This paper further extends the ‘kernel’-based approach to clustering proposed by E. Diday in early 70s. According to this approach, a cluster’s centroid can be represented by parameters of any analytical model, such as linear regression equation, built over the cluster. We address the problem of producing regressionwise clusters to be separated in the input variable space by building a hybrid c...

Knowledge management (KM) adoption in the supply chain network needs a good investment as well as few changes in the culture of the entire SC. Knowledge management is the process of creating, distributing and transferring information. The goal of this study is to Rank KM criteria in supply chain network in Iran which is important for firms these days. Criterion used in this paper were extracted...

In this paper, a new hybrid methodology is introduced to design a cost-sensitive fuzzy rule-based classification system. A novel cost metric is proposed based on the combination of three different concepts: Entropy, Gini index and DKM criterion. In order to calculate the effective cost of patterns, a hybrid of fuzzy c-means clustering and particle swarm optimization algorithm is utilized. This ...

In this paper, we construct a hierarchy of hybrid numerical methods for multi-scale kinetic equations based on moment realizability matrices, a concept introduced by Levermore, Morokoff and Nadiga in [15]. Following such a criterion, one can consider hybrid scheme where the hydrodynamic part is given either by the compressible Euler or Navier-Stokes equations, or even with more general models, ...

Nearest neighbor is pattern matching method for time series prediction in which most recent values of the time series are compared with previous available values and forecasting is achieved by finding the best match pattern (nearest neighbor). Usually Euclidean distance is used to check the similarity of pattern. In this paper two hybrid criteria of pattern matching are being proposed and evalu...

Abstract Under the multi-objective framework, this paper presents a hybrid algorithm to solve robust static output feedback control problem for continuous polytopic uncertain system. To obtain static output feedback gain, a new hybrid algorithm is proposed by combination of a hybrid algorithm of the Particle Swarm Optimization (PSO) and Differential Evolution (DE), and the linear matrix inequal...

We study a multiple measurement vector (MMV) problem where multiple signals share a common sparse support set and are sampled by a common sensing matrix. Although we can expect that joint sparsity can improve the recovery performance over a single measurement vector (SMV) problem, compressive sensing (CS) algorithms for MMV exhibit performance saturation as the number of multiple signals increa...

Feature extraction is a very important preprocessing step for classification of hyperspectral images. The linear discriminant analysis (LDA) method fails to work in small sample size situations. Moreover, LDA has a poor efficiency for non-Gaussian data. LDA is optimized by a global criterion. Thus, it is not sufficiently flexible to cope with the multi-modal distributed data. In this work, we p...

In this paper a new concept for control and performance assessment of compressed air energy storage (CAES) systems in a hybrid energy system is introduced. The proposed criterion, based on the concept of energy harvest index (HEI), measures the capability of a storage system to capture renewable energy. The overall efficiency of the CAES system and optimum control and design from the technical ...