In the present study, a gene expression programming algorithm has been applied to propose new and accurate correlations for estimating total emissivity of CO2-H2O homogeneous mixtures in air-fuel combustion environmen...
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In the present study, a gene expression programming algorithm has been applied to propose new and accurate correlations for estimating total emissivity of CO2-H2O homogeneous mixtures in air-fuel combustion environment without soot formation at atmospheric condition. The main parameters of the correlations include temperature (T: 300-2500 K), partial pressure of water vapor (p(w): 2.0265-20.265 kPa), partial pressure of carbon dioxide (p(c): 4.053-20.265 kPa), and mean beam length (L: 0.01-25 m). The RADCAL statistical narrow-band model was used in order to generate 78,000 values of total emissivity to be used as the benchmark data for the correlations. 34,620 total emissivity data points were selected for developing the correlations and 43,380 data points were selected for the optimization and testing the capability of the correlations. All the benchmark data were split into two sub-data sets based on temperature (i.e., the first data set: 300 K <= T <1200 K, the second data set: 1200 K <= T <= 2500 K). For each sub-data set, different correlations have been developed. The average absolute relative deviations of the estimated results from the benchmark data are 3.6% of the low temperature, and 3.9% of the high temperature data sets.
gene expression programming (GEP) is a new evolutionary algorithm, which has the very good applications in the field of function finding. In view of the insufficiency of traditional GEP, this paper puts forward an imp...
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ISBN:
(纸本)9781509000227
gene expression programming (GEP) is a new evolutionary algorithm, which has the very good applications in the field of function finding. In view of the insufficiency of traditional GEP, this paper puts forward an improved gene expression programming algorithm based on hybrid strategy (HSI-GEP). This paper has two improvements: (1) using mirror and reset mechanism to replace the inferior individuals of population, to improve the quality and the diversity of population;(2) introducing the clonal selection before tournament selection in order to improve the mining ability of algorithm about the superior individuals. The experiments compared with the improved GEP from authoritative literatures about function finding problems have been carried on, and the results show that HSI-GEP is of high quality, has fast convergence rate and obvious competitiveness.
Metrological parameter prediction is an important task carried out by metrological researchers and water resource analyst for the estimation of water demand, water resource planning, management and operation. Accurate...
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ISBN:
(纸本)9781467397544
Metrological parameter prediction is an important task carried out by metrological researchers and water resource analyst for the estimation of water demand, water resource planning, management and operation. Accurate predictions of these parameters are still an open problem. M5 model tree and gene expression programming are two popular machine learning techniques which are considered as white-box model. In this paper, we have applied two machine learning techniques, such as M5 model tree and gene expression programming, for the prediction of various metrological parameters at a weather station. Among these two techniques, one is better over other for the prediction of a set of parameters.
The population diversity greatly affects the evolutionary efficiency and solution quality of gene expression programming algorithm. Population diversity should be preserved by keeping certain distance between individu...
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ISBN:
(纸本)9781509000227
The population diversity greatly affects the evolutionary efficiency and solution quality of gene expression programming algorithm. Population diversity should be preserved by keeping certain distance between individuals in the population. Edit distance can describe the similarity of individuals well. Crossover is a way to create and maintain the distance of the individuals. In this paper, we propose two edit distance based crossover operators. Experimental results show that the proposed farthest edit distance based crossover operator is able to preserve the diversity of population and solve the optimization problem more efficiently.
This paper aims to model system of ordinary differential equations by using a new hybrid gene expression programming algorithm. gene expression programming is a recently developed evolutionary computation method for m...
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ISBN:
(纸本)9781479986460
This paper aims to model system of ordinary differential equations by using a new hybrid gene expression programming algorithm. gene expression programming is a recently developed evolutionary computation method for model learning and knowledge discovery. The hybrid algorithm combined immune clonal selection algorithm and memetic algorithm with gene expression programming to find not only the structure of system of differential equations but also optimize its constant parameters. The idea of immune clone principle is incorporated into the evolution process to enhance the diversity of population and the memetic algorithm is introduced to improve the ability of local search. Experiments on benchmark problems have shown that the hybrid approach is able to provide highly competitive results compared with that of conventional genetic programming applied to this problem.
