 541.51 m/min (687.95 or 721.32 based on the optimization procedure).

关键词： Optimization gene expression programming MATLAB software Draw frame Break draft Delivery speed

来源：评论

学校读者我要写书评

暂无评论

A gene expression programming-based method for real-time wear estimation of disc cutter on TBM cutterhead

引用

NEURAL COMPUTING & APPLICATIONS 2022年第22期34卷 20231-20247页

作者： Tao, Jianfeng Yu, Honggan Qin, Chengjin Sun, Hao Liu, Chengliang Shanghai Jiao Tong Univ Sch Mech Engn State Key Lab Mech Syst & Vibrat Shanghai 200240 Peoples R China

Frequent entry in the tunnel boring machine cutterhead for disc cutter wear inspection is a risky, time-consuming, and labor-intensive activity. Existing disc cutter wear prediction models mainly focus on cutter consumption before construction, and it is impossible to estimate the wear of a single cutter when they are applied to on-site construction. To solve this problem, this research presents a method for estimating the wear of each disc cutter on the cutterhead in real time by only using several monitored machine parameters. Firstly, a novel health index that can characterize the wear of each disc cutter is constructed, and the field parameters that have greater impact on the health index are selected. Then, the explicit mathematical expression between the selected parameters and the health index is established based on genetic expression programming. Finally, the on-site data collected from an Indian subway tunnel were used to validate the effectiveness and superiority of the proposed method. The results show that the proposed method can estimate the wear of each disc cutter in real time only by monitoring the rotational speed of cutterhead and tunneling speed. Its average accuracies on the validation set and test set are 90.6% and 85.9%, respectively. Compared with the ridge regression, decision tree, support vector regression and k-nearest neighbors, its accuracy on the test set is 13.0%, 12.7%, 11.2%, and 15.4% higher, respectively. Therefore, the proposed method can greatly reduce the cost for cutter inspection, and the explicit model can be easily deployed to the construction site.

关键词： Tunnel boring machine Disc cutter Wear estimation Real time gene expression programming

来源：评论

学校读者我要写书评

暂无评论

A gene expression programming approach for thermodynamic properties of working fluids used on Organic Rankine Cycle

引用

NEURAL COMPUTING & APPLICATIONS 2019年第8期31卷 3947-3955页

作者： Sahin, Arzu Sencan Dikmen, Erkan Senturk, Samet Suleyman Demirel Univ Fac Technol TR-32260 Isparta Turkey

The selection of appropriate fluid in Organic Rankine Cycles (ORC) is an important issue. The thermodynamic properties of working fluids affect the efficiency, operation and environmental impact of the system. Many working fluids for ORC power plants are available. Pentane (R-601) and R245fa are the most used for ORC. In this work, a gene expression programming (GEP) model for estimating thermodynamic properties of pentane (R-601) and R245fa was used. New formulations are presented for determination of the enthalpy and entropy values of two working fluids. The actual results were compared to the results obtained with GEP. The obtained results showed that the formulations are effectively capable of evaluating the thermodynamic properties of working fluids. The GEP-based formulations are simple. These formulations will be helpful for thermodynamic analysis of ORC systems.

关键词： gene expression programming Organic Rankine Cycle Working fluid Pentane R245fa Thermodynamic properties

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：