Otago University Research Archive
Browsing Knowledge Engineering Laboratory by Date Published
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Browsing Knowledge Engineering Laboratory by Date Published
Now showing items 1-20 of 25
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(Discussion Paper, 2001)Fuzzy neural networks are connectionist systems that facilitate learning from data, reasoning over fuzzy rules, rule insertion, rule extraction, and rule adaptation. The concept evolving fuzzy neural networks (EFuNNs), ... -
(Discussion Paper, 2000)In any data set there some of the data will be bad or noisy. This study identifies two types of noise and investigates the effect of each in the training data of backpropagation neural networks. It also compares the mean ... -
(Discussion Paper, 2000)Although widely studied for many years, colour image quantisation remains a challenging problem. We propose to use an evolving self-organising map model for the on-line image quantisation tasks. Encouraging results are ... -
(Discussion Paper, 2000)In a consensus ensemble all members must agree before they classify a data point. But even when they all agree some data is still misclassified. In this paper we look closely at consistently misclassified data to investigate ... -
(Discussion Paper, 2000)The paper applies novel techniques for on-line, adaptive learning of macroeconomic data and a consecutive analysis and prediction. The evolving connectionist system paradigm (ECOS) is used in its two versions—unsupervised ... -
(Discussion Paper, 2000)In real world information systems, data analysis and processing are usually needed to be done in an on-line, self-adaptive way. In this respect, neural algorithms of incremental learning and constructive network models are ... -
(Discussion Paper, 2000)The English and Māori word translator ngā aho whakamāori-ā-tuhi was designed to provide single head-word translations to on-line web users. There are over 13,000 words all based on traditional text sources, derived because ... -
(Discussion Paper, 2000)Māori speech data collection and analysis is an ongoing process, as new and existing data sets are continuously accessed for many different experimental speech perception and generation processing tasks. A data management ... -
(Discussion Paper, 2000)We report on the clustering of nodes in internally represented acoustic space. Learners of different languages partition perceptual space distinctly. Here, an Evolving Connectionist-Based System (ECOS) is used to model the ... -
(Discussion Paper, 1999)The speech recognition field is one of the most challenging fields that has faced scientists for a long time. The complete solution is still far from reach. The efforts are concentrated with huge funds from the companies ... -
(Discussion Paper, 1999)The chapter presents a new methodology for building adaptive, incremental learning systems for image pattern classification. The systems are based on dynamically evolving fuzzy neural networks that are neural architectures ... -
(Discussion Paper, 1999)The paper is a study on a new class of spatial-temporal evolving fuzzy neural network systems (EFuNNs) for on-line adaptive learning, and their applications for adaptive phoneme recognition. The systems evolve through ... -
(Discussion Paper, 1999)The paper introduces evolving connectionist systems (ECOS) as an effective approach to building on-line, adaptive intelligent systems. ECOS evolve through incremental, hybrid (supervised/unsupervised), on-line learning. ... -
(Discussion Paper, 1999)In this paper, an adaptive neuro-fuzzy system, called HyFIS, is proposed to build and optimise fuzzy models. The proposed model introduces the learning power of neural networks into the fuzzy logic systems and provides ... -
(Discussion Paper, 1999)The paper introduces a new type of evolving fuzzy neural networks (EFuNNs), denoted as mEFuNNs, for on-line learning and their applications for dynamic time series analysis and prediction. mEFuNNs evolve through incremental, ... -
(Discussion Paper, 1999)This paper discusses the problem of adaptation in automatic speech recognition systems (ASRS) and suggests several strategies for adaptation in a modular architecture for speech recognition. The architecture allows for ... -
(Discussion Paper, 1998)This paper describes combined approaches of data preparation, neural network analysis, and fuzzy inferencing techniques (which we collectively call neuro-fuzzy engineering) to the problem of environmental modelling. The ... -
(Discussion Paper, 1998)Biological processes are among the most challenging to predict and control. It has been recognised that the development of an intelligent system for the recognition, prediction and control of process states in a complex, ... -
(Discussion Paper, 1998)Variation in fruit maturation can influence harvest timing and duration, post-harvest fruit attributes and consumer acceptability. Present methods of managing and identifying lines of fruit with specific attributes both ... -
(Discussion Paper, 1998)The paper introduces one paradigm of neuro-fuzzy techniques and an approach to building on-line, adaptive intelligent systems. This approach is called evolving connectionist systems (ECOS). ECOS evolve through incremental, ...
Now showing items 1-20 of 25