Recently, mobility has gathered tremendous interest as the users' desire for consecutive
connections and better quality of service has increased. An accurate prediction of user …

This paper proposes a novel model called Space Time Features-based Recurrent Neural
Network (STF-RNN) for predicting people next movement based on mobility patterns …

The applications of both Feed Forward Neural network and Multilayer perceptron are very
diverse and saturated. But the linear threshold unit of feed forward networks causes fast …

This paper proposes the application of functional link neural networks (FLNNs) for structural
response prediction of tall buildings due to seismic loads. The ground acceleration data are …

In the data classification process involving higher order ANNs, it'sa herculean task to
determine the optimal ANN classification model due to non-linear nature of real world …

Due to society aging, age-related issues such as mild cognitive impairments (MCI) and
dementia are attracting the attention of health professionals, scientists and governments …

Stock exchange that is, buying and selling of stock is considered to be an important factor in
the economy sector. The Stockbrokers typically use time series or technical analysis in …

Now days cellular users are expecting seamless connectivity and better quality of
experience from service providers. In cellular networks, user mobility is crucial since it raises …

In this paper, we have proposed a multiplicative FLANN (MFLANN) model for time series
forecasting. In addition, an improved version of teaching learning based optimisation …

Abstract System identification problems are generally inverse vibration problems.
Sometimes it is difficult to handle the inverse problems by traditional methods and classical …