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Applying Data Mining Techniques In The Selection Of Plant Traits, Dean Diepeveen, Leisa Armstrong
Applying Data Mining Techniques In The Selection Of Plant Traits, Dean Diepeveen, Leisa Armstrong
Leisa Armstrong
In the agricultural sector, farmers are provided with crop related information by various research agencies in order to make critical decisions about which is the most profitable crop variety choice. Research agencies provide information which is generic, rather than being tailored to the individual farmers cropping situation. A number of specific plant and growth traits are used to establish the most suitable crop varieties. When selecting crop varieties for release to growers, the application of data mining techniques to crop research data enables the customization of information to each individual farmers farming situation. The challenge for agricultural research perspective is …
A Wrapper-Based Feature Selection For Analysis Of Large Data Sets, Jinsong Leng, Craig Valli, Leisa Armstrong
A Wrapper-Based Feature Selection For Analysis Of Large Data Sets, Jinsong Leng, Craig Valli, Leisa Armstrong
Leisa Armstrong
Knowledge discovery from large data sets using classic data mining techniques has been proved to be difficult due to large size in both dimension and samples. In real applications, data sets often consist of many noisy, redundant, and irrelevant features, resulting in degrading the classification accuracy and increasing the complexity exponentially. Due to the inherent nature, the analysis of the quality of data sets is difficult and very limited approaches about this issue can be found in the literature. This paper presents a novel method to investigate the quality and structure of data sets, i.e., how to analyze whether there …
Application Of A Data Mining Framework For The Identification Of Agricultural Production Areas In Wa , Yunous Vagh, Leisa Armstrong, Dean Diepeveen
Application Of A Data Mining Framework For The Identification Of Agricultural Production Areas In Wa , Yunous Vagh, Leisa Armstrong, Dean Diepeveen
Leisa Armstrong
This paper will propose a data mining framework for the identification of agricultural production areas ill WA. The data mining (DM) framework was developed with the aim of enhancing the analysis of agricultural datasets compared to currently used statistical methods. The DM framework is a synthesis of different technologies brought together for the purpose of enhancing the interrogation of these datasets. The DM framework is based on the data, information, knowledge and wisdom continuum as a horizontal axis, with DM and online analytical processing (OLAP) forming the vertical axis. In addition the DM framework incorporates aspects of data warehousing phases, …
The Application Of Data Mining Techniques To Characterize Agricultural Soil Profiles, Leisa Armstrong, D Diepeveen, R Maddern
The Application Of Data Mining Techniques To Characterize Agricultural Soil Profiles, Leisa Armstrong, D Diepeveen, R Maddern
Leisa Armstrong
The advances in computing and information storage have provided vast amounts of data. The challenge has been to extract knowledge from this raw data; this has lead to new methods and techniques such as data mining that can bridge the knowledge gap. This research aimed to assess these new data mining techniques and apply them to a soil science database to establish if meaningful relationships can be found. A large data set extracted from the WA Department of Agriculture and Food (AGRIC) soils database has been used to conduct this research. The database contains measurements of soil profile data from …
An Evaluation Of Methodologies For Eagriculture In An Australian Context, Leisa Armstrong, Dean Diepeveen
An Evaluation Of Methodologies For Eagriculture In An Australian Context, Leisa Armstrong, Dean Diepeveen
Leisa Armstrong
Australian agricultural producers’ profits are dependent on the decisions they make about farm productivity systems. They may use recommendations and information provided by government agencies and private consultants. For cereal growers, success is dependent on decisions made about selection of crop varieties suitable for their agronomic and climatic conditions. This paper reports on research which aimed to evaluate some current eAgriculture methodologies for their application in the Western Australian agricultural industry. In particular the paper illustrates the findings from a project which aimed to explain the variability seen in crop varieties grown in Western Australia. The problems associated with crop …
Introducing A New Technology To Enhance Community Sustainability: An Investigation Of The Possibilities Of Sun Spots, Suppachart Tantisureeporn, Leisa Armstrong
Introducing A New Technology To Enhance Community Sustainability: An Investigation Of The Possibilities Of Sun Spots, Suppachart Tantisureeporn, Leisa Armstrong
Leisa Armstrong
The introduction of the Sun SPOT, Small Programmable Object Technology, developed by Sun Microsystems has been depicted as providing a revolutionary change in cyber physical interaction. Based on Sun Java Micro Edition (ME), this sensor technology has the potential to be used across a number of discipline areas to interface with systems, the environment and biological domains. This paper will outline the potential of Sun SPOTs to enhance community sustainability. An action based research project was carried out to investigate the potential uses of these technologies and develop a prototype system as a proof of concept. The research will compare …
Selecting Areas For Land Use Change In A Catchment, Neil Dunstan, Leisa Armstrong, Dean A. Diepeveen
Selecting Areas For Land Use Change In A Catchment, Neil Dunstan, Leisa Armstrong, Dean A. Diepeveen
Leisa Armstrong
Some farming areas in Australia have been degraded by agricultural practices that result in rises in the water table that bring salt to the surface and reduce the quality of runoff water and the yield from pasture and crops. There is a need for a balanced choice of land uses that can reduce the salinity problem. A framework is proposed that uses catchment data and a hydrology model to predict areas with high rates of recharge and to identify sites for land use change.
An Information-Based Decision Support Framework For Eagriculture, Leisa Armstrong, Dean Diepeveen
An Information-Based Decision Support Framework For Eagriculture, Leisa Armstrong, Dean Diepeveen
Leisa Armstrong
The ability of farmers to acquire knowledge to make decisions is limited by the information quality and applicability. An inconsistency in information delivery and standards for the integration of information also limits the decision making process. Knowledge Discovery in Databases (KDD) methodology described for the data mining is an example of how frameworks can be used to facilitate such data integration. This research will examine how such a ICT based framework can be used to facilitate the acquisition of knowledge for the farmer decision making process. The Farmer Knowledge and Decision Support Framework (FKDSF) takes information provided to farmers and …