A data mining application of the incidence semirings
- Authors: Abawajy, Jemal , Kelarev, Andrei , Yearwood, John , Turville, Christopher
- Date: 2013
- Type: Text , Journal article
- Relation: Houston Journal of Mathematics Vol. 39, no. 4 (2013), p. 1083-1093
- Relation: http://purl.org/au-research/grants/arc/LP0990908
- Full Text: false
- Reviewed:
- Description: This paper is devoted to a combinatorial problem for incidence semirings, which can be viewed as sets of polynomials over graphs, where the edges are the unknowns and the coefficients are taken from a semiring. The construction of incidence rings is very well known and has many useful applications. The present article is devoted to a novel application of the more general incidence semirings. Recent research on data mining has motivated the investigation of the sets of centroids that have largest weights in semiring constructions. These sets are valuable for the design of centroid-based classification systems, or classifiers, as well as for the design of multiple classifiers combining several individual classifiers. Our article gives a complete description of all sets of centroids with the largest weight in incidence semirings.
A Tool for Assisting Group Decision-Making for Consensus Outcomes in Organizations
- Authors: Afshar, Faye , Yearwood, John , Stranieri, Andrew
- Date: 2006
- Type: Text , Book chapter
- Relation: E-Supply Chain Technologies and Management p. 316-343
- Full Text: false
- Reviewed:
Performance evaluation of multivariate non-normal process using metaheuristic approaches
- Authors: Ahmad, S. , Abdollahian, Mali , Bhatti, M.I. , Huda, Shamsul , Yearwood, John
- Date: 2014
- Type: Text , Journal article
- Relation: Journal of Applied Statistical Science Vol. 20, no. 3 (2014), p. 299-315
- Full Text: false
- Reviewed:
- Description: Multivariate process performance indices generally rely on the assumption that the process follow normal distribution but in practice its non-normal with correlated characteristics patterns. This paper proposes two metaheuristic-based approaches to fit Burr distribution to such data; a single candidate model based approach using a Simulated Annealing (SA) technique and a population based approach using a constraint-based Evolutionary Alogorithn (EA). The fitted Burr distribution is then used to estimate the proportion of Non-conforming (PNC) which is then used to fit an appropiate Burr distribution to individual Geometric distance variables. Empirical performance of the proposed methods have been evaluated on real industrial data set using PNC criterion. Experimental results demonstrate that the new approach perform well than the existing.
An argumentation-based multi-agent system for e-tourism dialogue
- Authors: Avery, John , Yearwood, John , Stranieri, Andrew
- Date: 2001
- Type: Text , Conference paper
- Relation: Paper presented at Hybrid Information Systems, First International Workshop on Hybrid Intelligent Systems, Adelaide : 11th - 12th December, 2003 p. 497-512
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000112
Managing ontology evolution : Capturing the semantics of change
- Authors: Avery, John , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the Tenth Australian World Wide Web Conference, Gold Coast, Queensland : 4th July, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000844
A global optimization approach to classification
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John
- Date: 2002
- Type: Text , Journal article
- Relation: Optimization and Engineering Vol. 9, no. 7 (2002), p. 129-155
- Full Text: false
- Reviewed:
- Description: In this paper is presented an hybrid algorithm for finding the absolute extreme point of a multimodal scalar function of many variables. The algorithm is suitable when the objective function is expensive to compute, the computation can be affected by noise and/or partial derivatives cannot be calculated. The method used is a genetic modification of a previous algorithm based on the Prices method. All information about behavior of objective function collected on previous iterates are used to chose new evaluation points. The genetic part of the algorithm is very effective to escape from local attractors of the algorithm and assures convergence in probability to the global optimum. The proposed algorithm has been tested on a large set of multimodal test problems outperforming both the modified Prices algorithm and classical genetic approach.
