Abbas Toloie- Eshlaghy et al./ Elixir Mgmt. Arts 41 (2011) 5877-5881 5877 Introduction Smart systems have many applications as one of the modern tools in different fields of sciences for optimization and prediction. These evolutionary achievements in information technology have allowed processing of the information in parallel. Human being has tried to imitate brain mechanism to discover the secrets of creation in order to find this complex architecture of creation leading to development of smart systems. This major change in human knowledge led to an important achievement in science and scientific methods and has been used as scientific complex tool to solve problems of human beings. This tool has been mostly applied in reliability and many progresses were made in this field. In this paper which is done with use of one of the advanced techniques in this field i.e. neuro-fuzzy networks, we try to predict reliability of tire in passenger cars. Neuro-fuzzy networks –based models are able to predict variable behavior property and desirably and can predict its future behavior. Our goal is to model a nonlinear prediction for reliability. With regard to promotion and development of automotive industries and competitive atmosphere in this industry, important issues such as useful life of the car and safety were raised. In this regard, reliability entered automotive industry as an important index which can answer some of the above cases. Reliability is defined as the possibility that a component or system performs its assumed tasks properly under defined conditions and at special time. Material and methods Fuzzy deduction system Fuzzy set theory is a relatively new mathematical theory which was presented by Iranian student, Professor Lotfi Asgarzadeh alias Zadeh, in order to find mathematical models which are compatible with human thinking and deductive manner as well as natural and real models. Word fuzzy means confused and unspecified and is used for description of unreal and unspecified phenomena. A fuzzy system is a system based on fuzzy rules of if-then which images input space on output space with use of fuzzy variables and fuzzy decision making. In summary, starting point of a fuzzy system design is to find a set of if-then rules from knowledge of the experts or the studied knowledge. Artificial neural network Main idea of neural networks is human brain. At present, scientists try to have access to information processing by researching function of human brain and algorithm and modeling of its internal mechanism. Main component of these models is information processing unit which simulates function of neural neurons which are called neural neuron. Although it seems that a neuron is a simple entity, neurons can be connected to each other in a system structure. More than 40 traits of natural neurons have been recorded in information processing. More information about neurons and neural system is presented in detail. Human brain neurons ANN It is a system which has been created by connecting some factors to each other. It is inspired by biological study of neural systems of living creatures especially human being. On the other hand, neural networks try to make the machines which act like human brain. In order to make such machines, some components which act like biological neurons are used. Function of a neural system is as follows: When an input model is defined for it, it should be able to produce an output model (Toloie Eshlaghy, 2008). Figure 1 shows simple scheme of a neural system model. As figure 1 show, each neural system has been composed of three layers including: input layer, output layer and hidden layer. Figure 1: simple scheme of a neural system model Tele: E-mail addresses: toloie@gmail.com © 2011 Elixir All rights reserved Prediction of reliability of vehicle tire with use of Neuro-fuzzy networks Abbas Toloie- Eshlaghy and Parisa Sadat Tabatabaei Kooshki Department of Industrial Management, Science and Research Branch, Islamic Azad University, Tehran, Iran. ABSTRACT In this paper, one of the artificial intelligence techniques called networks for prediction of reliability of the tire is neuro-fuzzy network. At first key indices which are effective on reliability of tire are identified and then some rules have been designed and applied for system training with use of experts’ views. ANFIS system implements Takagi –Sugno fuzzy system as a system and inference and deduction of the system are mixed and an efficient tool is provided for simulating a nonlinear mapping. In the performed simulations, some 4-input networks are different with membership functions and have been studied in different iterations for prediction and finally the model which had high predictability was selected as optimal model. © 2011 Elixir All rights reserved. ARTICLE INFO Article history: Received: 3 October 2011; Received in revised form: 25 November 2011; Accepted: 12 December 2011; Keywords Reliability, Fuzzy system, ANFIS neural –fuzzy system. Elixir Mgmt. Arts 41 (2011) 5877-5881 Management Arts Available online at www.elixirpublishers.com (Elixir International Journal)