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...

Original scientific paper This paper proposes a Neuro-fuzzy system for quantitative assessment of the effects of intelligent transportation systems and technologies on road fatalities. The basic idea in developing Neuro-fuzzy system is the fact that intelligent transportation systems and technologies activate some safety mechanisms and in turn the activation of safety mechanisms will have a pos...

The classical analysis of real time systems tries to ensure that the instance of every task finishes before its absolute deadline (strict guarantee). The probabilistic approach tends to estimate the probability that it will happen. The deterministic timed behavior is an important parameter for analysing the robustness of the system. Most of related works are mainly based on the determinism of t...

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...

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...

Weather prediction is an ever challenging area of investigation for scientists. The Adaptive Neuro-Fuzzy Inference System (ANFIS) has been widely used for modeling different kinds of nonlinear systems including rainfall forecasting. Adaptive Neuro-Fuzzy Inference Systems (ANFIS) combines the capabilities of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) to solve different ki...

A Neuro-Fuzzy (NF) system is a combination of Artificial Neural Network (ANN) and Fuzzy Inference System (FIS) in such a way that ANN learning algorithms are used to determine the parameters of FIS. Potential interactions between connectionist learning systems and evolutionary search procedures have attracted lots of research work recently. There is no guarantee that the learning algorithm conv...

The paper deals with devising the combination of fuzzy inference systems (FIS) and neural networks called the adaptive network fuzzy inference system (ANFIS) to determine the forming limit diagram (FLD). In this paper, FLDs are determined experimentally for two grades of low carbon steel sheets using out-of-plane (dome) formability test. The effect of different parameters such as work hardening...

abstract evapotranspiration as one of the most important components of the hydrologic cycle, plays a key role in water resources management, crop yield simulation and irrigation scheduling. therefore, presenting a low cost and precision model is very essential for calculations of hourly eto. although, there are empirical formulas, their performances are not all satisfactory due to the complicat...

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...