In this paper, we present a machine vision system that was developed on the basis of neural networks to identify twelve houseplants. Image processing system was used to extract 41 features of color, texture and shape from the images taken from front and back of the leaves. The features were fed into the neural network system as the recognition criteria and inputs. Multilayer perceptron (MLP) ne...

Nowadays, firms apply the merger and acquisition strategy for gaining synergy, increasing the wealth of stockholders, economics of scales, enhancing efficiency, increasing the ability to research and develop, developing the firm and decreasing the risk. Developing an optimized model with the ability to identify the effective variables on the merger and acquisition process has a significant ...

The paper aims to forecast the Philippine storm frequencies using nonlinear Poisson autoregressive model with exogenous variables. nonlinearity is defined by its kernel which an artificial neural network (ANN) one hidden layer and two output neurons, trained simultaneously semesters ahead for a given input. Furthermore, covariates studied were Average Sea Surface Temperatures in NINO3.4 region ...

Introduction: C. elegans neural network is a good sample for neural networks studies, because its structural details are completely determined. In this study, the virtual neural network of this worm that was proposed by Suzuki et al. for control of movement was reconstructed by adding newly discovered synapses for each of these network neurons. These synapses are newly discovered in the actu...

in this paper we propose a method for solving some well-known classes of lane-emden type equations which are nonlinear ordinary differential equations on the semi-in nite domain. the proposed approach is based on an unsupervised combined arti cial neural networks (ucann) method. firstly, the trial solutions of the differential equations are written in the form of feed-forward neural networks co...

In this paper we present an improved neural network to solve strictly convex quadratic programming(QP) problem. The proposed model is derived based on a piecewise equation correspond to optimality condition of convex (QP) problem and has a lower structure complexity respect to the other existing neural network model for solving such problems. In theoretical aspect, stability and global converge...

Presented paper deals with images of nanotubes that provide a new way of a surface bioactivation of dental titanium implants. The evaluation of selected material parameters forms an important part of material quality assessment. The first step is an image segmentation and object detection. In the following step, object classification is a crucial point in separation object. Various methods coul...