a‎s we know, developing mathematical models and numerical procedures that would appropriately treat and solve systems of linear equations where some of the system's parameters are proposed as fuzzy numbers is very important in fuzzy set theory. for this reason, many researchers have used various numerical methods to solve fuzzy linear systems. in this paper, we define the concepts of midpoint a...

‎this paper deals with one problem that needs to be addressed in the emerging field known under the name computing with perceptions‎. ‎it is the problem of describing‎, ‎approximately‎, ‎a given fuzzy set in natural‎ ‎language‎. ‎this problem has lately been referred to as the problem of retranslation‎. ‎an approaches to ‎dealing with the retranslation problem is discussed in the paper‎, ‎that ...

CFNN hybrid system in Multi-sensor data fusion introduced fuzzy logic reasoning and neural network adaptive, self-learning ability, and using fuzzy neurons, so networking skills appropriate to adjust the input and output fuzzy membership function, and can dynamically optimize fuzzy reasoning in global by means of compensated logic algorithm, to make the network more fault tolerance, stability a...

An extension of the Adaboost algorithm is proposed for obtaining fuzzy rule based classifiers from imprecisely perceived data. Isolated fuzzy rules are regarded as weak learners, and knowledge bases as ensembles. Rules are iteratively added to a base, and the search of the best rule at each iteration is carried out by a genetic algorithm driven by a fuzzy fitness function. The successive weight...

Risk management is one of the most influential parts of project management that has a major impact on the success or failure of projects. Due to the increasing use of information technology (IT) systems in all fields and the high failure rate of IT projects in software development and production, it is essential to effectively manage these projects is essential. Therefore, this study is aimed t...

Application of fuzzy logic structures in computeraided design (CAD) of digital electronics substantially improves quality of design solutions by providing designers with flexibility in formulating goals and selecting tradeoffs. In addition, the following aspects of a design process are positively impacted by application of fuzzy logic: utilization of domain knowledge, interpretation of uncertai...

In this paper neuro-fuzzy technique is used for the first time in modeling eco-friendly furnace parameters to predict the melting rate of the molten metal required to produce homogenous and quality castings. The relationship between the process variables (input) viz. flame temperature, preheat air temperature, rotational speed of the furnace dome, percentage of excess air, melting time, fuel co...

A fuzzy multi-criteria group decision making approach that makes use of quality function deployment (QFD), fusion of fuzzy information and 2-tuple linguistic representation model is developed for supplier selection. The proposed methodology seeks to establish the relevant supplier assessment criteria while also considering the impacts of inner dependence among them. Two interrelated house of qu...

Synopsis Water quantity and quality are considered to be the main driving forces the reservoir operation. Barra Bonita reservoir, located in the southeast region of Brazil, is chosen as the case study for the application of the proposed methodology. Herein, optimization and artificial intelligence (AI) techniques are applied in the simulation and operation of the reservoir. A fuzzy stochastic d...

Capability indices compare the actual performance of a manufacturing process to the desired performance. In practice these indices are estimated using sample data, often with quite small sample sizes. Thus, it is of interest to obtain confidence limits for actual capability index given a sample estimate. Most of the traditional methods for assessing the capability of manufacturing process are d...