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...

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...

In this paper, a hybrid meta-heuristic algorithm, based on imperialistic competition algorithm (ICA), harmony search (HS), and simulated annealing (SA) is presented. The body of the proposed hybrid algorithm is based on ICA. The proposed hybrid algorithm inherits the advantages of the process of harmony creation in HS algorithm to improve the exploitation phase of the ICA algorithm. In addition...

in recent decade, the new advanced nanofluids, composed from various particles, have attracted the attention of researchers. this class of nanofluids, which can be prepared by suspending several types (two or more than two) of nanoparticles in base fluid, is termed as hybrid nanofluids. in this work, an experimental investigation on the effects of temperature and concentration of nanoparticles ...

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 ...

abstract autoregressive integrated moving average (arima) has been one of the widely used linear models in time series forecasting during the past three decades. recent studies revealed the superiority of artificial neural network (ann) over traditional linear models in forecasting. but neither arima nor anns can be adequate in modeling and forecasting time series since the first model cannot d...

evolutionary algorithms are some of the most crucial random approaches tosolve the problems, but sometimes generate low quality solutions. on the otherhand, learning automata are adaptive decision-making devices, operating onunknown random environments, so it seems that if evolutionary and learningautomaton based algorithms are operated simultaneously, the quality of results willincrease sharpl...

this paper provides a comparison of the maximum inter-story drifts and tip acceleration of both a 16 and 30 stories building each with different structural systems; hybrid r.c moment frame with shear walls and hybrid steel frame with shear walls and x bracing which are equipped by passive dampers. each of the building models were analyzed as fully non-linear structures for variety of dampers pl...