Introduction: Identifying the potential firing patterns following different brain regions under normal and abnormal conditions increases our understanding of events at the level of neural interactions in the brain. Furthermore, it is important to be capable of modeling the potential neural activities to build precise artificial neural networks. The Izhikevich model is one of the simplest biolog...

Geological facies interpretation is essential for reservoir studying. The method of classification and identification seismic traces is a powerful approach for geological facies classification and distinction. Use of neural networks as classifiers is increasing in different sciences like seismic. They are computer efficient and ideal for patterns identification. They can simply learn new algori...

the aim of this study was to propose a method for improving the power of recognition and classification of thromboembolic syndrome based on the analysis of ‎ gene expression data using artificial neural networks. the studied method was performed on a dataset which contained data about 117 patients admitted to a hospital in durham in 2009. of all the studied patients, 66 patients were suffering ...

abstract tax is one of the main sources of financing government budget. therefore, having a clear picture about the attainable amount of taxes are not only necessary for optimal allocation of scarce resources for tax collection, but also helps the government to develop precise tax collection programs .in this article, the structural features of the tax revenues series have first been examined i...

according to this fact that wind is now a part of global energy portfolio and due to unreliable and discontinuous production of wind energy; prediction of wind power value is proposed as a main necessity. in recent years, various methods have been proposed for wind power prediction. in this paper the prediction structure involves feature selection and use of artificial neural network (ann). in ...

in this paper, an attempt has been made to introduce a new control strategy including plug-in hybrid electric vehicle (phev) and diesel engine generator to control the voltage and frequency of autonomous microgrids. the proposed control strategy has multiple advantages over the recent control methods in microgrids. the proposed method applies the primary and secondary frequency control strategy...

this paper presents a prediction model based on a new neuro-fuzzy algorithm for estimating time in construction projects. the output of the proposed prediction model, which is employed based on a locally linear neuro-fuzzy (llnf) model, is useful for assessing a project status at different time horizons. being trained by a locally linear model tree (lolimot) learning algorithm, the model is int...

changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. the cognition of causes is very important, because the system can be diagnosed and fault tolerated. in this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. the main fe...

statistical process control (spc) charts play a major role in quality control systems, and their correct interpretation leads to discovering probable irregularities and errors of the production system. in this regard, various artificial neural networks have been developed to identify mainly singular patterns of spc charts, while having drawbacks in handling multiple concurrent patterns. in this...