Most fuzzy controllers and fuzzy expert systems must predefine membership functions and fuzzy inference rules to map numeric data into linguistic variable terms and to make fuzzy reasoning work. In this paper, we propose a general learning method as a framework for automatically deriving membership functions and fuzzy if-then rules from a set of given training examples to rapidly build a protot...

Software fault prediction means identification of the faultprone parts in the software. This enables to focus testing activities on those software modules that are predicted as fault-prone. As can be seen in literature, many soft computing techniques are employed to make more accurate predictions previously. However, software fault prediction has not become routine activity in the software deve...

allocation and removing of excess water from the irrigation and drainage network is one of the most important activities in the management of these networks. side weir is one of the most common structures for this purpose. study on the flow hydraulic characteristics of this structure included two parts, defining the water surface profiles and estimating the discharge coefficient. to estimate th...

Competition is the driving force of today's economy and it is vital for organizations to gain competitive advantages. In recent years, outsourcing has been the focus of managers as a tool for developing organizations and improving productivity. This study deals to analyze the outsourcing risks of the supply chain in the automotive industry using fuzzy inference systems. For this purpose, in the...

fuzzy rule-based classification system (frbcs) is a popular machine learning technique for classification purposes. one of the major issues when applying it on imbalanced data sets is its biased to the majority class, such that, it performs poorly in respect to the minority class. however many cases the minority classes are more important than the majority ones. in this paper, we have extended ...

The adaptive neural fuzzy inference system is used to simulate trajectory tracking in aircraft landing operationsmanagement. The advantage of the approach is that by using the linguistic representation ability of fuzzy sets and the learning ability of neural networks, the approximate linguistic representations can be improved or updated as more data become available. This approach is illustrate...

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...

Abtract: The construction of fuzzy rule-based classification systems with both good generalization ability and interpretability is a chalenging issue. The paper aims to present a novel framework for the realization of these important (and many times conflicting) goals simultaneously. The generalization performance is obtained with the adaptation of Support Vector algorithms for the identificati...

Abstract: A Fuzzy logic control law is presented and implemented for trajectory tracking of multiple under actuated autonomous surface vessels. In this study, an individual unmanned ship is used to be the leader that tracks the desired path; other unmanned ships are used to be the followers which track the leader only by using its position. A fuzzy controller was implemented for the ship leader...