A Neural Networks Approach to Inverse Optimization

Kinematic Synthesis of Parallel Manipulator via Neural Network Approach

In this research, Artificial Neural Networks (ANNs) have been used as a powerful tool to solve the inverse kinematic equations of a parallel robot. For this purpose, we have developed the kinematic equations of a Tricept parallel kinematic mechanism with two rotational and one translational degrees of freedom (DoF). Using the analytical method, the inverse kinematic equations are solved for spe...

HYBRID ARTIFICIAL NEURAL NETWORKS BASED ON ACO-RPROP FOR GENERATING MULTIPLE SPECTRUM-COMPATIBLE ARTIFICIAL EARTHQUAKE RECORDS FOR SPECIFIED SITE GEOLOGY

The main objective of this paper is to use ant optimized neural networks to generate artificial earthquake records. In this regard, training accelerograms selected according to the site geology of recorder station and Wavelet Packet Transform (WPT) used to decompose these records. Then Artificial Neural Networks (ANN) optimized with Ant Colony Optimization and resilient Backpropagation algorith...

Optimizing Multiple Response Problem Using Artificial Neural Networks and Genetic Algorithm

  This paper proposes a new intelligent approach for solving multi-response statistical optimization problems. In most real world optimization problems, we are encountered adjusting process variables to achieve optimal levels of output variables (response variables). Usual optimization methods often begin with estimating the relation function between the response variable and the control variab...

GMDH Type Neural Networks and Their Application to the Identification of the Inverse Kinematics Equations of Robotic Manipulators (RESEARCH NOTE)

Traffic Signal Prediction Using Elman Neural Network and Particle Swarm Optimization

Prediction of traffic is very crucial for its management. Because of human involvement in the generation of this phenomenon, traffic signal is normally accompanied by noise and high levels of non-stationarity. Therefore, traffic signal prediction as one of the important subjects of study has attracted researchers’ interests. In this study, a combinatorial approach is proposed for traffic signal...