摘要
ＡｄａｐｔｉｖｅＬｅａｒｎｉｎｇＲａｔｅＯｐｔｉｍｉｚａｔｉｏｎＢＰＡｌｇｏｒｉｔｈｍｗｉｔｈＬｏｇａｒｉｔｈｍｉｃＯｂｊｅｃｔｉｖｅＦｕｎｃｔｉｏｎＬｉＣｈｕｎｙｕ（李春雨）ＳｈｅｎｇＺｈａｏｈａｎ（盛昭瀚）（ＥｃｏｎｏｍｉｃＭａｎａｇｅｍｅｎｔＳ...
This paper presents an improved BP algorithm. The approach can reduce the amount of computation by using the logarithmic objective function. The learning rate μ(k) per iteration is determined by dynamic optimization method to accelerate the convergence rate. Since the determination of the learning rate in the proposed BP algorithm only uses the obtained first order derivatives in standard BP algorithm(SBP), the scale of computational and storage burden is like that of SBP algorithm,and the convergence rate is remarkably accelerated. Computer simulations demonstrate the effectiveness of the proposed algorithm
