In this thesis a neural network-based fuzzy modeling approach to assess student learning characteristic and update the student model in Intelligent Learning Environments is proposed. The neural network-based fuzzy diagnostic model is a general diagnostic model which can be used to implement the diagnostic process in any learning environment according to designers’ and teachers' suggestions. Fuz...

introduction according to the shortage of water resources in the world, it seems necessary the use of refined water, particularly in arid and semi-arid areas such as iran. the correct treatment, management and the control of refining process needs to investigate effective parameters in this process precisely. therefore, because of the uncertainty and complexity in refining qualitative parameter...

Fuzzy neural networks have several features that make them well suited to a wide range of knowledge engineering applications. These strengths include fast and accurate learning, good generalisation capabilities, excellent explanation facilities in the form of semantically meaningful fuzzy rules, and the ability to accommodate both data and existing expert knowledge about the problem under consi...

We propose a weather prediction model in this article based on neural network and fuzzy inference system (NFIS-WPM), and then apply it to predict daily fuzzy precipitation given meteorological premises for testing. The model consists of two parts: the first part is the “fuzzy rule-based neural network”, which simulates sequential relations among fuzzy sets using artificial neural network; and t...

Hierarchical fuzzy neural networks can use less rules to model nonlinear system with high accuracy. But the normal training method for hierarchical fuzzy neural networks is very complex. In this paper we modify the backpropagation approach and employ a time-varying learning nte that is determined from input-output data and model stnicture. Stable learning algorithms for the premise and the cons...

Road accident prediction plays an important role in accessing and improving the road safety. Besides the conventional generalized linear regression, the prediction approaches based on fuzzy logic and neural networks have increasingly been proven to have a significant accident-predicting capability in recent years. However, fuzzy logic and neural network have their respective limitations. For ex...

The recognition of ten Thai isolated numerals from zero to nine and 60 Thai polysyllabic words are compared between different recognition techniques, namely, Neural Network, Modified Rackpropagation Neural Network. Fuzzy-Neural Network, and Hidden Markov Model. The I j-state left-to-right discrete hidden markov model in cooperation with the vector quantization technique has been studied and com...

There are two main approaches to design a neural fuzzy system; namely, through expert knowledge, and through numerical data. While the computational structure of a system is manually crafted by human experts in the former case, self-organizing neural fuzzy systems that are able to automatically extract generalized knowledge from batches of numerical training data are proposed for the latter. Ne...

This paper presents a fuzzy filtered neural network approach as an application to handwritten numerical representation. A multilayer feedforward adaptive network is used for training the model and for application of the fuzzy filters. Fuzzy filters are integrated with the neural nets for processing the physical data of the images available for the handwritten digits. The use of the fuzzy filter...