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...

short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . these results made the hybrid tools and approaches a more common method for ...

A hybrid approach for intrusion detection in computer networks is presented in this paper. The proposed approach combines an evolutionary-based fuzzy system with an Ant Colony Optimization procedure to generate high-quality fuzzy-classification rules. We applied our hybrid learning approach to network security and validated it using the DARPA KDD-Cup99 benchmark data set. The results indicate t...

This paper proposes a mixed integer programming model to solve a non-identical parallel machine (NIPM) scheduling with sequence-dependent set-up times and human resiliency engineering. The presented mathematical model is formulated to consider human factors including Learning, Teamwork and Awareness. Moreover, processing time of jobs are assumed to be non-deterministic and dependent to their st...

in this paper we apply hybrid functions of general block-pulse‎ ‎functions and legendre polynomials for solving linear and‎ ‎nonlinear multi-order fractional differential equations (fdes)‎. ‎our approach is based on incorporating operational matrices of‎ ‎fdes with hybrid functions that reduces the fdes problems to‎ ‎the solution of algebraic systems‎. ‎error estimate that verifies a‎ ‎converge...

in this paper by combining caching and replication techniques proposed a hybrid heuristic method based on the greedy algorithm to use the benefit of each other techniques. the algorithm in each interaction compares all the contents and one that made the best benefit value is selected for replication. the hybrid approach tested in a simulation environment and the results show that hybrid algorit...

Short term prediction of traffic flow is one of the most essential elements of all proactive traffic control systems. Although various methodologies have been applied to forecast traffic parameters, several researchers have showed that compared with the individual methods, hybrid methods provide more accurate results . These results made the hybrid tools and approaches a more common method for ...

In this paper, we present a noisy version of the algebraic geometric approach of identifying parameters of discrete-time linear hybrid system. Two approximate ways of estimating hybrid parameters are considered: one is using MSE criteria, while the other is based on the information divergence that measures the distance between the error probability density function (PDF) of the identified model...

Introduction: All of the Imaging modalities have advantages and disadvantages alone. So if we want to have the best and perfect image, combining these modalities produces something we desired. PET-MR images consist of morphologic and metabolic data. MRI and PET provide high spatial and contrast resolution and high sensitivity and molecular information respectively. Hybrid PET-...