Data integration for distributed and heterogeneous XML data sources is still an open challenging, and XML DTD matching is crucial task in this process. A considerable amount of algorithms for comparing XML DTDs have been proposed in the literature. Yet, the existing approaches fall short in ability to identify semantic similarities in fuzzy XML DTDs. To fill this gap, in this paper, we provide ...

Today hybrid computing is a popular framework for solving complex problems. If we have knowledge expressed in rules, we can build an Expert System, and if we have data, or can learn from stimulation (training) then we can use Artificial Neural Networks. In this paper we present the FUzzy NEUrule System (FUNEUS) which is a Neuro Fuzzy approach based on fuzzy Adaline neurons and uses Differential...

The complexity of an autonomous robot's navigation task, poses several roadblocks to the use of traditional fuzzy control schemes, such as much larger input space than typical fuzzy applications, adding inputs increases the required number of set evaluations exponentially, as the size of a rule base swells, manual description becomes difficult to impossible. Therefore in this paper a new behavi...

Fusion of Artificial Neural Networks (ANN) and Fuzzy Inference Systems (FIS) have attracted the growing interest of researchers in various scientific and engineering areas due to the growing need of adaptive intelligent systems to solve the real world problems. ANN learns from scratch by adjusting the interconnections between layers. FIS is a popular computing framework based on the concept of ...

The purpose of this paper is to provide an algorithm for the motion picture companies to evaluate the key capabilities from firm viewpoint under fuzzy environment. The fundamental concepts we have adopted include the eigenvector method, fuzzy Delphi method, fuzzy set theory, and multi-criteria decision making method. With the concept of balanced scorecard and the interviewing managers of motion...

This paper proposes a nonlinear approach for designing traffic responsive and coordinated ramp control using a self adapting fuzzy system. The traffic responsive metering rate is determined every minute by an adaptive fuzzy logic algorithm. The coordination between multiple on-ramps is ensured by the integration of a common input into all ramp controllers upstream of a bottleneck and a periodic...

Model predictive control (MPC) is a well-known control technique, which has been applied to complex and nonlinear processes. Fuzzy predictive control incorporates fuzzy goals and constraints in MPC, by combining predictive control with fuzzy decision making. In this paper, we propose the integration of weighted criteria in fuzzy predictive control, where the decision-maker can specify the prefe...

This paper studies a stabilization problem for a multirate digital control of fuzzy systems based on the approximately discretized model. In the multirate control scheme, a numerical integration scheme is used to approximately predict the current state from the state measured at the sampling points. It is shown that the multirate digital fuzzy controller stabilizing an approximate discrete-time...

Fuzzy sets, having been the long-standing mainstay of modeling and manipulating imperfect information, are an obvious candidate for representing uncertain beliefs. Unfortunately, unadorned fuzzy sets are too limited to capture complex or potentially inconsistent beliefs, because all too often they reduce to absurdities (“nothing is possible”) or trivialities (“everything is possible”). However,...

This paper proposes a fuzzy inference based neural network for the forecasting of short term loads. The forecasting model is the integration of fuzzy inference engine and the neural network, known as Fuzzy Inference Neural Network (FINN). A FINN initially creates a rule base from existing historical load data. The parameters of the rule base are then tuned through a training process, so that th...