One aspect of the use of biomass for energy purposes which remains controversial concerns their full environmental sustainability. Considering the crucial importance of this problem, numerous authors have carried out evaluations of the environmental impact of the various types of biomass by means of several approaches. Although some of these methods are excellent environmental evaluation tools,...

In this paper, an empirical evaluation of three infer­ ence methods for uncertain reasoning is presented in the context of Pathfinder, a large expert system for the diagnosis of lymph node pathology. The inference procedures evaluated are (1) Bayes' theorem, a:ssum­ ing evidence is conditionally independent given each hypothesis, (2) odds-likelihood updating, assuming evidence is conditionally ...

Abstract – This paper investigates the identification of nonlinear systems by neural networks. As the identification methods, Feedforward Neural Networks (FNN), Radial Basis Function Neural Networks (RBFNN), Runge-Kutta Neural Networks (RKNN) and Adaptive Neuro Fuzzy Inference Systems (ANFIS) based identification mechanisms are studied and their performances are comparatively evaluated on a thr...

introduction: epilepsy is a clinical syndrome in which seizures have a tendency to recur. sodium valproate is the most effective drug in the treatment of all types of generalized seizures. finding the optimal dosage (the lowest effective dose) of sodium valproate is a real challenge to all neurologists. in this study, a new approach based on adaptive neuro-fuzzy inference system (anfis) was pre...

In this work, an artificial neural network (ANN) model along with a combination of adaptive neuro-fuzzy inference system (ANFIS) and particle swarm optimization (PSO) i.e. (PSO-ANFIS) are proposed for modeling and prediction of the propylene/propane adsorption under various conditions. Using these computational intelligence (CI) approaches, the input parameters such as adsorbent shape (S<su...

In this paper, a new fuzzy interpolative reasoning method is proposed for the sparse rule bases by using the highest points and slopes of the antecedent and consequent fuzzy sets. The proposed fuzzy reasoning methods are not only suitable for the four kinds of fuzzy sets in inference rules, but also can guarantee the convexity and normality of the reasoning consequence. Furthermore, the computa...

Seismic hazard assessment like many other issues in seismology is a complicated problem, which is due to a variety of parameters affecting the occurrence of an earthquake. Uncertainty, which is a result of vagueness and incompleteness of the data, should be considered in a rational way. Using fuzzy method makes it possible to allow for uncertainties to be considered. Fuzzy inference system,...

A comparison is made of two approaches to approximate reasoning: Mamdani's interpolation method and the implication method. Both approaches are variants of Zadeh's compositional rule of inference. It is shown that the approaches are not equivalent. A correspondence between the approaches is established via the inverse of the implied fuzzy relation. The interpolation method has the lowest time-c...