The structure and performance of organisations – natural or manmade – are intricately linked, and these multifaceted interactions are increasingly being investigated using Multi Agent System concepts. This paper shows how a selection of generic structural metrics for organisations can be explored using a combination of Pareto Frontier exemplars, from extensive simulations of simple goal-orienta...

A new output-based method for non-intrusive assessment of speech quality for voice communication system is proposed and its performance evaluated. The method is based on comparing the output speech to an appropriate reference representing the closest match from a pre-formulated codebook containing optimally clustered speech parameter vectors extracted from a large number of various undistorted ...

Over 3 000 Mozambican smallholder farmers supply cassava to Company XYZ. XYZ needs an effective supplier segmentation method gain insight into how it should direct its resources for the greatest impact. This paper describes application of the  k -means algorithm, agglomerative hierarchical clustering, and a self-organising map with ward clustering segment these suppliers. The insights gained fr...

Automatic mood detection from music has two main benefits. Firstly, having the knowledge of mood in advance can allow for possible enhancement of the music experience (such as mood-based visualizations) and secondly it makes 'query by mood' from music data-banks possible. This research is concerned with the automatic detection of mood from the electronic music genre, in particular that of drum ...

This chapter investigates the use of different artificial intelligence and classical techniques for forecasting the monthly yield of the US 10-year Treasury bonds from a set of four economic indicators. The task is particularly challenging due to the sparseness of the data samples and the complex interactions amongst the variables. At the same time, it is of high significance because of the imp...

The ability to grow extra nodes is a potentially useful facility for a self-organising neural network. A network that can add nodes into its map space can approximate the input space more accurately, and often more parsimoniously, than a network with predefined structure and size, such as the Self-Organising Map. In addition, a growing network can deal with dynamic input distributions. Most of ...

Object discovery in visual object categorisation (VOC) is the problem of automatically assigning class labels to objects appearing in given images. To achieve stateof-the-art results in this task, a large set of positive and negative training images from publicly available benchmark data sets have been used to train discriminative classification methods. The immediate drawback of these methods ...

In this presentation I will discuss modern imputation methods based on the neural nets methodology. The most important method used here is the Tree-Structured Self-Organising Map, or TS-SOM. The TS-SOM is a computationally fast variation of the basic Self-Organising Maps, or SOMs. It is a combination of the SOM, tree-structured clustering and computational speedup techniques. SOM is an iterativ...

1. ABSTRACT There are many reports of patients who, after sustaining brain damage, exhibit a selective recognition deficit for certain categories of object. There has been much controversy as to whether this is informative about the neural organisation of knowledge in the human brain. In this paper we describe an unsupervised neural network model that is trained to process images from a variety...

With so much modern music being so widely available both in electronic form and in more traditional physical formats, a great opportunity exists for the development of a general-purpose recognition and music classification system. We describe an ongoing investigation into the subject of musical recognition purely by the sonic content from a standard recording.