A Joint Optimization of Momentum Item and Levenberg-Marquardt Algorithm to Level Up the BPNN’s Generalization Ability
نویسندگان
چکیده
منابع مشابه
Levenberg Marquardt ( LM ) Algorithm 1 –
1 – Introduction Parameter estimation for function optimization is a well established problem in computing, as there are countless applications in practice. For this work, we will focus specifically in implementing a distributed and parallel implementation of the Levenberg Marquardt algorithm, which is a well established numerical solver for function approximation given a limited data set. Para...
متن کاملOn a Riemannian Version of the Levenberg-Marquardt Algorithm
*This research was carried out as part of NWO research project 611-304-019, 'Address: Free University, Department of Economics and Econometrics, De Boelelaan 1105, 1081 HV Amsterdam, The Netherlands. E-mail: [email protected].
متن کاملOptimization in companion search spaces: the case of cross-entropy and the Levenberg-Marquardt algorithm
We present a new learning algorithm for the supervised training of multilayer perceptrons for classification that is significantly faster than any previously known method. Like existing methods, the algorithm assumes a multilayer perceptron with a normalized exponential (softmax) output trained under a cross-entropy criterion. However, this output-criteria pairing turns out to have poor propert...
متن کاملA New Cuckoo Search Based Levenberg-Marquardt (CSLM) Algorithm
Back propagation neural network (BPNN) algorithm is a widely used technique in training artificial neural networks. It is also a very popular optimization procedure applied to find optimal weights in a training process. However, traditional back propagation optimized with Levenberg marquardt training algorithm has some drawbacks such as getting stuck in local minima, and network stagnancy. This...
متن کاملA modified Levenberg–Marquardt algorithm for quasi-linear geostatistical inversing
The Quasi-Linear Geostatistical Approach is a method of inverse modeling to identify parameter fields, such as the hydraulic conductivity in heterogeneous aquifers, given observations of related quantities like hydraulic heads or arrival times of tracers. Derived in the Bayesian framework, it allows to rigorously quantify the uncertainty of the identified parameter field. Since inverse modeling...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Mathematical Problems in Engineering
سال: 2014
ISSN: 1024-123X,1563-5147
DOI: 10.1155/2014/653072