in this research, an innovative numerical simulating approach for time domain analysis of multi degrees of freedom structures with uncertainty in dynamic properties is presented. a full scale finite element model of multi-story and multi bays of three sample structures has been constructed. the reduced order model of structure with holding the dominant and effective gramians in the balanced sta...

this article deals with the issues associated with developing a new design methodology for the nonlinear model-predictive control (mpc) of a chemical plant. a combination of multiple neural networks is selected and used to model a nonlinear multi-input multi-output (mimo) process with time delays.  an optimization procedure for a neural mpc algorithm based on this model is then developed. the p...

introduction: autism spectrum disorders (asd) belong to the pervasive neurodevelopmental disorders. the prevalence of asd has increased significantly throughout recent decades, bringing the overall estimated prevalence to 11.3 per 1000 children. asd is characterized by severe difficulties in reciprocal social interaction, stereotyped patterns of behavior and profound impairments in verbal and n...

In this work, artificial neural network (ANN) has been employed to propose a practical model for predicting the surface tension of multi-component mixtures. In order to develop a reliable model based on the ANN, a comprehensive experimental data set including 15 ternary liquid mixtures at different temperatures was employed. These systems consist of 777 data points generally containing hydrocar...

appropriate scheduling and sequencing of tasks on machines is one of the basic and significant problems that a shop or a factory manager encounters; this is why in recent decades extensive studies have been done on scheduling issues. one type of scheduling problems is just-in-time (jit) scheduling and in this area, motivated by jit manufacturing, this study investigates a mathematical model for...

We describe a general mechanism for adaptation in multiagent systems in which agents modify their behavior based on their memory of past events. These behavior changes can be elicited by environmental dynamics or arise as response to the actions of other agents. The agents use memory to estimate the global state of the system from individual observations and adjust their actions accordingly. We...