Neural network integration of field observations for soil endocrine disruptor characterisation.

Research output: Contribution to journal › Article › peer-review

Original language	English
Pages (from-to)	240-248
Journal	Science of the Total Environment
Volume	468-469
DOIs	https://doi.org/10.1016/j.scitotenv.2013.08.007
Publication status	Published - 15 Jan 2014

Keywords

@article{39d01475563b4100b11622373f1d667d,

title = "Neural network integration of field observations for soil endocrine disruptor characterisation.",

keywords = "Board Nov 2013, Endocrine disrupting compounds, National Soils Inventory of Scotland, Neural networks, Sample analysis",

author = "M.J. Aitkenhead and S.M. Rhind and Z.L. Zhang and C.E. Kyle and M.C. Coull",

year = "2014",

month = jan,

day = "15",

doi = "10.1016/j.scitotenv.2013.08.007",

language = "English",

volume = "468-469",

pages = "240--248",

journal = "Science of the Total Environment",

}

TY - JOUR

T1 - Neural network integration of field observations for soil endocrine disruptor characterisation.

AU - Aitkenhead, M.J.

AU - Rhind, S.M.

AU - Zhang, Z.L.

AU - Kyle, C.E.

AU - Coull, M.C.

PY - 2014/1/15

Y1 - 2014/1/15

KW - Board Nov 2013

KW - Endocrine disrupting compounds

KW - National Soils Inventory of Scotland

KW - Neural networks

KW - Sample analysis

U2 - 10.1016/j.scitotenv.2013.08.007

DO - 10.1016/j.scitotenv.2013.08.007

M3 - Article

VL - 468-469

SP - 240

EP - 248

JO - Science of the Total Environment

JF - Science of the Total Environment

ER -