孪生支持向量机(twin support vector machine,TWSVM)是在支持向量机的基础上产生的机器学习算法,具有训练速度快、分类性能优越等优点。但是孪生支持向量机无法很好地处理参数选择问题,不合适的参数会降低分类能力。人工鱼群算法(artif...孪生支持向量机(twin support vector machine,TWSVM)是在支持向量机的基础上产生的机器学习算法,具有训练速度快、分类性能优越等优点。但是孪生支持向量机无法很好地处理参数选择问题,不合适的参数会降低分类能力。人工鱼群算法(artificial fish swarm algorithm,AFSA)是一种群智能优化算法,具有较强的全局寻优能力和并行处理能力。本文将孪生支持向量机与人工鱼群算法结合,来解决孪生支持向量机的参数选择问题。首先将孪生支持向量机的参数作为人工鱼的位置信息,同时将分类准确率作为目标函数,然后通过人工鱼的觅食、聚群、追尾和随机行为来更新位置和最优解,最后迭代结束时得到最优参数和最优分类准确率。该算法在训练过程中自动确定孪生支持向量机的参数,避免了参数选择的盲目性,提高了孪生支持向量机的分类性能。展开更多
This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port.To eliminate the influence of outliers,local outlier factor(lof) is extended to detect outliers in time series,and then ...This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port.To eliminate the influence of outliers,local outlier factor(lof) is extended to detect outliers in time series,and then different dummy variables are constructed to capture the effect of outliers based on domain knowledge.Next,a hybrid forecasting model combining projection pursuit regression(PPR) and genetic programming(GP) algorithm is proposed.Finally,the hybrid model is applied to forecasting container throughput of Qingdao Port and the results show that the proposed method significantly outperforms ANN,SARIMA,and PPR models.展开更多
文摘孪生支持向量机(twin support vector machine,TWSVM)是在支持向量机的基础上产生的机器学习算法,具有训练速度快、分类性能优越等优点。但是孪生支持向量机无法很好地处理参数选择问题,不合适的参数会降低分类能力。人工鱼群算法(artificial fish swarm algorithm,AFSA)是一种群智能优化算法,具有较强的全局寻优能力和并行处理能力。本文将孪生支持向量机与人工鱼群算法结合,来解决孪生支持向量机的参数选择问题。首先将孪生支持向量机的参数作为人工鱼的位置信息,同时将分类准确率作为目标函数,然后通过人工鱼的觅食、聚群、追尾和随机行为来更新位置和最优解,最后迭代结束时得到最优参数和最优分类准确率。该算法在训练过程中自动确定孪生支持向量机的参数,避免了参数选择的盲目性,提高了孪生支持向量机的分类性能。
文摘This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port.To eliminate the influence of outliers,local outlier factor(lof) is extended to detect outliers in time series,and then different dummy variables are constructed to capture the effect of outliers based on domain knowledge.Next,a hybrid forecasting model combining projection pursuit regression(PPR) and genetic programming(GP) algorithm is proposed.Finally,the hybrid model is applied to forecasting container throughput of Qingdao Port and the results show that the proposed method significantly outperforms ANN,SARIMA,and PPR models.
