نتایج جستجو برای: levenberg marquardt artificial neural network

تعداد نتایج: 1027510  

2012
E. Lopez-Sandoval A. Mello J. J. Godina-Nava A. R. Samana

We present a deterministic and direct method inspired by the ideas of the Power Series Method applied to solve a chemical kinetics inverse problem. We use a power series as a trial solution approximation, and the data is used as initial condition and boundary value condition to solve the coupled differential equation of chemical kinetics and to obtain the rate constant parameters. The approach ...

2013
David Scanlan David Mulvaney

This paper makes two principal contributions. The first is that there appears to be no previous a description in the research literature of an artificial neural network implementation on a graphics processor unit (GPU) that uses the Levenberg-Marquardt (LM) training method. The second is an initial attempt at determining when it is computationally beneficial to exploit a GPU’s parallel nature i...

2015
Nazri Mohd Nawi M. Z. Rehman Abdullah Khan Arslan Kiyani Haruna Chiroma Tutut Herawan

The Levenberg-Marquardt (LM) gradient descent algorithm is used extensively for the training of Artificial Neural Networks (ANN) in the literature, despite its limitations, such as susceptibility to the local minima that undermine its robustness. In this paper, a bioinspired algorithm referring to the Bat algorithm was proposed for training the ANN, to deviate from the limitations of the LM. Th...

A. Farmany H. Noorizadeh

Genetic algorithm and partial least square (GA-PLS), the kernel PLS (KPLS) and Levenberg-Marquardt artificial neural network (L-M ANN) techniques were used to investigate the correlationbetween retention time (RT) and descriptors for 15 nanoparticle compounds which obtained by thecomprehensive two dimensional gas chromatography system (GC x GC). Application of thedodecanethiol monolayer-protect...

S. T . A. Niaki Vahid Arabzadeh Vida Arabzadeh

One of the most important processes in the early stages of construction projects is to estimate the cost involved. This process involves a wide range of uncertainties, which make it a challenging task. Because of unknown issues, using the experience of the experts or looking for similar cases are the conventional methods to deal with cost estimation. The current study presents data-driven metho...

2014
Nazri Mohd. Nawi Abdullah Khan M. Z. Rehman

RNNs have local feedback loops within the network which allows them to shop earlier accessible patterns. This network can be educated with gradient descent back propagation and optimization technique such as second-order methods; conjugate gradient, quasi-Newton, Levenberg-Marquardt have also been used for networks training [14, 15]. But still this algorithm is not definite to find the global m...

The quantitative structure-retention relationship (QSRR) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. The genetic algorithm (GA) was employed to select the variables that resulted in the best-fitted models. After the variables were selected, the linear multi...

سجادی, سید جواد , صبوری, حسین ,

Crop yield prediction has an important role in agricultural policies such as specification of the crop price. Crop yield prediction researches have been based on regression analysis. In this research canola yield was predicted using Artificial Neural Networks (ANN) using 11 crop year climate data (1998-2009) in Gonbad-e-Kavoos region of Golestan province. ANN inputs were mean weekly rainfall, m...

In the present paper, informatics-aided quantitative structure activity relationship (QSAR) models using genetic algorithm-partial least square (GA-PLS), genetic algorithm-Kernel partial least square (KPLS), and Levenberg-Marquardt artificial neural network (LM ANN) approach were constructed to access the antimalarial activity (pIC50) of 2,5-diaminobenzophenone derivatives. Comparison of errors...

Journal: :Neurocomputing 2013
Shahrokh Asadi Jamal Shahrabi Peyman Abbaszadeh Shabnam Tabanmehr

This paper proposes a hybrid intelligent model for runoff prediction. The proposed model is a combination of data preprocessing methods, genetic algorithms and levenberg–marquardt (LM) algorithm for learning feed forward neural networks. Actually it evolves neural network initial weights for tuning with LM algorithm by using genetic algorithm. We also use data pre-processing methods such as dat...

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