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Mendeley readers
Attention Score in Context
| Title |
Artificial Neural Network Modeling of the Water Quality Index Using Land Use Areas as Predictors
|
|---|---|
| Published in |
Water Environment Research (10614303), February 2015
|
| DOI | 10.2175/106143014x14062131179276 |
| Pubmed ID | |
| Authors |
Nabeel M. Gazzaz, Mohd Kamil Yusoff, Mohammad Firuz Ramli, Hafizan Juahir, Ahmad Zaharin Aris |
| Abstract |
This paper describes the design of an artificial neural network (ANN) model to predict the water quality index (WQI) using land use areas as predictors. Ten-year records of land use statistics and water quality data for Kinta River (Malaysia) were employed in the modeling process. The most accurate WQI predictions were obtained with the network architecture 7-23-1; the back propagation training algorithm; and a learning rate of 0.02. The WQI forecasts of this model had significant (p < 0.01), positive, very high correlation (ρs = 0.882) with the measured WQI values. Sensitivity analysis revealed that the relative importance of the land use classes to WQI predictions followed the order: mining > rubber > forest > logging > urban areas > agriculture > oil palm. These findings show that the ANNs are highly reliable means of relating water quality to land use, thus integrating land use development with river water quality management. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Science communicators (journalists, bloggers, editors) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 75 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 1% |
| Unknown | 74 | 99% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 14 | 19% |
| Student > Ph. D. Student | 12 | 16% |
| Researcher | 5 | 7% |
| Student > Doctoral Student | 4 | 5% |
| Student > Bachelor | 4 | 5% |
| Other | 14 | 19% |
| Unknown | 22 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 19 | 25% |
| Computer Science | 6 | 8% |
| Agricultural and Biological Sciences | 5 | 7% |
| Environmental Science | 4 | 5% |
| Social Sciences | 2 | 3% |
| Other | 9 | 12% |
| Unknown | 30 | 40% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 March 2015.
All research outputs
#20,660,571
of 25,382,440 outputs
Outputs from Water Environment Research (10614303)
#941
of 1,487 outputs
Outputs of similar age
#269,135
of 361,196 outputs
Outputs of similar age from Water Environment Research (10614303)
#9
of 21 outputs
Altmetric has tracked 25,382,440 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,487 research outputs from this source. They receive a mean Attention Score of 2.0. This one is in the 21st percentile – i.e., 21% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 361,196 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 21 others from the same source and published within six weeks on either side of this one. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.