- Description: C1
- Description: 2003000061
Optimization of feed forward MLPs using the discrete gradient method
- Authors: Bagirov, Adil , Yearwood, John , Ghosh, Ranadhir
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at CIMCA 2004: International Conference on Computational Intelligence for Modelling, Control & Automation, Gold Coast, Queensland : 12th July, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000845
An algorithm for clustering based on non-smooth optimization techniques
- Authors: Bagirov, Adil , Rubinov, Alex , Sukhorukova, Nadezda , Yearwood, John
- Date: 2003
- Type: Text , Journal article
- Relation: International Transactions in Operational Research Vol. 10, no. 6 (2003), p. 611-617
- Full Text: false
- Reviewed:
- Description: The problem of cluster analysis is formulated as a problem of non-smooth, non-convex optimization, and an algorithm for solving the cluster analysis problem based on non-smooth optimization techniques is developed. We discuss applications of this algorithm in large databases. Results of numerical experiments are presented to demonstrate the effectiveness of this algorithm.
- Description: C1
- Description: 2003000422
A new nonsmooth optimization algorithm for minimum sum-of-squares clustering problems
- Authors: Bagirov, Adil , Yearwood, John
- Date: 2006
- Type: Text , Journal article
- Relation: European Journal of Operational Research Vol. 170, no. 2 (2006), p. 578-596
- Full Text: false
- Reviewed:
- Description: The minimum sum-of-squares clustering problem is formulated as a problem of nonsmooth, nonconvex optimization, and an algorithm for solving the former problem based on nonsmooth optimization techniques is developed. The issue of applying this algorithm to large data sets is discussed. Results of numerical experiments have been presented which demonstrate the effectiveness of the proposed algorithm. © 2004 Elsevier B.V. All rights reserved.
- Description: C1
- Description: 2003001520
Using global optimization to improve classification for medical diagnosis and prognosis
- Authors: Bagirov, Adil , Rubinov, Alex , Yearwood, John
- Date: 2001
- Type: Text , Journal article
- Relation: Topics in health information management Vol. 22, no. 1 (2001), p. 65-74
- Full Text: false
- Description: Global optimization-based techniques are studied in order to increase the accuracy of medical diagnosis and prognosis with data from various databases. First, we discuss feature selection, the problem of determining the most informative features for classification in the databases under consideration. Then, we apply a technique based on convex and global optimization for classification in these databases. The third application of this technique is a method that calculates centers of clusters to predict when breast cancer is likely to recur in patients for which cancer has been removed. The technique achieves high accuracy with these databases. Better classifiers will lead to improved assistance in making medical diagnostic and prognostic decisions.
- Description: 2003003662
A novel approach to optimal pump scheduling in water distribution systems
- Authors: Bagirov, Adil , Barton, Andrew , Mala-Jetmarova, Helena , Al Nuaimat, Alia , Ahmed, S. T. , Sultanova, Nargiz , Yearwood, John
- Date: 2012
- Type: Text , Conference paper
- Relation: 14th Water Distribution Systems Analysis Conference 2012, WDSA 2012 Vol. 1; Adelaide, Australia; 24th-27th September; p. 618-631
- Relation: http://purl.org/au-research/grants/arc/LP0990908
- Full Text: false
- Reviewed:
- Description: The operation of a water distribution system is a complex task which involves scheduling of pumps, regulating water levels of storages, and providing satisfactory water quality to customers at required flow and pressure. Pump scheduling is one of the most important tasks of the operation of a water distribution system as it represents the major part of its operating costs. In this paper, a novel approach for modeling of pump scheduling to minimize energy consumption by pumps is introduced which uses pump's start/end run times as continuous variables. This is different from other approaches where binary integer variables for each hour are typically used which is considered very impractical from an operational perspective. The problem is formulated as a nonlinear programming problem and a new algorithm is developed for its solution. This algorithm is based on the combination of the grid search with the Hooke-Jeeves pattern search method. The performance of the algorithm is evaluated using literature test problems applying the hydraulic simulation model EPANet.
