检索结果-内蒙古大学图书馆

gene expression programming as a basis for new generation of electricity demand prediction models

COMPUTERS & INDUSTRIAL ENGINEERING 2014年第1期74卷 120-128页

作者： Mousavi, Seyyed Mohammad Mostafavi, Elham Sadat Hosseinpour, Fariba Islamic Azad Univ Sci & Res Branch Dept Geog & Urban Planning Tehran Iran Isfahan Univ Technol Dept Ind Engn Esfahan Iran Islamic Azad Univ Fac Econ & Accounting Cent Tehran Branch IAUCTB Tehran Iran

This study proposes a new gene expression programming (GEP) approach for the prediction of electricity demand. The annual population, gross domestic product, stock index, and total revenue from exporting industrial products were used to predict the electricity demand of the same year in Thailand. Several statistical criteria were used to verify the validity of the model. Further, the contributions of the influencing variables to the prediction of the electricity demand were analyzed. Correlation coefficient, root mean squared error and mean absolute percent error were used to evaluate the performance of the model. In addition to its high accuracy, the derived model outperforms regression and other soft computing-based models. (C) 2014 Elsevier Ltd. All rights reserved.

关键词： Electricity demand gene expression programming Prediction

来源：评论

学校读者我要写书评

暂无评论

gene expression programming based formulations for splitting tensile strength of concrete

引用

CONSTRUCTION AND BUILDING MATERIALS 2012年第1期26卷 404-410页

作者： Ozcan, Fatih Nigde Univ Dept Civil Engn TR-51240 Nigde Turkey

In this study, gene expression programming (GEP) formulations for splitting tensile strength (f(spt)) of the cylinder specimens with 150 mm diameter and 300 mm height using compressive strength (f(c)) of concrete cube specimens with 150 mm dimension are developed. Two models, called as GEP-I and GEP-II, are developed for predicting f(spt) by using GEP. The database used in the GEP models is based on experimental data obtained from literature. In the GEP-I model, while f(c) is used as input variable, f(spt) is used as output variable. However, in the GEP-II model, as well as f(c), water-binder ratio (WB) is used as input variables. The data sets used in training and testing stages are randomly selected among all experimental data. The GEP formulations are also validated with additional experimental data other than the data used in training and testing sets of the GEP models. Experimental f(spt) results of concrete specimens are compared with GEP formulations, proposed formulations by some national building codes and the developed regression-based formulation results. The results show that GEP formulations have strong potential as a feasible tool for prediction of the f(spt) from only 150 mm cube f(c) or WB and 150 mm cube f(c) of concrete. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Compressive strength Splitting tensile strength gene expression programming

来源：评论

学校读者我要写书评

暂无评论

gene expression programming for evaluation of aggregate angularity effects on permanent deformation of asphalt mixtures

引用

CONSTRUCTION AND BUILDING MATERIALS 2019年 211卷 470-478页

作者： Leon, Lee P. Gay, Derek UWI Dept Civil & Environm Engn St Augustine Trinidad Tobago

The shape of the aggregate influences the particle interlocking capabilities, thus influencing the deformation behaviour of mixes. The research paper explores the use of gene-expression programming (GEP) as an unconventional approach to predict permanent deformation of asphalt concrete with the inclusion of aggregate angularity. Data for prediction of permanent deformation of dense graded asphalt concrete was obtained through laboratory experiments. The development and analysis of the proposed GEP technique was completed by using laboratory data. The new technique for the assessment of permanent deformation strain with additional angularity factor was developed. The GEP approach concluded satisfactory outcomes of the estimation of permanent deformation when compared to regression analysis. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Aggregate angularity Permanent deformation Asphalt concrete gene expression programming

来源：评论

学校读者我要写书评

暂无评论

gene expression programming with multiple chromosomes

引用

INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2011年第4期14卷 235-241页

作者： Wang, Bo Yao, Min Zhu, Rong Zhejiang Univ Sch Comp Sci Hangzhou Zhejiang Peoples R China Zhejiang Chinese Med Univ Sch Informat Technol Hangzhou Zhejiang Peoples R China Zhejiang Univ Sch Comp Sci & Technol Hangzhou Zhejiang Peoples R China Jiaxing Univ Sch Informat Engn Jiaxing Peoples R China Nanjing Univ State Key Lab Novel Software Technol Nanjing Jiangsu Peoples R China

gene expression programming (GEP) has been widely used in the areas of pattern recognition and knowledge discovery, however, when dealing with complicated problems, it is very time-consuming and the number of generations is large. In order to overcome these drawbacks, this paper proposes a multi-chromosomes GEP algorithm (MC-GEP). Firstly, the individual is composed of multiple chromosomes, each chromosome consists of one or more genes. Secondly, the expression of each chromosome or combinations of several chromosomes may be chosen to indicate the individual. Finally, chromosome recombination is changed and performed orderly like meiosis. Experimental results show that MC-GEP can reduce the running time and the number of generations with respect to the GEP.

