CAJ | 학술논문

公交客流是公交规划和运营调度的基础。针对短期公交客流的非线性、随机性和复杂性及支持向量机单核核函数自适应能力较弱的特点，提出一种基于多核最小二乘支持向量机的公交客流预测方法。该方法既考虑到了公交客流的历史数据规律，又顾及到短期公交客流的时变特性，充分利用了相关参数的知识信息。为了保证模型的自适应能力和提高模型的泛化能力，作者提出了综合评价指标，并采用改进遗传算法实现向量机参数优化。最后，结合LS．SVM工具箱，在MATLAB平台上实现长春市短期公交客流的预测。预测结果表明，提出的多核预测方法具有较高的准确性、较强的鲁棒性和自适应能力，在公交客流预测中有具有较好的应用价值。
공교객류시공교규화화운영조도적기출。침대단기공교객류적비선성、수궤성화복잡성급지지향량궤단핵핵함수자괄응능력교약적특점，제출일충기우다핵최소이승지지향량궤적공교객류예측방법。해방법기고필도료공교객류적역사수거규률，우고급도단기공교객류적시변특성，충분이용료상관삼수적지식신식。위료보증모형적자괄응능력화제고모형적범화능력，작자제출료종합평개지표，병채용개진유전산법실현향량궤삼수우화。최후，결합LS．SVM공구상，재MATLAB평태상실현장춘시단기공교객류적예측。예측결과표명，제출적다핵예측방법구유교고적준학성、교강적로봉성화자괄응능력，재공교객류예측중유구유교호적응용개치。
Public transportation flow is the basic data for the public transport planning and operation scheduling. Based on the multiple-kernel least square support vector machine （MLS-SVM）, the paper presented a new pubic transportation flow prediction model according to the non-linear, stochastic and complex characteristics of short-term public traffic flow. The proposed model not only considered the history data, but also took the character of the short-term public flow into account. In order to improve the suitability of the tradition model, a new evaluation index was proposed to portray the training performance of MLS-SVM. Crossover and mutation was modified with the genetic algorithm （GA）, then using the improved CA optimized the penalty parameter and nuclear parameter. The model was applied to Chang-chun city, the result showed that the proposed model had satisfactory perform ache and robustness, and had good potential for predicting the short-term public transportation flow.