The article presents regulation possibilities of mechatronic system via Internet and possible improvements of such control using Artificial Neural Network. Due to the development of Internet technique and speed increase of transmission, the inexpensive convenient communication approach is provided for the remote control system The paper also handles the advantages and disadvantages of Internet ...

Abstract— During last few decades’ accurate prediction of protein structural class has been a challenging problem. Efficient and meaningful representation of protein molecule plays a significant role. In this paper Chou’s pseudo amino acid composition along with amphiphillic correlation factor has been used to represent protein data. A simple functionally linked artificial neural network has be...

Tailor-made blanks are sheet metal assemblies with different thicknesses and/or materials and/or surface coatings. A monolithic sheet can be machined to make the required thickness variations that is referred as tailor machined blanks. Due to the thickness variation in tailor machined blanks, laser bending of these blanks is more complicated than monolithic plates. In this article, laser formin...

Automatic control of the robotic manipulator involves study of kinematics and dynamics as a major issue. This paper involves the forward and inverse kinematics of 2-DOF robotic manipulator with revolute joints. In this study the DenavitHartenberg (D-H) model is used to model robot links and joints. Also forward and inverse kinematics solution has been achieved using Artificial Neural Networks f...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

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 the present work, an artificial neural network (ANN) model was used to study the quantitative structure retention relationship (QSRR) of retention index (RI) of some volatile compounds in natural cocoa and conched chocolate powder. Molecular structural descriptors are selected using genetic algorithm to construct the nonlinear QSRR models, kernel partial least squares PLS (KPLS) and Levenber...