Many real-world problems can be cast into a multiple-information aggregation framework where preliminary evaluations of separate information sources are combined to produce more accurate and reliable evaluation than would otherwise be the case. In this paper we describe a syllable-proximity evaluation problem in automatic speech recognition that fits well into this aggregation framework. A fuzz...

In this paper we present a study on the application of fuzzy sets for the start-up optimisation of a combined cycle power plant. We fuzzyfy the output process variables and then we properly combine the resulting fuzzy sets in order to get a single value in the lattice [0,1] providing the effectiveness (zero bad, one excellent) of the given start-up regulations. We tested the methodology on a la...

This paper processes a combined method, based on VIKOR and Data Envelopment Analysis (DEA) to select the units with most efficiency. We utilize the VIKOR as compromise solution method. This research is a two-stage model designed to fully rank the alternatives, where each alternative has multiple inputs and outputs. The problem involves BELIEF parameters in the solution procedure. First, the alt...

Fuzzy logic is an important technique for modeling uncertainty in expert systems (i.e., in cases where inferencing of conclusion from given evidence is difficult to ascertain). This paper proposes a fuzzy expert system framework that combines case-based and rule-based reasoning effectively to produce a usable tool for Type 2 Diabetes Mellitus (T2DM) management. The major targets are on combined...

Data envelopment analysis is a nonparametric technique checking efficiency of DMUs using math programming. In conventional DEA, it has been assumed that the status of each measure is clearly known as either input or output. Kao and Hwang (2008) developed a data envelopment analysis (DEA) approach for measuring efficiency of decision processes which can be divided into two stages. The first stag...

The increasing technology of high-resolution image airborne sensors, including those on board Unmanned Aerial Vehicles, demands automatic solutions for processing, either on-line or off-line, the huge amountds of image data sensed during the flights. The classification of natural spectral signatures in images is one potential application. The actual tendency in classification is oriented toward...

In this paper a combination of neuro-fuzzy classifiers for improved classification performance and reliability is considered. A general fuzzy min-max (GFMM) classifier with agglomerative learning algorithm is used as a main building block. An alternative approach to combining individual classifier decisions involving the combination at the classifier model level is proposed. The resulting class...

A systematic approach for constructing interpretable fuzzy model based on reduction methodology is proposed. Fuzzy clustering algorithm, combined with least square method, is used to identify initial fuzzy model with overestimated rule number. Orthogonal least square algorithm and similar fuzzy sets merging are then applied to remove redundancy of the fuzzy model. In order to obtain high accura...

A generalized probability mixture density governs an additive fuzzy system. The fuzzy system’s if-then rules correspond to the mixed probability densities. An additive fuzzy system computes an output by adding its fired rules and then averaging the result. The mixture’s convex structure yields Bayes theorems that give the probability of which rules fired or which combined fuzzy systems fired fo...

the concept of intelligently controlling the search process of gravitational search algorithm (gsa) is introduced to develop a novel data mining technique. the proposed method is called fuzzy gsa miner (fgsa-miner). at first a fuzzy controller is designed for adaptively controlling the gravitational coefficient and the number of effective objects, as two important parameters which play major ro...