introduction: the adaptive neuro-fuzzy inference system (anfis) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. in this study we used this model in breast cancer detection. methodology: a set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used.  first, the risk fact...

accurate analysis and interpolation of heavy metals, especially arsenic concentrationin ground watercan play a significant role in planning and continuous monitoring of water resources. the analysis may also prevent human health issues.the purpose of this paper was to evaluate newly published sugeno type fuzzy inference system as an interpolation method for estimating the amount of arsenic in k...

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...

The ball and beam system is one of the most popular laboratory setups for control education. In this paper, we design a fuzzy PD cascade controller for a ball and beam system using Asexual Reproduction Optimization (ARO) technique. The ball & beam system consists of a servo motor, a grooved beam, and a rolling ball. This system utilizes a servo motor to control ball’s position on the beam. Chan...

Introduction: In radiotherapy with external surrogates, exact information of tumor position is one of the key factors that improves treatment delivery. Many dynamic tumors in thorax region of patient move mainly due to respiration and are known as intra-fractional motion error that must be compensated, as well. One of clinical strategy is using Stereotactic Body Radiation Thera...

This paper presents an adaptive neuro-fuzzy controller ANFIS (Adaptive Neuro-Fuzzy Inference System) for a bilateral teleoperation system based on FPGA (Field Programmable Gate Array). The proposed controller combines the learning capabilities of neural networks with the inference capabilities of fuzzy logic, to adapt with dynamic variations in master and slave robots and to guarantee good prac...

In this study, the road traffic congestion of Dehradun city is evaluated from traffic flow information using fuzzy techniques. Three different approaches namely Sugeno, Mamdani models which are manually tuned techniques, and an Adaptive Neuo-Fuzzy Inference System (ANFIS) which an automated model decides the ranges and parameters of the membership functions using grid partition technique, based...

This article presents a study on the use of parametrized operators in the Inference System of linguistic fuzzy systems adapted by evolutionary algorithms, for achieving better cooperation among fuzzy rules. This approach produces a kind of rule cooperation by means of the inference system, increasing the accuracy of the fuzzy system without losing its interpretability. We study the different al...

In this paper, we consider the production possibility set with n production units such that the following four principles that governs: inclusion observations, conceivability, immensity and convexity. Our goal is to estimate the output of a same and new production unit with existing production possibility and amount of input is specified. So, initially we find the interval changes of each input...