TY  - CONF
UR  - https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867905924&doi=10.1109%2fICCISci.2012.6297303&partnerID=40&md5=5958889d2263409a7b189748e161ef64
A1  - Shah, H.
A1  - Jaafar, J.
A1  - Ibrahim, R.
A1  - Saima, H.
A1  - Maymunah, H.
VL  - 1
EP  - 537
Y1  - 2012///
SN  - 9781467319386
N2  - The weather prediction has gained much attention around the world due to climate changes. It includes the temperature, wind, fog, humidity, and rainfall. In this study, only rainfall prediction is considered because it plays a vital role in planning and reforming the agricultural structures and in managing the storm water, runoff and pollution control systems. It is found that there is uncertainty in data (e.g. inconsistent, incomplete, human error, missing values, and device error in data) obtained through heterogeneous devices. It leads to uncertain rainfall prediction which adversely affects human life, time, and economy. To overcome these issues, different techniques are proposed by researchers for accurate rainfall prediction. However, there is still a need to reduce the uncertainty from the obtained data and manage it properly for accomplishing the accurate rainfall prediction. In this respect, a hybrid approach will be adopted by considering Possibilitic fuzzy C-mean and Interval type-2 Fuzzy logic methods to address problem of uncertainty in data. The outcome of this study may enrich the rainfall prediction accuracy. © 2012 IEEE.
N1  - cited By 3; Conference of 2012 International Conference on Computer and Information Science, ICCIS 2012 - A Conference of World Engineering, Science and Technology Congress, ESTCON 2012 ; Conference Date: 12 June 2012 Through 14 June 2012; Conference Code:93334
KW  - Fuzzy C mean; Heterogeneous devices; Human errors; Human lives; Hybrid approach; Missing values; Possibilistic; Rainfall prediction; Stormwaters; Type-2 fuzzy logic; Type-2 fuzzy logic system; Uncertainty; Weather prediction
KW  -  Agricultural runoff; Climate change; Fuzzy logic; Hybrid systems; Information science; Rain; Technology; Water pollution
KW  -  Forecasting
SP  - 532
ID  - scholars2816
TI  - A hybrid system using Possibilistic fuzzy C-mean and interval type-2 Fuzzy logic for forecasting: A review
CY  - Kuala Lumpur
AV  - none
ER  -