关键词： gene expression programming GEP MC-GEP multi-chromosomes

来源：评论

学校读者我要写书评

暂无评论

gene expression programming for parametric optimization of an electrochemical machining process

引用

INTERNATIONAL JOURNAL OF INTERACTIVE DESIGN AND MANUFACTURING - IJIDEM 2023年第2期17卷 649-666页

作者： Mandal, Kishal Kalita, Kanak Chakraborty, Shankar Jadavpur Univ Dept Prod Engn Kolkata India Vel Tech Rangarajan Dr Sagunthala R&D Inst Sci & Dept Mech Engn Avadi India

Due to its capability to generate intricate shape profiles on various electrically conductive difficult-to-machine work materials, electrochemical machining (ECM) process has found immense applications in aerospace, automotive, die making, artillery and surgical instruments manufacturing industries. Like other machining processes, the performance of an ECM process with respect to various product quality characteristics is also influenced by its different input parameters. This paper proposes the novel application of an almost unexplored evolutionary algorithm in the form of gene expression programming for parametric optimization of an ECM process while treating electrolyte concentration, electrolyte flow rate, applied voltage and tool feed rate as the input parameters, and material removal rate (MRR) and average surface roughness (Ra) as the responses. It is noticed that an optimal parametric intermix as electrolyte concentration = 15.1417 g/l, electrolyte flow rate = 6.1846 l/min, applied voltage = 15.94709 V and tool feed rate = 0.99995 mm/min would lead to simultaneous optimization of both the responses. A comparative analysis of its optimization performance in relation to accuracy and variability of the derived solutions, and computational speed against genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO) and artificial bee colony (ABC) optimization techniques validates its superiority over the others. At the derived optimal combination, MRR is increased by 26.14, 3.64, 12.50 and 12.55%, and Ra is reduced by 1.28, 21.97, 21.03 and 7.86% against GA, PSO, ACO and ABC techniques. An optimal Pareto front is also developed to determine the optimal parametric intermixes for having maximum MRR and minimum Ra values. The scatter plots would assist the process engineers in investigating the influences of the input parameters of the considered ECM process on its responses.

关键词： ECM gene expression programming Optimization Process parameter Response

来源：评论

学校读者我要写书评

暂无评论

gene expression programming and one-dimensional chaotic maps

引用

INTERNATIONAL JOURNAL OF MODERN PHYSICS C 2002年第1期13卷 13-24页

作者： Hardy, Y Steeb, WH Rand Afrikaans Univ Int Sch Sci Comp ZA-2006 Auckland Pk South Africa

gene expression programming is applied to find one-dimensional maps. A survey on gene expression programming is also given.

关键词： gene expression programming chromosomes replication chaotic maps

来源：评论

学校读者我要写书评

暂无评论

gene expression programming for Quantum Computing

引用

ACM TRANSACTIONS ON QUANTUM COMPUTING 2023年第4期4卷 1-14页

作者： Alvarez, Gonzalo Bennink, Ryan Irle, Stephan Jakowski, Jacek Oak Ridge Natl Lab POB 2008MS6102 Oak Ridge MS 37831 USA Oak Ridge Natl Lab POB 2008MS6211 Oak Ridge MS 37831 USA Oak Ridge Natl Lab POB 2008MS6493 Oak Ridge MS 37831 USA

We introduce QUANTUMGEP, a scientific computer program that uses gene expression programming (GEP) to find a quantum circuit that either (1) maps a given set of input states to a given set of output states or (2) transforms a fixed initial state to minimize a given physical quantity of the output state. QUANTUMGEP is a driver program that uses evendim, a generic computational engine for GEP, both of which are free and open source. We apply QUANTUMGEP as a powerful solver for MaxCut in graphs and for condensed matter quantum many-body Hamiltonians.

