The Supply Chain is considered a necessity for the success of organizations seeking the most economic, environmental and social impacts. In addition, the implementation and suitable execution of this supply chain seems to be necessary. Considering the importance of the social impacts of this supply chain, a fuzzy multi-objective mathematical model is provided such that, in addition to consideri...

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...

OBJECTIVE This in vitro study evaluated the effect of Ankaferd Blood Stopper (ABS) contamination on the microleakage of one-step and two-step self-etching adhesives. STUDY DESIGN Class V cavities were prepared at the cemento-enamel junction on both buccal and lingual surfaces of 60 freshly extracted human molars. Teeth were randomly assigned into three groups according to contamination materi...

The complexity of systems and their multi-faceted relationships mean that the combined application of simulation methods, or hybrid simulation, will enable synergies across techniques and will provide greater insights to problem solving. In this paper we present a hybrid simulation case study in which two models have been developed; an Agent-Based Simulation (ABS) and a Discrete-Event Simulatio...

In many multiagent domains, no single observation event is sufficient to determine that the behavior of individuals is suspicious. Instead, suspiciousness must be inferred from a combination of multiple events, where events refer to the individual’s interactions with other individuals. Hence, a detection system must employ a detector that combines evidence frommultiple events, in contrast to mo...

I n this paper, we specify that the GARCH(1,1) model has strong forecasting volatility and its usage under the truncated standard normal distribution (TSND) is more suitable than when it is under the normal and student-t distributions. On the contrary, no comparison was tried between the forecasting performance of volatility of the daily return series using the multi-step ahead forec...

Modelling and forecasting Stock market is a challenging task for economists and engineers since it has a dynamic structure and nonlinear characteristic. This nonlinearity affects the efficiency of the price characteristics. Using an Artificial Neural Network (ANN) is a proper way to model this nonlinearity and it has been used successfully in one-step-ahead and multi-step-ahead prediction of di...

background: the measurement data regarding the influent and effluent of wastewater treatment plant (wwtp) provides a general overview, demonstrating an overall performance of wwtp. nevertheless, these data do not provide the suitable operational information for the optimization of individual units involved in a wwtp. a full-scale evolution of wwtp was carried out in this study via a reconciled ...

Abs t rac t – Current methods for GPS receiver autonomous integrity monitoring are limited by the assumptions they make. Using published studies of navigation system reliability, this paper develops a prior probability model for spacecraft and receiver anomalies based on non-ideal failure models and the uncertainty present in their failure distribution parameters. With this model, the threshold...