Ecological data prediction and visualization system

Figures & data

Figure 1. Map of Putrajaya Lake and Wetlands, showing water quality sampling stations (Malek et al. 2009).

Table 1. Mean limnological properties of Putrajaya Wetlands based on data collected from 2001 to 2006.

Parameter	Minimum value	Maximum value	Mean	Standard deviation
Rainfall (mm)	0.0	71.8	0.4	13.63488
Wind speed (m/s)	0.23	1.73	0.7	0.23655
Sunshine (h)	0.00	11.20	6.29	2.559912
Temperature (°C)	25.77	35.28	30.22	1.766512
pH	4.26	8.61	7.14	0.515269
Dissolved oxygen (mg/l)	3.27	8.50	6.43	0.996298
Secchi depth (m)	0.05	2.00	0.60	0.303146
Turbidity (NTU)	0.00	527.00	35.24	44.984791
Conductivity (μS/cm)	37	228	98.54	40.375525
Total PO4 (mg/l)	0.00	1.13	0.04	0.112034
NH3-N (mg/l)	0.00	2.63	0.14	0.326953
NO3-N (mg/l)	0.00	5.17	1.42	1.114293
Total Chlorophyta (cells/ml)	1	510	37	50.871022

Figure 2. Prediction module flowchart. HEA = hybrid evolutionary algorithm.

Figure 3. Visualization module flowchart.

Figure 4. Graphical user interface of the system.

Figure 5. Example of visualization interface.

Figure 6. Scenario of integrating rule sets generated from the hybrid evolutionary algorithm into a thematic map after uploading the map profile.

Figure 7. Dialogue box when the Options menu is selected on the main toolbar.

Figure 8. Select output variable.

Table 2. Results of rule sets and accuracy generated using the hybrid evolutionary algorithm.

	Rule sets
Putrajaya Wetlands	Condition statement (IF)	(THEN)	(ELSE)	Accuracy (%)
Central Wetlands (CW)	((((Sunshine*Sunshine)> =79.010)AND(Cond> =52.825))AND ((DO*DO)> =49.065))	Tchlorophyta= (exp(NO3N)*50.846)	Tchlorophyta= (((NO3N/exp(NO3N)) *45.347)− (((NO3N*(−10.179))/(149.747-Cond))*51.734))	91.14
Lower East Wetlands (LE)	(((158.687/Rainfall) >90.737)OR(((Cond+ Sunshine)> =74.965)OR((Cond> 16.596)AND(Rainfall >10.321))))	Tchlorophyta=(NH3N+ (Temp+(−1.215)))	Tchlorophyta=((((Turb +234.147) +(−1.610)) +(−1.610)) +(−1.304))	93.59
Upper Bisa Wetlands (UB)	((Turb*428.965)> 428.965)	Tchlorophyta=((85.916/ ((41.978/NO3N)-Cond))+28.769)	Tchlorophyta= 226.054	96.55
Upper East Wetlands (UE)	((Sunshine<=9.583) AND((Rainfall> =8.487)OR(Rainfall< =6.549)))	Tchlorophyta= (exp(exp(Windspeed)) +(exp(exp(Windspeed)) +23.026))	Tchlorophyta= (Turb+236.425)	96.97
Upper North Wetlands (UN)	(((exp(NO3N)/TPO4) >19.590)OR((Sunshine/ TPO4)<=86.085))	Tchlorophyta= ((ln(|ln(|Turb|)|)+ 5.129)+(Cond/(exp(pH)/ (Cond-(-144.302)))))	Tchlorophyta= (((32.515/NO3N)+ 121.739)+Turb)	84.96
Upper West Wetlands (UW)	((((Cond+NH3N)+ NH3N)+(Cond+ NH3N))<97.474)	Tchlorophyta=(((pH/ (Sunshine-Rainfall))+23.026)+ ((Sunshine*pH)/ exp(Cond)))	Tchlorophyta=(Rainfall+ (((Sunshine*pH)/ (Cond +(-80.792))) +23.212))	95.12

Figure 9. (a) Putrajaya Wetlands; (b) thematic map of Putrajaya Wetlands.

Figure 10. Visualization of Chlorophyta abundance over time.

Malek S, Salleh A, Baba MS. 2009. Prediction of population dynamics of Bacillariophyta in the tropical Putrajaya lake and wetlands (Malaysia) by a recurrent artificial neural networks. Second International Conference on Environmental and Computer Science. IEEE. p. 407–410.

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