Energy accounting is a system for regularly measuring, analyzing, and reporting the energy use of various activities. This done to increase efficiency monitor impact usage on environment. Primary now by determining amount fossil fuel required generate it. However, if fuels become scarcer, this strategy becomes less viable. Instead, new approach will be required, one that takes into consideratio...

Soft computing is an alternative to hard and classic math models especially when it comes to uncertain and incomplete data. This includes regression and relationship modeling of highly interrelated variables with applications in curve fitting, interpolation, classification, supervised learning, generalization, unsupervised learning and forecast. Fuzzy cognitive map (FCM) is a recurrent neural s...

The search for key sectors in an economy has been and still is one of the more recurrent themes in input–output analysis. When using clustering techniques, sectors can only belong to a group, having a particular performance. But, actually, the same sector could be important from different perspectives at the same time, to a different degree. So, a fuzzy clustering approach is needed. In this wo...

This paper proposes a design for a robust adaptive controller for the Dynamical Positioning (DP) of underwater vehicles with unknown hydrodynamic coefficients, unknown disturbances and input dead-zones. First, for convenience of controller design, the Multi-Input Multi-Output (MIMO) system is divided into several Single-Input Single-Output (SISO) systems. Next, a Dynamic Recurrent Fuzzy Neural ...

This paper describes preference classes and preference Moore machines as a basis for integrating different hybrid neural representations. Preference classes are shown to provide a basic link between neural preferences and fuzzy representations at the preference class level. Preference Moore machines provide a link between recurrent neural networks and symbolic transducers at the preference Moor...

In this paper, we propose a modified hybridization of electromagnetism-like mechanism (EM) and particle swarm optimization (PSO) algorithms, called mEMPSO, for designing the proposed functional-link based Petri recurrent fuzzy neural system (FLPRFNS). The mEMPSO implements an instant update particle velocity strategy such that each particle updates its information instantaneously. For reducing ...

Goal: The present work aims to improve the project portfolio selection processes under uncertainty of pharmaceutical companies by integrating two Multicriteria Decision Making (MCDM) methods in a fuzzy environment: AHP and VIKOR methods. Design / Methodology Approach: We employed normative axiomatic modeling as methodology for our work. MCDM are subjective representing decision-makers preferenc...

Abs t rac t . Approaches to data mining proposed so far are mainly symbolic decision trees and numerical feedforward neural networks methods. While decision trees give, in many cases, lower accuracy compared to feedforward neural networks, the latter show black-box behaviour, long training times, and difficulty to incorporate available knowledge. We propose to use an incrementally-generated rec...

The PAM robot arm is belonged to highly nonlinear systems where perfect knowledge of their parameters is unattainable by conventional modeling techniques because of the timevarying inertia, hysteresis and other joint friction model uncertainties. To guarantee a good tracking performance, robust-adaptive control approaches combining conventional methods with new learning techniques are required....