the purpose of this research is to detect manipulation of stock prices in tehran stock exchange that it has been done through hybrid genetic algorithm-artificial neural network (ann-ga) model and the simplified quadratic discriminant function (sqdf) model. in this study, the variables of price, trading volume and free float stock to match the results of the model and the actual data of price ma...

An important reason for the continued popularity of Artificial Neural Networks (ANNs) in the machine learning community is that the gradient-descent backpropagation procedure gives ANNs a locally optimal change procedure and, in addition, a framework for understanding the ANN learning performance. Genetic programming (GP) is also a successful evolutionary learning technique that provides powerf...

background and objectives: rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. materials and met...

Liquefaction of soil is one of the major causes for the significant damages to the buildings, lifeline systems and harbor facilities caused by the earthquakes. At present artificial intelligence techniques such as artificial neural network (ANN) and support vector machine (SVM) based models are found to be more efficient compared to statistical methods. The present study discusses about the eva...

Our humanoid robot learns to provide position estimates of objects placed on a table, even while the robot is moving its torso, head and eyes (cm range accuracy). These estimates are provided by trained artificial neural networks (ANN) and a cartesian genetic programming (GP) method, based solely on the inputs from the two cameras and the joint encoder positions. No prior camera calibration and...

this study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ann) in broiler chicken. artificial neural networks (anns) are powerful tools for modeling systems in a wide range of applications. the ann model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...

We implemented a method to improve the accuracy of a genetic program (GP) for classifying an epistatic data population by limiting the number of population features passed to the GP. An epistatic population was generated and used, where the correct combination of “true” features was necessary in order to correctly classify each member of the population. Our method of limiting the number of feat...

Background and Objectives: Rheological characteristics of dough are important for achieving useful information about raw-material quality, dough behavior during mechanical handling, and textural characteristics of products. Our purpose in the present research is to apply soft computation tools for predicting the rheological properties of dough out of simple measurable factors. Materials and Me...