image classification is an issue which utilizes image processing, pattern recognition and classification methods. automatic medical image classification is a progressive area in image classification and it expected to be more developed in the future. due to this fact that automatic diagnosis which use intelligent methods such as medical image classification can assist pathologists by providing ...

the late detection of the kick (the entrance of underground fluids into oil wells) leads to oil wellblowouts. it causes human life loss and imposes a great deal of expenses on the petroleum industry.this paper presents the application of adaptive neuro-fuzzy inference system designed for an earlierkick detection using measurable drilling parameters. in order to generate the initial fuzzy infere...

Load sensor is developed using mamdani fuzzy inference system and sugeno fuzzy inference system. It is two input and one output sensor. Both mamdani-type fuzzy inference system and sugeno-type fuzzy inference system are simulated using MATLAB fuzzy logic toolbox. This paper outlines the basic difference between these two fuzzy inference system and their simulated results are compared. Index Ter...

Fuzzy inference systems and neural networks are complementary technologies in the design of adaptive intelligent systems. Artificial Neural Network (ANN) learns from scratch by adjusting the interconnections between layers. Fuzzy Inference System (FIS) is a popular computing framework based on the concept of fuzzy set theory, fuzzy if-then rules, and fuzzy reasoning. A neuro-fuzzy system is sim...

Terrorism has led to many problems in Thai societies, not only property damage but also civilian casualties. Predicting terrorism activities in advance can help prepare and manage risk from sabotage by these activities. This paper proposes a framework focusing on event classification in terrorism domain using fuzzy inference systems (FISs). Each FIS is a decisionmaking model combining fuzzy log...

This paper discusses design of adaptive Genetic Algorithms (GA) on the base Fuzzy Inference System (FIS). There are two possible ways for integrating Fuzzy Logic and Genetic Algorithms. One involves the applications of Genetic Algorithms for solving optimization and search problem related with fuzzy systems. The another, the use of “fuzzy tools” for modeling and adapting Genetic Algorithm contr...

background : drivers are vulnerable to musculoskeletal and psychological disorders because of substantially harmful agents in this stressful occupation. this study aims to investigate the influence of driver’s physical and psychological health on the risk of road accidents using fuzzy logic approach. methods : two input variables including musculoskeletal disorders (msds) and mental health, alo...

organizational performance is a complex issue given that performance is a multifaceted phenomenon whose components may have distinct managerial priorities and may even be mutually inconsistent. recently, the balanced scorecard approach (bsc), as an effective multi-criteria evaluation concept received much attention in organizational performance measurement. although the bsc conceptual framework...

supplier evaluation and selection is complex which caused by the dynamic and fuzzy environment. current mcdm methods do not consider the nature of the environment that can affect the process of evaluation and ranking. the aim of this study is to propose a dynamic fuzzy hybrid mcdm method for evaluation, ranking and selection. the proposed method employs fuzzy analytic hierarchy process (fahp) f...

An important and difficult issue in designing a Fuzzy Inference System (FIS) is the specification of fuzzy sets, and fuzzy rules. The aim of this paper is to demonstrate how an additional qualitative information, i.e., monotonicity property, can be exploited and extended to be part of an FIS designing procedure (i.e., fuzzy sets and fuzzy rules design). In this paper, the FIS is employed as an ...