计算机系统应用
計算機繫統應用
계산궤계통응용
APPLICATIONS OF THE COMPUTER SYSTEMS
2014年
7期
161-164
,共4页
软件可靠性预测%粒子群优化算法%人工蜂群算法%支持向量机
軟件可靠性預測%粒子群優化算法%人工蜂群算法%支持嚮量機
연건가고성예측%입자군우화산법%인공봉군산법%지지향량궤
software reliability prediction%particle swarm optimization%artificial bee colony algorithm%support vector machine
软件可靠性预测是指在软件开发初期对软件中各模块出错的可能性进行预测，对提高软件的可信性具有重要意义。提出了一种基于粒子群与人工蜂群优化支持向量机的软件可靠性预测模型，将粒子群优化算法与人工蜂群算法相结合的混合算法引入到支持向量机的参数选择中，提高软件可靠性预测的效果。实验结果表明，该模型比BP网络预测模型、粒子群优化支持向量机等预测模型收敛速度更快、预测精度更高，能更好的进行软件可靠性预测。
軟件可靠性預測是指在軟件開髮初期對軟件中各模塊齣錯的可能性進行預測，對提高軟件的可信性具有重要意義。提齣瞭一種基于粒子群與人工蜂群優化支持嚮量機的軟件可靠性預測模型，將粒子群優化算法與人工蜂群算法相結閤的混閤算法引入到支持嚮量機的參數選擇中，提高軟件可靠性預測的效果。實驗結果錶明，該模型比BP網絡預測模型、粒子群優化支持嚮量機等預測模型收斂速度更快、預測精度更高，能更好的進行軟件可靠性預測。
연건가고성예측시지재연건개발초기대연건중각모괴출착적가능성진행예측，대제고연건적가신성구유중요의의。제출료일충기우입자군여인공봉군우화지지향량궤적연건가고성예측모형，장입자군우화산법여인공봉군산법상결합적혼합산법인입도지지향량궤적삼수선택중，제고연건가고성예측적효과。실험결과표명，해모형비BP망락예측모형、입자군우화지지향량궤등예측모형수렴속도경쾌、예측정도경고，능경호적진행연건가고성예측。
Software reliability prediction can predict the fault-prone modules at the early age of sofrware development. And it is important to improve the credibility of the software. In order to improve the effect of software reliability prediction, this paper proposes a PSOABC-SVM model to predict software reliability, and puts forward a model of predicting the software reliability based on PSOABC-SVM. The experimental results show that this model can achieve more precise prediction results than other prediction models such as BP neural network and PSO-SVM. The PSOABC-SVM model is more applicable for software reliability prediction.
