CAJ | 학술논문

　　自锚式悬索桥造型美观，且不需要庞大的锚碇。其将主缆锚固于加劲梁上，受力发生了极大的变化。因此，研究自锚式悬索桥的可靠性十分必要。采用 BP 神经网络法拟合可靠度计算的极限状态函数，引入粒子群算法优化神经网络法的初始权值，实现函数拟合的双优化，新算法则利用 MATLAB 编程实现。极限状态函数显化后，结合蒙特卡洛法计算自锚式悬索桥在正常使用极限状态下的可靠度。
　　자묘식현색교조형미관，차불수요방대적묘정。기장주람묘고우가경량상，수력발생료겁대적변화。인차，연구자묘식현색교적가고성십분필요。채용 BP 신경망락법의합가고도계산적겁한상태함수，인입입자군산법우화신경망락법적초시권치，실현함수의합적쌍우화，신산법칙이용 MATLAB 편정실현。겁한상태함수현화후，결합몽특잡락법계산자묘식현색교재정상사용겁한상태하적가고도。
The self-anchored suspension bridge has the adva-ntages of beautiful appearance, and does not need huge anchor. The main cable is anchored in the stiffening girder, its stress changed. Therefore, study on the reliability of self-anchored suspension bridge is very necessary. Using BP neural networ-k method to fit the reliability calculation of the limit state func-tion, bringing in the initial weight of particle swarm optimiza-tion neural network method, realize the dual optimization func-tion fit ing, a new algorithm using MATLAB programming. To manifest the limit state function, calculate the self-anchored suspension bridge in reliability under serviceability limit states with Monte Carlo method.