Fuzzy associative memories (FAMs) belong to the class of fuzzy neural networks (FNNs). A FNN is an artificial neural network (ANN) whose input patterns, output patterns, and/or connection weights are fuzzy-valued [19, 11]. Research on FAM models originated in the early 1990’s with the advent of Kosko’s FAM [35, 37]. Like many other associative memory models, Kosko’s FAM consists of a single-lay...

Abstract. The 2-tuple linguistic computational model is an important tool to deal with linguistic information. To extend the application of hesitant fuzzy linguistic term sets and avoid information loss, this paper introduces hesitant fuzzy 2-tuple linguistic term sets that are expressed by using several symbolic numbers in [0,1]. Considering the order relationship between hesitant fuzzy 2tuple...

The fuzzy weighted average is widely used to solve hierarchical evaluation problems, including fuzzy consideration for the operations of scoring, weighting and aggregating. Previous works considered the fuzziness of score and weight, and used the additive function to aggregate these weighted scores. This study considers the aggregation operator also as a fuzzy variable, and uses a generalized m...

The research aims to prioritize the solutions overcome challenges of Lean Six Sigma 4.0 (LSS 4.0). It is an integrated approach with lean, six sigma, and Industry attributes. This helps achieve organizational excellence sustainable development goals. Fuzzy stepwise weight assessment ratio analysis (fuzzy-SWARA) was used estimate weights LSS challenges. Furthermore, fuzzy-weighted aggregated sum...

This paper gives a study of how to carry out a combined refrigerant volume control using an electronic expansion valve (EEV) and the specific measures to apply selftuning fuzzy algorithm to refrigeration control system. The simulation analysis on the superheat fuzzy controller was completed by Simulink. Different scale factors and weight factors were employed during the process, and their effec...

In this paper we propose a novel training algorithm for RBF networks that is based on extended kalman filter and fuzzy logic.After the user choose how many prototypes to include in the network, the extended kalman filter simultancously solves for the prototype vectors and the weight matrix.The fuzzy logic is used to cope with the devergence problem caused by the insufficiently known a priori fi...

In this article, by using fuzzy AHP and TOPSIS technique we propose a new method for project selection problem. After reviewing four common methods of comparing alternatives investment (net present value, rate of return, benefit cost analysis and payback period) we use them as criteria in AHP tree. In this methodology by utilizing improved Analytical Hierarchy Process by Fuzzy set theory, first...

Localization is one of the most important research topics in the wireless sensor network applications. To improve the indoor localization accuracy, the centroid localization algorithm based on Mamdani fuzzy system has been adopted to attain the weight between sensor node and anchor node. This paper proposes a novel optimized input membership function by bat algorithm in fuzzy inference system u...

A new neuro-fuzzy system’s architecture and a learning method that adjusts its weights as well as automatically determines a number of neurons, centers’ location of membership functions and the receptive field’s parameters in an online mode with high processing speed is proposed in this paper. The basic idea of this approach is to tune both synaptic weights and membership functions with the hel...