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 pr...
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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.
Accurate forecasting of construction and demolition waste (CDW) generation could provide valuable information for the planning, design, and management of CDW at municipal levels. However, the lack of reliable forecast...
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Accurate forecasting of construction and demolition waste (CDW) generation could provide valuable information for the planning, design, and management of CDW at municipal levels. However, the lack of reliable forecasting approaches and historical records makes it difficult to predict the amount of CDW for a long-or short-term plan. To effectively tackle the CDW forecasting problem, a novel computer-based prediction model, gene expression programming (GEP), is introduced and tested. With the CDW and other data on predictor variables from the last two decades, the amount of CDW is forecasted in this study. Results and findings obtained from this research show that GEP is an effective model for predicting waste generation, with lower average forecasting error than the multiple linear model and the artificial neural network. Research issues related to model selection, training, and validation are also discussed in the paper. (C) 2014 American Society of Civil Engineers.
Software aging, with the growing software complexity, which can cause the degradation of performance and even software failure, has never been able to be avoided. In order to monitor the software aging of server, some...
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Software aging, with the growing software complexity, which can cause the degradation of performance and even software failure, has never been able to be avoided. In order to monitor the software aging of server, some researchers proposed different modeling methods, such as linear regression and auto-regressive and moving average (ARMA) model, to analyze and predict the performance. However, these models cannot express the combined effects of a variety of resources on system performance. In this paper, a dynamic modeling algorithm based on gene expression programming (GEP) theory is put forward. The GEP model can monitor, evaluate and predict the system performance by building the direct relationship between some performance index and multiple computing resources including the utilization of CPU and memory, I/O performance, network transmission, etc. In addition, the new GEP model can be adjusted to trace the performance trend and the running state of system by moving window strategy. Finally, three experiments are designed and the results demonstrate that the GEP model can express the overall trend with essential details, which will have higher precision and practicability than those of traditional models when the trend of data has complex changes, and the multi-stage GEP model can be established to analyze and predict the healthy state of system during the process of aging.
This paper proposes ground-motion prediction equations(GMPEs) for the horizontal component of earthquake in Iranian plateau. These equations present the velocity and acceleration response spectra at 5% damping ratio a...
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This paper proposes ground-motion prediction equations(GMPEs) for the horizontal component of earthquake in Iranian plateau. These equations present the velocity and acceleration response spectra at 5% damping ratio as continuous period functions, within range of 0.1 to 4 seconds. So far many equations have been presented and the recent suggested proportions are functions of several parameters. In this research, due to easy usage and lack of information in Iran, only the magnitude of earthquake, the distance between earthquake source and the location and the ground type are used as important factors. Iranian plateau is divided into two zones: Alborz-Central Iran and Zagros, each of which is divided into rock and soil region according to the ground type. Regarding the fact that the occurred and reported earthquakes in Iran are shallow, surface wave magnitude (Ms) is used in this study. Moreover, hypocentral distance is considered as distance between the earthquake source and the location. To obtain the velocity and acceleration response spectra, a gene expression programming(GEP) algorithm is used which utilizes no constant regression model and the model is acquired smartly as a continuous period function. The consequences show a consistency with high proportionality coefficient among the observed and anticipated results.
In this paper,We studied the gene expression programming, on the analysis of the structure of geneexpression trees, finally, the target feature recognition based on gene expression programming experiment and simulati...
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In this paper,We studied the gene expression programming, on the analysis of the structure of geneexpression trees, finally, the target feature recognition based on gene expression programming experiment and simulation. The results show that the GEP algorithm for identification of unknown nonlinear systems is feasible.
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