关键词： genetic algorithms gene expression programming quantum computing condensed matter quantum chemistry

来源：评论

学校读者我要写书评

暂无评论

gene expression programming approach to event selection in high energy physics

引用

IEEE TRANSACTIONS ON NUCLEAR SCIENCE 2006年第4期53卷 2221-2227页

作者： Teodorescu, Liliana Brunel Univ Uxbridge UBB 3PH Middx England

gene expression programming is a new evolutionary algorithm that overcomes many limitations of the more established genetic Algorithms and genetic programming. Its first application to high energy physics data analysis is presented. The algorithm was successfully used for event selection on samples with both low and high background level. It allowed automatic identification of selection rules that can be interpreted as cuts applied on the input variables. The signal/background classification accuracy was over 90% in all cases.

关键词： event selection evolutionary algorithms gene expression programming

来源：评论

学校读者我要写书评

暂无评论

gene expression programming and Trading Strategies

Gene Expression Programming and Trading Strategies

引用

9th IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations (AIAI)

作者： Sermpinis, Georgios Fountouli, Anastasia Theofilatos, Konstantinos Karathanasopoulos, Andreas Univ Glasgow Sch Business Adam Smith Bldg Glasgow G12 8QQ Lanark Scotland Univ Patras Dept Comp Engn & Informat GR-26110 Patras Greece Univ East London Business Sch London England

ISBN: (纸本)9783642411410;9783642411427

This paper applies a gene expression programming (GEP) algorithm to the task of forecasting and trading the SPDR Down Jones Industrial Average (DIA), the SPDR S&P 500 ( SPY) and the Powershares Qqq Trust Series 1 (QQQ) exchange traded funds (ETFs). The performance of the algorithm is benchmarked with a simple random walk model (RW), a Moving Average Convergence Divergence (MACD) model, a genetic programming (GP) algorithm, a Multi-Layer Perceptron (MLP), a Recurrent Neural Network (RNN) and a Gaussian Mixture Neural Network (GM). The forecasting performance of the models is evaluated in terms of statistical and trading efficiency. Three trading strategies are introduced to further improve the trading performance of the GEP algorithm. This paper finds that the GEP model outperforms all other models under consideration. The trading performance of GEP is further enhanced when the trading strategies are applied.

关键词： genetic programming gene expression programming Daily Trading DJIA S&P500

来源：评论

学校读者我要写书评

暂无评论

gene expression programming-based multivariate model for earth infrastructure: predicting ultimate bearing capacity of rock socketed shafts in layered soil-rock strata

引用

MODELING EARTH SYSTEMS AND ENVIRONMENT 2024年第4期10卷 5241-5256页

作者： Nawaz, Muhammad Naqeeb Haseeb, Muhammad Qamar, Sana Ullah Hassan, Waqas Shahzad, Arfan Natl Univ Sci & Technol NUST NUST Inst Civil Engn Islamabad 44000 Pakistan Natl Univ Comp & Emerging Sci FAST NUCES Dept Sci & Humanities Chiniot Faisalabad Campus Faisalabad Pakistan

The evaluation of ultimate bearing capacity (Qu) of rock socketed shafts (RSSs) is crucial for the design of foundation systems. This study proposes a new data-driven multivariate formulation using gene expression programming (GEP) to assess Qu of RSSs in layered soil-rock strata. A dataset of 151 points from the literature was used to develop the prediction model. Six influencing features were considered: the material constant for rock (mi), unconfined compression strength (sigma c), geological strength index (GSI), length of socket in soil (Lss), length of socket in rock (Lsr), and diameter of the socket base (d). The model predicts the ultimate bearing capacity factor (Nu). The proposed GEP-based formulation showed high accuracy. For the training data, the correlation coefficient (R) was 0.90, with root mean square error (RMSE), mean absolute error (MAE), relative root mean square error (RRMSE), relative standard error (RSE), and performance index (rho) values of 1.40, 0.98, 0.37, 0.18, and 0.2, respectively. For the testing data, R was 0.86, with RMSE, MAE, RRMSE, RSE, and rho values of 1.37, 0.93, 0.49, 0.26, and 0.26, respectively. The model's efficiency was validated through comparison with existing correlations, sensitivity analysis, and rock socketed shaft test results. The proposed GEP-based model showed significantly improved performance over the ensemble learning (EL) model from the previous study, with a 44.23% higher R value, a 22% lower RMSE, and a 26% lower MAE. Additionally, a computer application was developed to facilitate quick estimation of Nu, enhancing the model's practical applicability in earth systems and infrastructure.

关键词： Ultimate bearing capacity factor Rock socketed shafts Layered soil-rock strata gene expression programming Sensitivity analysis

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：