in this study, the profitability of contrarian and momentum strategies were traded in mid- term based on trading volume. the stocks were categorized into three parts (high, middle and low) at the outset. then, the relationship between excess return with three components such as cross-sectional risk, lead-lag effect and time-series pattern were examined based on jegadeesh and titman approach.the...

background: injuries and deaths from road traffic crashes are one of the main public health problems throughout the world. this study aimed to identify determinants of fatality traffic accident in iran for the twenty-span year from 1991 to 2011. methods: a time series analysis (1991-2011) was used to examine the effects of some of the key explanatory factors (gdp per capita, number of doctors p...

This paper proposes a discrete recurrent neural network model to implement winner-take-all function. This network model has simple organizations and clear dynamic behaviours. The dynamic properties of the proposed winner-take-all networks are studied in detail. Simulation results are given to show network performance. Since the network model is formulated as discrete time systems , it has advan...

Recurrent fuzzy neural networks (FNNs) have been widely applied to dynamic system processing problems. However, most recurrent FNNs focus on the use of type-1 fuzzy sets. This paper proposes a Mamdani-type recurrent interval type-2 FNN (M-RIT2FNN) that uses interval type-2 fuzzy sets in both rule antecedent and consequent parts. The reason for using interval type-2 fuzzy sets is to increase net...

As neural network algorithms show high performance in many applications, their efficient inference on mobile and embedded systems are of great interests. When a single stream recurrent neural network (RNN) is executed for a personal user in embedded systems, it demands a large amount of DRAM accesses because the network size is usually much bigger than the cache size and the weights of an RNN a...

in this paper, a model based on gmdh type neural network, is used to predict gas price in the spot market while using oil spot market price, gas spot market price, gas future market price, oil future market price and average temperature of the weather. the results suggest that gmdh neural network model, according to the root mean squared error (rmse) and direction statistics (dstat) statistics ...

A new predictive scheme is proposed for the control of Linear Time Invariant (LTI) systems with a constant and known delay in the input and unknown disturbances. It has been achieved to include disturbances effect in the prediction even though there are completely unknown. The Artstein reduction is then revisited thanks to the computation of this new prediction. An extensive comparison with the...