基于遺傳神經(jīng)網(wǎng)絡(luò)的路面使用性能評價預(yù)測
發(fā)布時間：2018-10-19 09:04
【摘要】：基于遺傳神經(jīng)網(wǎng)絡(luò)算法,在進行高速公路路面使用性能評價與預(yù)測時,引入遺傳神經(jīng)網(wǎng)絡(luò),建立高速公路路面使用性能評價與預(yù)測模型,通過該模型,評價和預(yù)測了吉林某高速公路路面使用性能。結(jié)果表明:與BP網(wǎng)絡(luò)預(yù)測PCI的結(jié)果相比,遺傳神經(jīng)網(wǎng)絡(luò)預(yù)測PCI的結(jié)果與高速路面PCI實際值誤差縮小更明顯,這表明遺傳神經(jīng)網(wǎng)絡(luò)模型預(yù)測精度得到很大程度提高。測試結(jié)果說明,本研究提出的遺傳神經(jīng)網(wǎng)絡(luò)預(yù)測方法是可行的,它可以作為高速路面一種有效預(yù)測手段,提供科學(xué)方法進行公路路面使用性能的評價與預(yù)測。
[Abstract]:Based on genetic neural network algorithm, the evaluation and prediction model of expressway pavement performance is established by introducing genetic neural network in the evaluation and prediction of expressway pavement performance. The pavement performance of a highway in Jilin province is evaluated and forecasted. The results show that compared with the results of PCI prediction by BP neural network, the error of PCI prediction by genetic neural network is much smaller than that of PCI on high speed pavement, which indicates that the prediction accuracy of genetic neural network model has been improved greatly. The test results show that the genetic neural network prediction method proposed in this paper is feasible and can be used as an effective method to predict the performance of highway pavement.
【作者單位】： 江西科技學(xué)院;
【分類號】：U416.2
本文編號：2280698
[Abstract]:Based on genetic neural network algorithm, the evaluation and prediction model of expressway pavement performance is established by introducing genetic neural network in the evaluation and prediction of expressway pavement performance. The pavement performance of a highway in Jilin province is evaluated and forecasted. The results show that compared with the results of PCI prediction by BP neural network, the error of PCI prediction by genetic neural network is much smaller than that of PCI on high speed pavement, which indicates that the prediction accuracy of genetic neural network model has been improved greatly. The test results show that the genetic neural network prediction method proposed in this paper is feasible and can be used as an effective method to predict the performance of highway pavement.
【作者單位】： 江西科技學(xué)院;
【分類號】：U416.2
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