- Description: E1
An algorithm for minimization of pumping costs in water distribution systems using a novel approach to pump scheduling
- Authors: Bagirov, Adil , Barton, Andrew , Mala-Jetmarova, Helena , Al Nuaimat, Alia , Ahmed, S. T. , Sultanova, Nargiz , Yearwood, John
- Date: 2013
- Type: Text , Journal article
- Relation: Mathematical and Computer Modelling Vol. 57, no. 3-4 (2013), p. 873-886
- Relation: http://purl.org/au-research/grants/arc/LP0990908
- Full Text: false
- Reviewed:
- Description: The operation of a water distribution system is a complex task which involves scheduling of pumps, regulating water levels of storages, and providing satisfactory water quality to customers at required flow and pressure. Pump scheduling is one of the most important tasks of the operation of a water distribution system as it represents the major part of its operating costs. In this paper, a novel approach for modeling of explicit pump scheduling to minimize energy consumption by pumps is introduced which uses the pump start/end run times as continuous variables, and binary integer variables to describe the pump status at the beginning of the scheduling period. This is different from other approaches where binary integer variables for each hour are typically used, which is considered very impractical from an operational perspective. The problem is formulated as a mixed integer nonlinear programming problem, and a new algorithm is developed for its solution. This algorithm is based on the combination of the grid search with the Hooke-Jeeves pattern search method. The performance of the algorithm is evaluated using literature test problems applying the hydraulic simulation model EPANet. © 2012 Elsevier Ltd.
- Description: 2003010583
An application of novel clustering technique for information security
- Authors: Beliakov, Gleb , Yearwood, John , Kelarev, Andrei
- Date: 2011
- Type: Text , Conference paper
- Relation: Applications and Techniques in Information Security Workshop p. 5-11
- Full Text: false
- Reviewed:
- Description: This article presents experimental results devoted to a new application of the novel clustering technique introduced by the authors recently. Our aim is to facilitate the application of robust and stable consensus functions in information security, where it is often necessary to process large data sets and monitor outcomes in real time, as it is required, for example, for intrusion detection. Here we concentrate on the particular case of application to profiling of phishing websites. First, we apply several independent clustering algorithms to a randomized sample of data to obtain independent initial clusterings. Silhouette index is used to determine the number of clusters. Second, we use a consensus function to combine these independent clusterings into one consensus clustering . Feature ranking is used to select a subset of features for the consensus function. Third, we train fast supervised classification algorithms on the resulting consensus clustering in order to enable them to process the whole large data set as well as new data. The precision and recall of classifiers at the final stage of this scheme are critical for effectiveness of the whole procedure. We investigated various combinations of three consensus functions, Cluster-Based Graph Formulation (CBGF), Hybrid Bipartite Graph Formulation (HBGF), and Instance-Based Graph Formulation (IBGF) and a variety of supervised classification algorithms. The best precision and recall have been obtained by the combination of the HBGF consensus function and the SMO classifier with the polynomial kernel.
- Description: 2003009195
Does the Delphi process lead to increased accuracy in group-based judgmental forecasts or does it simply induce consensus amongst judgmental forecasters?
- Authors: Bolger, Fergus , Stranieri, Andrew , Wright, George , Yearwood, John
- Date: 2011
- Type: Text , Journal article
- Relation: Technological Forecasting and Social Change Vol. , no. (2011), p.
- Full Text: false
- Reviewed:
- Description: We investigate the relative impact of internal Delphi process factors - including panelists' degree of confidence, expertise, majority/minority positioning - and an external factor, richness of feedback - on opinion change and subsequent accuracy of judgmental forecasts. We found that panelists who had low confidence in their judgmental forecast and/or who were in a minority were more likely to change their opinion than those who were more confident and/or in a majority. The addition of rationales, or reasons, to the numeric feedback had little impact upon panelists' final forecasts, despite the quality of panelists' rationales being significantly positively correlated with accurate forecasts and thus of potential use to aid forecast improvement over Delphi rounds. Rather, the effect of rationales was similar to that of confidence: to pull panelists towards the majority opinion regardless of its correctness. We conclude that majority opinion is the strongest influence on panelists' opinion change in both the 'standard' Delphi, and Delphi-with-reasons. We make some suggestions for improved variants of the Delphi-with-reasons technique that should help reduce majority influence and thereby permit reasoned arguments to exert their proper pull on opinion change, resulting in forecast accuracy improvements over Delphi rounds. © 2011.
