Sharif Digital Repository

We consider biobjective shortest path problems in networks with fuzzy arc lengths. Considering the available studies for single objective shortest path problems in fuzzy networks, using a distance function for comparison of fuzzy numbers, we propose three approaches for solving the biobjective problems. The first and second approaches are extensions of the labeling method to solve the single objective problem and the third approach is based on dynamic programming. The labeling methods usually producing several nondominated paths, we propose a fuzzy number ranking method to determine a fuzzy shortest path. Illustrative examples are worked out to show the effectiveness of our algorithms  

Nowadays, genetic disorders, like cancer and birth defects, are a great threat to human life. Since the first noticing of these types of diseases, many efforts have been made and researches performed in order to recognize them and find a cure for them. These disorders affect genes and they appear as abnormal traits in a genetic organism. In order to recognize abnormal genes, we need to predict splice sites in a DNA signal; then, we can process the genetic codes between two continuous splice sites and analyze the trait that it represents. In addition to abnormal genes and their consequent disorders, we can also identify other normal human traits like physical and mental features. So the... 

This paper focuses on the observer design for a 2D nano-positioner. In order to position the stage with a desired accuracy, it is required to adjust the stage displacements with a closed-loop control system. Since displacement and velocity of the main stage are not measured directly in the designed nano-positioning system, some observers should be designed to estimate these state variables using data provided by measurable variables. To this end, three different observers were designed based on neural, fuzzy and adaptive neuro fuzzy inference system (ANFIS) networks. With the purpose of obtaining data for training the observer model, a reference model is required. For this reason, the... 

Graph theory has numerous applications to problems in systems analysis, operations research, transportation, and economics. In many cases, however, some aspects of a graph-theoretic problem may be uncertain. For example, the vehicle travel time or vehicle capacity on a road network may not be known exactly. In such cases, it is natural to make use of fuzzy set theory to deal with the uncertainty. Here, we are concerned with finding shortest chains in a graph with fuzzy distance for every edge. We propose a dynamic programming approach to solve the fuzzy shortest chain problem using a suitable ranking method. By using MATLAB, two illustrative examples are worked out to demonstrate the... 

Untethered small-scale robots can accomplish tasks which are not feasible by conventional macro robots. In the current research, we have designed and fabricated a miniature magnetic robot actuated by an external magnetic field. The proposed robot has two coaxial wheels and one magnetic dipole which is capable of rolling and moving on the surface by variation in the direction of magnetic field. To generate the desired magnetic field, a Helmholtz electromagnetic coil is manufactured. To steer the robot to the desired position, at first the robot dynamics is investigated, and subsequently a controller based on a neuro-fuzzy network has been designed. Finally, the proposed controller is... 

Magnetic flux leakage is the most widely used method for oil and gas pipeline non destructive testing. The saturation level of the sample under test has a significant effect on its efficiency; therefore, the magnetizing yoke requires an elaborate design. The finite element method is the conventional approach used for this purpose, but it is very time consuming. In this article, a neuro-fuzzy method is presented to model the behavior of the magnetizing yoke. Modeling a few different designs with the finite element method and using the results for training the neuro-fuzzy model eradicates the necessity of modeling a huge number of designs with the finite element method. The acquired... 

In this study, a novel artificial intelligence-based approach is presented to directly estimate the surface topography. To this aim, performance of different artificial intelligence-based techniques, including the multi-layer perceptron neural, radial basis function neural, and adaptive neural fuzzy inference system networks, in estimation of the sample topography is investigated. The results demonstrate that among the designed observers, the multi-layer perceptron method can estimate surface characteristics with higher accuracy than the other methods. In the classical imaging techniques, the scanning speed of atomic force microscope is restricted due to the time required by the oscillating...