Sharif Digital Repository

Order statistic (OS) CFAR processor is a powerful detector, but similar to many other CFAR detectors, suffers from clutter edge as well as interfering targets. To overcome these problems, two derivations of this detector have been developed. These are order statistic greatest of (OSGO) and order statistic smallest of (OSSO) CFAR processors. The cost, paid for this improvement, is a considerable decrease in detection probability for homogenous Weibull clutter. Furthermore, a substantial performance degradation of OSGO in interfering target (high target masking effect) and an excessive false alarm of OSSO in clutter edge, also, occur. This behavior is a result of non-soft rules used in these... 

Fuzzy functions are used to identify the structure of system models and reasoning with them. Fuzzy functions can be determined by any function identification method such as Least Square Estimates (LSE), Maximum Likelihood Estimates (MLE) or Support Vector Machine Estimates (SVM). However, estimating fuzzy functions using LSE method is structurally a new and unique approach for determining fuzzy functions. By using this approach, there is no need to know or to develop an in-depth understanding of essential concepts for developing and using the membership functions and selecting the t-norms, co-norms and implication operators. Furthermore, there is no need to apply fuzzification and... 

Route choice modeling is one of the most important parts of traffic assignment problem. Recently, this model is used to describe the reactions of drivers to Traveler Information Systems in order to develop accurate Advanced Traffic Management and Information System (ATMIS). Therefore accurate model is necessary. In this paper we proposed a new model based on Type-II fuzzy logic to model route choice problem. This model can take account of the imprecision, uncertainties and vagueness lying in the dynamic choice process and makes more accurate modeling of drivers' behavior than deterministic, stochastic and Type-I fuzzy models. In our proposed model we consider average speed and cost... 

In mechanical assemblies, individual components are placed together to deliver a certain function. The performance, quality, and cost of the mechanical assembly are significantly affected by its tolerances. Toleranced dimensions inherently generate an uncertain environment in a mechanical assembly. This paper presents a proper method for tolerance analysis of mechanical assemblies with asymmetric tolerances based on an uncertainty model. This mathematical approach is based on fuzzy logic and tolerance accumulation models such as worst-case and root-sum-square methods. A fuzzy-based tolerance representation is developed to model uncertainty of tolerance components in the mechanical... 

Due to the vague nature of fuzzy numbers, ranking them according to their magnitude is an interesting area of fuzzy numbers. For this reason, several techniques have been proposed for ranking them. Each of these techniques has shown non-intuitive results in specific cases. Cheng employed 'distance method' for ranking fuzzy numbers in Ref [3]. Then Chu and Tsao in [5] found another method. In this article, some problems of Cheng distance method is indicated and then a new revised method for ranking fuzzy numbers has been proposed which can avoid problem for ranking fuzzy numbers. The considerable priority of the proposed method is its simplicity and easiness in calculation with distance... 

Intrusion detection systems (IDS) are tools located inside computer networks that analyze the network traffics. In this paper, a novel fuzzy-evolutionary system is presented to effectively detect the intrusion in computer networks. This system utilizes a hybridization of simulated annealing heuristic and tabu search algorithm to improve the accuracy of fuzzy if-then rules as intrusion detectors. Each of these algorithms has its advantageous and disadvantageous. Using the hybrid model of both algorithms, the proposed system employs the good features of them to improve the accuracy of obtained rules. Evaluation of the proposed system is done on the KDDCup99 Dataset which has information about... 

In this paper, by a simple example it is shown that existing market-based criteria alone cannot completely and correctly evaluate the transmission network expansion from market view. However criteria congestion cost (CC) and social welfare (SW) together are able to correctly evaluate transmission network from market view and so they are adopted for the market-based transmission expansion planning. To simply indicate the limits of CC and SW social welfare percentage (SWP) and congestion cost percentage (CCP) are defined. To consider uncertainty in bids of market producers and consumers, and also indeterminacy in the acceptable boundaries of the SWP and CCP and their priorities, fuzzy... 

In this paper, by a simple example it is shown that existing market-based criteria alone cannot completely and correctly evaluate the transmission network expansion from market view. However criteria congestion cost (CC) and social welfare (SW) together are able to correctly evaluate transmission network from market view and so they are adopted for the market-based transmission expansion planning. To simply indicate the limits of CC and SW social welfare percentage (SWP) and congestion cost percentage (CCP) are defined. To consider uncertainty in bids of market producers and consumers, and also indeterminacy in the acceptable boundaries of the SWP and CCP and their priorities, fuzzy... 

To reduce the semantic gap in the content based image retrieval (CBIR) systems we propose a fuzzy rule base approach. By submitting a query to the proposed system, it first extracts its low-level features and then checks its rule base for determining the proper weight vector for its distance measure. It then uses this weight vector to determine what images are more similar to the query image. For the training purpose, an algorithm is provided by which the system adjusts its fuzzy rules' parameters by gathering the trainers' opinions on which and how much the image pairs are relevant. For further improving the performance of the system, a feature space dimensionality reduction method is also... 

