Sharif Digital Repository

This paper introduces the concept of mapping of Artificially Intelligent (AI) computational systems. The concept of homunculus from human neurophysiology is extended to AI systems. It is assumed that an AI system behaves similarly to a mini-column or ganglion in the natural animal brain that comprises a layer of afferent (input) neurons, a number of interconnecting processing cells, and a layer of efferent (output) neurons or organs. The objective of the present study was to identify the correlation between the stimulus to each afferent neuron and the corresponding response from each efferent organ when the intelligent system is subjected to certain stimuli. To clarify the general concept, a... 

Interactions between the members of an imaginary universe, where all the members are adaptive and have learning capability, is simulated numerically by using artificial neural networks. The universe is called λ-universe for brevity. It is shown here that in such a universe, rules governing the behavior of the members might be formed inside the universe by its own members and the randomness which is observed in the behavior of its members is a direct result of the learning capability of the members. Although this is not a simulation of the real universe, some fundamental concepts of astrophysics have been implemented in it  

Trusses are suitable load-bearing structural systems for heavy concentrated loads. In this paper, it is shown that it is possible to use active control mechanisms to enhance the load-bearing capacity of the trusses. Under heavy loading, some elements of a truss might experience high stresses and show non-linear behavior, resulting in large deformations in the truss. Under such a condition, some elements of the truss might damage which can lead to the collapse of the truss. Application of control forces on some of the degrees of freedom of the truss can render help the truss tolerate larger forces before its collapse. A neural network can then be trained to learn the relationship between the... 

Active control of multi-storey frame structures with nonlinear hysteretic response has been studied in this paper. A new nonlinear optimal control algorithm based on nonlinear Newmark integration method and distributed genetic algorithm (DGA) has been developed. The objective has been to reduce the response to below any desired level. In this study, DGA has been used to determine the weights in the control law corresponding to displacement, velocity and acceleration. The capabilities of the method has been assessed through simulation where an eight-storey frame with bilinear hysteretic behaviour has been subjected to a white noise ground acceleration and controlled by the controllers... 

In this analytical study, it has been desired to develop a practical and simple control mechanism to control, at a given point and its neighborhood, the sound arriving from a distant source, assuming that a primary pure-tone sound pressure is propagated from a relatively far distance. The control model consists of a microphone as a sensor for measuring the sound pressure and a loud speaker for applying the control force. Corresponding equations have been developed to determine an optimum control force, and afterwards a parametric study on the factors affecting the control results has been performed. The results show that the control system can significantly reduce low frequency sound... 

A new method, based on the concepts of matrix analysis as well as the learning capabilities of neural networks, for the analysis of nonlinear trusses under dynamic loading is presented. The method can be applied to static trusses too. While there have been attempts in the past to use neural networks to identify and model different structures based on data measured on structural response directly, the main feature and advantage of this new method is in its capability to model a nonlinear truss by assembling the data collected on the response of its members. The basics of the method are: (1) for each truss member, a neural network is trained to learn and simulate its loadresponse behavior, (2)... 

The effect of response feedback on designing optimal controllers for nonlinear frames has been studied. Different combinations of response feedback have been used in the performance index. The Newmark based nonlinear instantaneous optimal control algorithm has been used as the control algorithm in controlling the response of an eight-story bilinear hysteretic frame subjected to white noise excitation and real earthquakes, and controlled by either eight actuators or a single actuator. While the objective has been to minimize the maximum control force for reducing the maximum drift to below the yielding level, the distributed genetic algorithm (DGA) has been used to determine the proper set of... 

New penalty functions, which have better convergence properties, as compared to the commonly used exterior and interior penalty functions, have been proposed in this paper. The convergence behavior and accuracy of ordinary penalty functions depend on the selection of appropriate penalty parameters. The optimization of ordinary penalty functions is accomplished after several rounds of optimization where, at each round a different but fixed value of penalty parameter is used. While some useful hints and rules for the selection of suitable penalty parameter values have been provided by different authors, the objective of this paper has been to improve this procedure by including the penalty...