MODEL NEURAL NETWORK BERBASIS FORWARD SELECTION UNTUK PREDIKSI JUMLAH PRODUKSI MINYAK KELAPA
نویسندگان
چکیده
منابع مشابه
Feed Forward Artificial Neural Network Model to Estimate the TPH Removal Efficiency in Soil Washing Process
Background & Aims of the Study: A feed forward artificial neural network (FFANN) was developed to predict the efficiency of total petroleum hydrocarbon (TPH) removal from a contaminated soil, using soil washing process with Tween 80. The main objective of this study was to assess the performance of developed FFANN model for the estimation of TPH removal. Mater...
متن کاملModeling SMA actuated systems based on Bouc-Wen hysteresis model and feed-forward neural network
Despite the fact that shape-memory alloy (SMA) has several mechanical advantages as it continues being used as an actuator in engineering applications, using it still remains as a challenge since it shows both non-linear and hysteretic behavior. To improve the efficiency of SMA application, it is required to do research not only on modeling it, but also on control hysteresis behavior of these m...
متن کاملSignal Prediction by Layered Feed - Forward Neural Network (RESEARCH NOTE).
In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...
متن کاملModel Selection for Neural Network Classification
Classification rates on out-of-sample predictions can often be improved through the use of model selection when fitting a model on the training data. Using correlated predictors or fitting a model of too high a dimension can lead to overfitting, which in turn leads to poor out-of-sample performance. I will discuss methodology using the Bayesian Information Criterion (BIC) of Schwarz (1978) that...
متن کاملFeed forward neural network entities
Feed Forward Neural Networks (FFNNs) are computational techniques inspired by the physiology of the brain and used in the approximation of general mappings from one nite dimensional space to another. They present a practical application of the theoretical resolution of Hilbert's 13 th problem by Kolmogorov and Lorenz, and have been used with success in a variety of applications. However, as the...
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: ILKOM Jurnal Ilmiah
سال: 2017
ISSN: 2548-7779,2087-1716
DOI: 10.33096/ilkom.v9i3.149.239-243