CAJ | 학술논문

针对制造业产品销售时序具有多维、小样本、非线性、多峰等特征，提出一种混沌果蝇支持向量机回归的产品销售预测方法。将混沌理论引入到果蝇优化算法中，从而提高果蝇种群多样性和搜索的遍历性，并在寻优过程中加入混沌扰动，避免搜索过程陷入局部最优，增加持续搜索可行解的能力。并用算例验证了混沌果蝇优化算法（Chaos Fruit Fly Optimization Algorithm，CFOA）的优化性能，通过优化支持向量机回归（Support Vector Regression， SVR）的参数构建销售预测模型，进行了汽车零部件销售预测。结果表明基于混沌果蝇支持向量机回归的产品销售预测方法是有效可行的。
침대제조업산품소수시서구유다유、소양본、비선성、다봉등특정，제출일충혼돈과승지지향량궤회귀적산품소수예측방법。장혼돈이론인입도과승우화산법중，종이제고과승충군다양성화수색적편력성，병재심우과정중가입혼돈우동，피면수색과정함입국부최우，증가지속수색가행해적능력。병용산례험증료혼돈과승우화산법（Chaos Fruit Fly Optimization Algorithm，CFOA）적우화성능，통과우화지지향량궤회귀（Support Vector Regression， SVR）적삼수구건소수예측모형，진행료기차령부건소수예측。결과표명기우혼돈과승지지향량궤회귀적산품소수예측방법시유효가행적。
Aiming at the product sale time series of manufacturing enterprise with multi-dimension, small samples, nonlin-earity, multi-peak, etc., a product sale forecasting method based on the chaotic fruit fly support vector regression is presented. Chaos mapping theory is combined with fruit fly optimization algorithm, thereby increasing fruit fly population diversity and search ergodicity, and chaos perturbation is added in the optimization process, which avoids the search being trapped in local optimum and increases the ability to search for feasible solutions. This paper verifies optimal performance of Chaos Fruit Fly Optimization Algorithm(CFOA)by examples, then applies CFOA to optimize parameters of Support Vector Regression(SVR), and builds sales forecasting model. The results of application show this model in sales prediction of auto parts is effective and feasible.