In this work, the artificial neural networks (ANN) technology was applied to the simulation of oleuropein extraction process. For this technology, a 3-layer network structure is applied, and the operation factors such as  amount  of  flow  intensity  ratio,  temperature,  residence  time,  and  pH  are  used  as  input  variables  of  the network,  whereas  the  extraction  yield  is  considere...

We show that a reinforcement learning method, adaptive critic based approximate dynamic programming, can be used to create fuzzy policy managers for adaptive control of a logistic system. Two different architectures are used for the policy manager, a feed forward neural network, and a fuzzy rule base. For both architectures, policy managers are trained that outperform LP and GA derived fixed po...

a neural network with feed forward topology and back propagation algorithm was used to investigate the effect of composition on mechanical properties in api x65 microalloyed steel (used in manufacturing of large diameter pipes). experimental data was obtained by cutting 100 specimens from pipes manufactured in industrial scale (with similar heats and manufacturing processes). the chemical analy...

The bulk of water pipes experience major degradation and deterioration problems. This research aims at estimating the condition in Shattora Shaker Al-Bahery’s distribution networks, Egypt. developed models involve training Elman neural network (ENN) feed-forward (FFNN) coupled with particle swarm optimization (PSO), genetic algorithms (GA), sine cosine algorithm (SCA), teaching-learning-based (...

In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN–GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Va...

The paper discusses about the Choquet Fuzzy Integral (CFI) based identification and control of a Real Time Dynamical System. The plant is modeled using Choquet fuzzy Integral based Neural Network with Gradient Descent as learning algorithm. This model is used for designing and simulating CFI based controller. Then this designed controller is implemented on real time system through MATLAB. Final...

the functions employed in an estimation of costly measured soil properties from either widely available or more easily obtained basic soil properties are referred to as pedotransfer functions. to develop pedotransfer functions, one can use multivariate regression, neural networks and neuro-fuzzy models. to make a comparison among the mentioned models, 153 soil samples were collected from soils ...

This paper investigates the ability of several alternate models of Artificial Neural Network (ANN) to predict the probability of occurrence of Hypertension (HT) in a mixed patient population. To do this a two-layer feed-forward neural network with 13 inputs and 1 output was created with a single hidden layer . Different types of networks structures, such as NEWFF (feed-forward back propagation ...

-Fuzzy ARTMAP is one of the recently proposed neural network paradigm where the fuzzy logic is incorporated. In this paper, we compare the Fuzzy ARTMAP neural network and the well-known back-propagation based Multi-layer perceptron (MLP), in the context of hand-written character recognition problem. The results presented in this paper shows that the Fuzzy ARTMAP out-performs its counterpart, bo...