List of Titles

Prediction of monthly rainfall in Victoria, Australia : Clusterwise linear regression approach

- Bagirov, Adil, Mahmood, Arshad, Barton, Andrew

Authors: Bagirov, Adil , Mahmood, Arshad , Barton, Andrew
Date: 2017
Type: Text , Journal article
Relation: Atmospheric Research Vol. 188, no. (2017), p. 20-29
Relation: http://purl.org/au-research/grants/arc/DP140103213
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Description: This paper develops the Clusterwise Linear Regression (CLR) technique for prediction of monthly rainfall. The CLR is a combination of clustering and regression techniques. It is formulated as an optimization problem and an incremental algorithm is designed to solve it. The algorithm is applied to predict monthly rainfall in Victoria, Australia using rainfall data with five input meteorological variables over the period of 1889–2014 from eight geographically diverse weather stations. The prediction performance of the CLR method is evaluated by comparing observed and predicted rainfall values using four measures of forecast accuracy. The proposed method is also compared with the CLR using the maximum likelihood framework by the expectation-maximization algorithm, multiple linear regression, artificial neural networks and the support vector machines for regression models using computational results. The results demonstrate that the proposed algorithm outperforms other methods in most locations. © 2017 Elsevier B.V.

Clustering in large data sets with the limited memory bundle method

- Karmitsa, Napsu, Bagirov, Adil, Taheri, Sona

Authors: Karmitsa, Napsu , Bagirov, Adil , Taheri, Sona
Date: 2018
Type: Text , Journal article
Relation: Pattern Recognition Vol. 83, no. (2018), p. 245-259
Relation: http://purl.org/au-research/grants/arc/DP140103213
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Description: The aim of this paper is to design an algorithm based on nonsmooth optimization techniques to solve the minimum sum-of-squares clustering problems in very large data sets. First, the clustering problem is formulated as a nonsmooth optimization problem. Then the limited memory bundle method [Haarala et al., 2007] is modified and combined with an incremental approach to design a new clustering algorithm. The algorithm is evaluated using real world data sets with both the large number of attributes and the large number of data points. It is also compared with some other optimization based clustering algorithms. The numerical results demonstrate the efficiency of the proposed algorithm for clustering in very large data sets.

Nonsmooth DC programming approach to the minimum sum-of-squares clustering problems

- Bagirov, Adil, Taheri, Sona, Ugon, Julien

Authors: Bagirov, Adil , Taheri, Sona , Ugon, Julien
Date: 2016
Type: Text , Journal article
Relation: Pattern Recognition Vol. 53, no. (2016), p. 12-24
Relation: http://purl.org/au-research/grants/arc/DP140103213
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Description: This paper introduces an algorithm for solving the minimum sum-of-squares clustering problems using their difference of convex representations. A non-smooth non-convex optimization formulation of the clustering problem is used to design the algorithm. Characterizations of critical points, stationary points in the sense of generalized gradients and inf-stationary points of the clustering problem are given. The proposed algorithm is tested and compared with other clustering algorithms using large real world data sets. © 2015 Elsevier Ltd. All rights reserved.

Patterns of time use among regional and rural adolescent girls : Associations with correlates of physical activity and health-related quality of life

- Casey, Meghan, Harvey, Jack, Telford, Amanda, Eime, Rochelle, Mooney, Amanda, Payne, Warren

Authors: Casey, Meghan , Harvey, Jack , Telford, Amanda , Eime, Rochelle , Mooney, Amanda , Payne, Warren
Date: 2016
Type: Text , Journal article
Relation: Journal of Science and Medicine in Sport Vol. 19, no. 11 (2016), p. 931-935
Relation: http://purl.org/au-research/grants/arc/LP0990206
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Description: Objectives: To describe patterns of time use among regional and rural adolescent girls and compare identified clusters with respect to correlates of physical activity (PA) and health-related quality of life (HRQoL). Methods: Data were from Year 7-9 adolescent girls (aged 12-15 years) from 16 schools involved in a cluster-randomised trial in regional and rural Victoria, Australia (n = 494). Time use data were collected using 24-h Previous Day Physical Activity Recall (PDPAR-24) questionnaire, collapsed into 17 categories of time use. Differences between time use clusters with regard to demographics, correlates of PA and HRQoL measured using PedsQL 4.0 Generic Core Scales, were investigated. Results: Two time use clusters were identified and were associated with correlates of PA and HRQoL. Girls who spent significantly more time in teams sports, non-team sports, school classes, watching TV and sleeping had higher levels of positively aligned PA correlates (e.g. self-efficacy, perceived sports competence) and HRQoL than girls characterised with high levels of computer use and video gaming. Conclusions: These findings highlight how different activity patterns of regional and rural girls affect HRQoL and can inform future intervention strategies to improve PA levels and HRQoL. Clusters characterised by low levels of PA and high computer use and video gaming require targeted interventions to address barriers to their participation. (C) 2016 Published by Elsevier Ltd on behalf of Sports Medicine Australia.

Five decades of research on capital budgeting – a systematic review and future research agenda

- Sureka, Riya, Kumar, Satish, Colombage, Sisira, Abedin, Mohammad

Authors: Sureka, Riya , Kumar, Satish , Colombage, Sisira , Abedin, Mohammad
Date: 2022
Type: Text , Journal article
Relation: Research in International Business and Finance Vol. 60, no. (2022), p.
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Description: This study synthesizes and reviews the existing literature on capital budgeting (CB) practices and their application to theories, contexts, characteristics and methodology. It aims to identify the prevalent issues and gaps in the literature and provide potential avenues for future research. After comprehensive search and rigorous scrutiny, this review encompasses 185 articles. A systematic literature review (SLR), triangulated with the bibliometric method, is carried out, adopting a meticulous approach to achieve a comprehensive overview of the field. Based on cluster analysis, four distinct themes are identified. Additionally, a conceptual framework is developed that shows the antecedents, moderators and outcomes of research on capital budgeting. Grounded on the detailed content analysis, 11 actionable future research directions are proposed to advance this field of research. © 2021 Elsevier B.V.

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