Abstract This article proposes a novel method to optimise the Dynamic Architecture Neural Network (DAN2) adapted for multi-task learning problem. The neural network adopts multi-head and serial architecture with DAN2 layers acting as basic subroutine. Adopting dynamic architecture, are added consecutively starting from minimal initial structure. optimisation an iterative heuristic scheme that s...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

Transportation and inventory are essential to hazardous materials logistics, while different classes of often transported over a network simultaneously. Despite their in-transit storage incompatibility, the superimposed risks among materials, which results from possible chemical reaction once accidents (e.g., leakage, explosion) happen, further complicate comprehensive plans. In this study, we ...

In recent years, studies in the field of deep learning have made significant progress. These focusedmore on datasets with balanced classification, and less research has been done imbalanced datasets, whichare great importance real world present challenges for classification. This articlestudies problem classifying data, introduces dynamic sampling neural networks,investigates multiclass problem...

Many events such as large-scale activities and traffic accidents could cause an increase in vehicle density area, which makes the evacuation of vehicles important. However, existing methods are not efficient limit to multi-vehicles sequences or destinations. In this paper, we introduce a novel dynamic weighted road network model for route planning. Based on model, planning algorithm can obtain ...

Detection of fake accounts on social networks is a challenging process. The previous methods in identification of fake accounts have not considered the strength of the users’ communications, hence reducing their efficiency. In this work, we are going to present a detection method based on the users’ similarities considering the network communications of the users. In the first step, similarity ...