Time-series prediction of shellfish farm closure: A comparison of alternatives
作者机构:Autonomous Systems ProgramCSIRO Computational InformaticsHobartTAS 7000Australia
出 版 物:《Information Processing in Agriculture》 (农业信息处理(英文))
年 卷 期:2014年第1卷第1期
页 面:42-50页
核心收录:
学科分类:0907[农学-林学] 0908[农学-水产] 07[理学] 070101[理学-基础数学] 0710[理学-生物学] 0830[工学-环境科学与工程(可授工学、理学、农学学位)] 0707[理学-海洋科学] 0905[农学-畜牧学] 0906[农学-兽医学] 0829[工学-林业工程] 0901[农学-作物学] 0701[理学-数学] 0812[工学-计算机科学与技术(可授工学、理学学位)]
主 题:Aquaculture Shellfish farm closure Data mining Time series data
摘 要:Shellfish farms are closed for harvest when microbial pollutants are *** pollutants are typically present in rainfall runoff from various land uses in *** currently use a number of observable parameters(river flow,rainfall,salinity)as proxies to determine when to close *** have proposed using the short term historical rainfall data as a time-series prediction problem where we aim to predict the closure of shellfish farms based only on ***-series event prediction consists of two steps:(i)feature extraction,and(ii)prediction.A number of data mining challenges exist for these scenarios:(i)which feature extraction method best captures the rainfall pattern over successive days that leads to opening or closure of the farms?,(ii)The farm closure events occur infrequently and this leads to a class imbalance problem;the question is what is the best way to deal with this problem?In this paper we have analysed and compared different combinations of balancing methods(under-sampling and over-sampling),feature extraction methods(cluster profile,curve fitting,Fourier Transform,Piecewise Aggregate Approximation,and Wavelet Transform)and learning algorithms(neural network,support vector machine,k-nearest neighbour,decision tree,and Bayesian Network)to predict closure events accurately considering the above data mining *** have identified the best combination of techniques to accurately predict shellfish farm closure from rainfall,given the above data mining challenges.