This paper presents a novel hybrid approach for intrusion detection in computer networks. The proposed approach combines an evolutionary based fuzzy system with an artificial immune system to generate high quality fuzzy classification rules. The performance of final fuzzy classification system has been investigated using the KDD-Cup99 benchmark dataset. The results indicate that in comparison to several traditional techniques, such as C4.5, Naïve Bayes, k-NN and SVM, the proposed hybrid approach achieves better classification accuracies for most of the classes of the intrusion detection classification problem. Therefore, the resulted fuzzy classification rules can be used to produce a... 

The process of scanning the events occurring in a computer system or network and analyzing them for warning of intrusions is known as intrusion detection system (IDS). This paper presents a new intrusion detection system based on tabu search based fuzzy system. Here, we use tabu search algorithm to effectively explore and exploit the large state space associated with intrusion detection as a complicated classification problem. Experiments were performed on KDD-Cup99 data set which has information about intrusive and normal behaviors on computer networks. Results show that the proposed method obtains notable accuracy and lower cost in comparison with several renowned algorithms  

A Magneto rheological (MR) rotary brake as a prosthesis knee is addressed here. To the gait of the amputee, the brake, automatically adapts knee damping coefficient using only local sensing of the knee torque and position. It is difficult to design a model-based controller, since the MR knee system has nonlinear and very complicated governing mathematical equations. Hence, a Hybrid self-organizing fuzzy controller and multidimensional wavelet neural network (HSFCMWNN) is proposed here to control the knee damping coefficient using of the inverse dynamics of the MR rotary damper. A Self-organizing fuzzy controller (SOFC) is also proposed and during the control process, the SOFC continually... 

In this paper we have proposed an evolutionary algorithm to induct fuzzy classification rules. The algorithm uses an ant colony optimization based local searcher to improve the quality of final fuzzy classification system. The proposed algorithm is performed on Intrusion Detection as a high-dimensional classification problem. Results show that the implemented evolutionary ACO-Based algorithm is capable of producing a reliable fuzzy rule based classifier for intrusion detection. © 2007 IEEE  

This article build upon fairness in pricing -i.e. a perceived fairness judgment by a buyer of a seller's prices (Haws and Bearden, 2006) - and dynamic pricing - a strategy in which prices vary over time, consumers, and/or circumstances (Haws and Bearden, 2006) - an analysis of the importance of the factors influencing consumers' perception of fairness. Specifically, it uses fuzzy cognitive maps on the model proposed by Haws and Bearden (2006) to find the most important path leading to consumer satisfaction with the price. The FCM analyzes the responses of a group of 30 experts from 4 leading companies in medical equipment importing to find the most important paths  

In this paper, a generalized intelligent water drops algorithm (IWD) for solving robot path planning problem is proposed. The authors want to reduce the time of reaching the optimal solution as much as possible. To do this, some new heuristic operators and a multi section graph model of environment is introduced. The authors divide graph to equal sections and compare behaviour of the solutions (paths) in each section with behaviour of them in other sections. This comparison uses a fuzzy inference system. Base on this comparison, a fuzzy number is assigned to each part of solutions. This fuzzy number determines the worth of a solution in a section. Less worth solutions need more improvement.... 

In this paper, a novel approach for tuning the parameters of fuzzy wavelet systems which are used for modeling of nonlinear and complex systems is proposed. In fuzzy inference system, each fuzzy rule is analogous to a wavelet basis function multiplied by a coefficient. Using clustering techniques, the center of these basis functions are located in the detected center of clusters. In this way, not only the approximation accuracy is increased, but also the number of unknown parameters is decreased. The feasibility of the proposed method is shown by modeling two highly nonlinear functions. The comparison of the results using the proposed approach, with the previous schemes, shows the... 

This paper presents a fuzzy approach for contrast enhancement, based on two multi-scale transforms, namely wavelet and contourlet transforms. Separability and nondirectionality of conventional 2D wavelet transform, makes it unsuitable for sparsely representation of curve or line shaped image objects. On the other hand, the contourlet transform is a good alternative for this purpose. In this paper, coefficient enhancement, both in wavelet and contourlet spaces, is carried out by making use of simple fuzzy rules. These rules make the enhancement procedure more understandable and flexible. With this method, the knowledge and experience of the expert from the distribution of the coefficients can... 

Trip distribution is considered as the second step in urban transportation planning. The important factors which affect trip distribution are the characteristics of origins and destinations and travel impedance between O/D. Trip distribution traditionally models with the deterministic variables although it seems affective variables in trip distribution molding are based on human perceptions. Since perceptions of people vary from one person to another, thus variables are imprecise and vague. Fuzzy approaches are proper tools of modeling non-deterministic variables. In this paper we present fuzzy estimation models of trip distribution for discretionary trip purposes including: shopping,... 

Data mining is a very popular technique which is successfully used in many areas. The aim of this paper is to present a data mining system for extracting knowledge from input datasets. We use the hybrid ant colony and simulated annealing algorithms to optimize extracted fuzzy rule set. The proposed method has the main feature of data mining techniques which is high accuracy. The proposed method is then implemented on UCI datasets. The results are compared with those of well-known methods, and show the competitive systems efficiency