Online group deliberation for the elicitation of shared values to underpin decision making
- Authors: Feldman, Yishai , Kraft, Donald , Kuflik, Tsvi , Afshar, Faezeh , Stranieri, Andrew , Yearwood, John
- Date: 2009
- Type: Text , Conference paper
- Relation: Paper presented at 7th International Conference, NGITS 2009, Next generation information technologies and systems, Haifa, Israel : 16th-18th June 2009 Vol. 5831, p. 158-168
- Full Text: false
- Description: Values have been shown to underpin our attitudes, behaviour and motivate our decisions. Values do not exist in isolation but have meaning in relation to other values. However, values are not solely the purview of individuals as communities and organisations have core values implicit in their culture, policies and practices. Values for a group can be determined by a minority in power, derived by algorithmically merging values each group member holds, or set by deliberative consensus. The elicitation of values for the group by deliberation is likely to lead to widespread acceptance of values arrived at, however enticing individuals to engage in face to face discussion about values has been found to be very difficult. We present an online deliberative communication approach for the anonymous deliberation of values and claim that the framework has the elements required for the elicitation of shared values.
- Description: 2003007509
Designing a decision module for modular artificial neural networks
- Authors: Ferguson, Brent , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the ICOTA6: 6th International Conference on Optimization - Techniques and Applications, Ballarat, Victoria : 9th December, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000854
Task decomposition for the problem of alphabetic character recognition
- Authors: Ferguson, Brent , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at RASC 2004: Fifth International Conference on Recent Advances in Soft Computing, Nottingham, United Kingdom : 16th December, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000855
Modular neural network design for the problem of alphabetic character recognition
- Authors: Ferguson, Brent , Ghosh, Ranadhir , Yearwood, John
- Date: 2005
- Type: Text , Journal article
- Relation: International Journal of Pattern Recognition and Artificial Intelligence Vol. 19, no. 2 (Mar 2005), p. 249-269
- Full Text: false
- Reviewed:
- Description: This paper reports on an experimental approach to nd a modularized articial neural network solution for the UCI letters recognition problem. Our experiments have been carried out in two parts. We investigate directed task decomposition using expert knowledge and clustering approaches to nd the subtasks for the modules of the network. We next investigate processes to combine the modules e ectively in a single decision process. After having found suitable modules through task decomposition we have found through further experimentation that when the modules are combined with decision tree supervision, their functional error is reduced signicantly to improve their combination through the decision process that has been implemented as a small multilayered perceptron. The experiments conclude with a modularized neural network design for this classication problem that has increased learning and generalization characteristics. The test results for this network are markedly better than a single or stand alone network that has a fully connected topology.
- Description: C1
- Description: 2003001355
A rule based plagiarism detection using decision tree
- Authors: Ghosh, Moumita , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at the CIMCA 2004: International Conference on Computational Intelligence for Modelling, Control and Automation, Gold Coast, Queensland : 12th July, 2004
- Full Text: false
- Reviewed:
- Description: E1
- Description: 2003000858
An evolutionary neural learning algorithm for offline cursive handwriting words with hamming network lexicon
- Authors: Ghosh, Moumita , Ghosh, Ranadhir , Yearwood, John
- Date: 2004
- Type: Text , Conference paper
- Relation: Paper presented at Seventeenth International Florida Artificial Intelligence Research Symposium Conference, FLAIRS 2004, Miami Beach, USA : 15th May, 2004
- Full Text: false
- Reviewed:
- Description: In this paper we incorporate a hybrid evolutionary method, which uses a combination of genetic algorithm and matrix based solution method such as QR factorization. A heuristic segmentation algorithm is initially used to over segment each word. Then the segmentation points are passed through the rule-based module to discard the incorrect segmentation points and include any missing segmentation points. Following the segmentation the connected contour is extracted between two correct segmentation points. The contour is passed through the feature extraction module that extracts the angular features of the contour, after which the EALS-BT algorithm finds the architecture and the weights for the classifier network. These recognized characters are grouped into words and passed to a variable length lexicon that retrieves words that has highest confidence value. Hamming neural network is used as a lexicon that rectifies the word misrecognized by the classifier. We have used CEDAR benchmark dataset and UCI Machine Learning repository (Upper case) to test the train and test the system
- Description: E1
- Description: 2003000865