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...

The review focuses on applications of artificial neural networks (ANNs) in various subsystems of pulp and paper making processes. Some applications are pertinent to modeling of pulping, bleaching and energy conservation process while others are related to control of refining, washing of brown stock, combustion of black liquor, lime kiln operation, grade changes and quality control. A general al...

Gas-liquid reactions occupy a large share of the chemical reactions that are carried out industrially. The estimation of reaction rate is the most primary but complex task and is a prerequisite in design & scaling up of reactors. Reaction rate is a function of number of parameters that include flow rates of gas and liquid phases, concentration of reactants and interfacial surface area, among ot...

In this article different types of artificial neural networks (ANN) were used for CNTFET (carbon nanotube transistors) simulation. CNTFET is one of the most likely alternatives to silicon transistors due to its excellent electronic properties. In determining the accurate output drain current of CNTFET, time lapsed and accuracy of different simulation methods were compared. The training data for...

Breast cancer is the second cause of dead among women. Early detection followed by appropriate cancer treatment can reduce the deadly risk. Medical professionals can make mistakes while identifying a disease. The help of technology such as data mining and machine learning can substantially improve the diagnosis accuracy. Artificial Neural Networks (ANN) has been widely used in intelligent breas...

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...

This study presents a new procedure based on Artificial Neural Network (ANN) for identification of double cracks in Functionally Graded Beams (FGBs). A cantilever beam is modeled using Finite Element Method (FEM) for analyzing a double-cracked FGB and evaluation of its first four natural frequencies for different cracks depths and locations. The obtained FEM results are verified against availab...

The use of artificial neural networks (ANN) for nonlinear system modeling is a field where still there is much theoretical work to be done. A structured ANN which obtains neural models of nonlinear systems is presented. Those neural models are Fourier-series based. To check the goodness of the method, conventional difference equations are re-modeled via ANN and their respective input/outputs co...

BACKGROUND Artificial neural networks (ANN) are gaining prominence as a method of classification in a wide range of disciplines. In this study ANN is applied to data from a verbal autopsy study as a means of classifying cause of death. METHODS A simulated ANN was trained on a subset of verbal autopsy data, and the performance was tested on the remaining data. The performance of the ANN models...

This tutorial article deals with the basics of artificial neural networks (ANN) and their applications in pattern recognition. ANN can be viewed as computing models inspired by the structure and function of the biological neural network. These models are expected to deal with problem solving in a manner different from conventional computing. A distinction is made between pattern and data to emp...