7 results for Aldridge, Colin H

  • Scale-free networks: a model for regional seismic systems?

    Aldridge, Colin H (2004-11)

    Conference item
    University of Otago

    Only the abstract was published in the proceedings. There is no full text.

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  • Sport and time geography: a good match?

    Moore, Antoni; Whigham, Peter A; Holt, Alec; Aldridge, Colin H; Hodge, Ken (2003-12)

    Conference paper
    University of Otago

    This paper proposes using the rich visual “language” of Hägerstrand’s time geography to represent time-space relationships in sport, in particular within the spatial and temporal constraints of a game of rugby. Despite being applied outside of its traditional social context, it is argued that time geography’s ability to model movements and relationships at the individual level makes it (and its modelling constructs such as prisms and lifelines) a powerful visualisation tool able to provide valuable insights into goal-oriented team sport. The visual tools of time geography are shown in the context of a video information system, SCRUM (Spatio-Chronological Rugby Union Model).

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  • Methods for creating scale-free networks without resorting to global knowledge

    Aldridge, Colin H (2005-11)

    Conference paper
    University of Otago

    This paper is a progress report on investigations into methods for evolving scalefree networks using less-than-global knowledge of network characteristics. The motivation for this work is the reliance on global knowledge by the now wellknown Albert-Barabási algorithm for evolving fat-tailed networks exhibiting powerlaw node degree distributions. This paper examines three approaches, namely tournament selection, a deterministic walk, and a stochastic walk. These methods yield fat-tailed node degree distributions to a greater or lesser extent, but not "classic" power-law distributions. The investigation is on-going.

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  • The "Kawachi" algorithm: a single-parameter network constructor?

    Aldridge, Colin H (2007-12-06)

    Conference item
    University of Otago

    Only the abstract and references were published in the proceedings. There is no full text.

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  • Spatio-temporal and object visualization in rugby union

    Moore, Antoni; Whigham, Peter A; Aldridge, Colin H; Holt, Alec; Hodge, Ken (2002-06)

    Working or discussion paper
    University of Otago

    The use of computer software as an aid to rugby, and sports coaching in general, is becoming increasingly utilized. Videoed sport is the most widely used form of raw data for sports analysis, though it is currently not being used to its full potential. Patterns of player movement and position, both for individuals and groupings of players, are important for understanding the complexities of professional team sports, and yet are not being adequately addressed. This paper outlines a project that aims to support coaching and/or commentary by visualizing and measuring the similarity of video-derived spatiotemporal information, and enabling timely access to relevant video clips. Specifically, methods by which a user of spatially-enabled sports software can visualize spatio-temporal and rugby object information will be discussed. Two issues are examined: (1) powerful spatio-temporal representation techniques for rugby constructs (such as the pitch, players and amalgamations of players: team, scrum, lineout, backline) and (2) user interface design and how it enables rugby object representation alongside the spatio-temporal visualization facility.

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  • Playing possum with knowledge discovery: inducing population density models from spatially referenced ecological data

    Aldridge, Colin H (2003-12)

    Conference paper
    University of Otago

    The author’s rough set based knowledge induction methodology (Aldridge 1998) and the C4.5 decision tree algorithm (Quinlan 1993) are applied to spatially referenced ecological data to develop models making use of spatial relationships. The data set records the habitat characteristics and the population distribution of a species of Australian arboreal marsupial, Peteroides volans, commonly known as the greater glider possum. The study area is 1600 hectares of south-eastern Australian coastal ranges and tableland. The ability of the possums to glide between trees suggested that identifying spatial relationships between habitat variables might be important when predicting local population density. A variable-sized “context window” is used in the search for spatial relationships. Other researchers using several machine learning methods to generate both spatial and non-spatial models have already studied the greater glider dataset. The results of these earlier studies are used as benchmarks against which to compare the results of the present work. The models developed using the rough set based algorithms are found to be statistically indistinguishable in terms of classification accuracy from the best of the models reported in the literature.

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  • A shape metric for evolving time series models

    Whigham, Peter A; Aldridge, Colin H (2000-04)

    Working or discussion paper
    University of Otago

    Most applications of Genetic Programming to time series modeling use a fitness measure for comparing potential solutions that treat each point in the time series independently. This non-temporal approach can lead to some potential solutions being given a relatively high fitness measure even though they do not correspond to the training data when the overall shape of the series is taken into account. This paper develops two fitness measures which emphasize the concept of shape when measuring the similarity between a training and evolved time series. One approach extends the root mean square error to higher dimensional derivatives of the series. The second approach uses a simplified derivative concept that describes shape in terms of positive, negative and zero slope.

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