| 000 | 03361ntm a2200289 a 4500 | ||
|---|---|---|---|
| 001 | vtls000092313 | ||
| 003 | KUKTEM | ||
| 005 | 20251117113300.0 | ||
| 008 | 151130t2015 my da f abm 000 0 eng d | ||
| 020 | _aTHE0000574(Local) | ||
| 039 | 9 |
_a201905160932 _bnazirah _c201711301230 _dfateeha _c201512011420 _dasma _y201511301433 _zasma |
|
| 040 | _aUMP | ||
| 090 | _aFKASA .M87 2015 r Bc. | ||
| 100 | 0 | _aNurul Murshida Mohd Sabri | |
| 245 | 1 | 0 |
_aDevelopment of forecasting in Sungai Muda, Kuala Muda, Kedah by utilizing artificial neural network (ANN) / _cNurul Murshida Mohd Sabri |
| 260 |
_aKuantan, Pahang : _bUMP, _c2015 |
||
| 300 |
_axiv, 57 p. : _bill. (some col.) ; _c30 cm. + _e1 CD ROM |
||
| 500 | _aFaculty of Civil Engineering and Earth Resources | ||
| 502 | _aProject Paper (Bachelors of Civil Engineering) -- Universiti Malaysia Pahang – 2015 | ||
| 504 | _aBibliography : p. 57 | ||
| 520 | 3 | _aThis report deals with flood problem which is usually happened in Malaysia when it coincides with monsoon and gave harm and damages to human life, as it had took many lives each time it happens. A case study of flood is going to be conduct to analyze the pattern of water level and to determine other causes that contributes to the flood. The main aim of the study is to minimize the effect of flood problems. It is also used to develop high accuracy model utilizing Artificial Neural Network (ANN) in predicting flood. Furthermore, it used to forecast flood occasion in the study area of station number of 5606410 of Sungai Muda (Jambatan Syed Omar) which is the main river that supplies water to Kedah and Penang. Besides, it used to investigate whether water level data alone can be used to produce modelling and to determine whether ANN is functioning in the forecasting. In this case study, a computational model will be used to stimulate the input data and generate the result, which is called Artificial Neural Network. ANN, which are modelled on the operating behaviour of the brain, are tolerant of some imprecision and are especially useful for classification and function approximation or mapping problems, to which hard and fast rules cannot be applied easily. The terminology of artificial neural networks has created form an organic biological model of neural system, which it comprises an asset of joined cells, the neurons. The neurons receive impulses or response from either input cells or any other neurons. It will perform some kind of transformation of the input and then, it will transfer the outcome to other neurons or also known as output cells. The neural networks are developed from many layers of connected neurons. The result showed that input 7+1 had the highest NSC value of 0.979 with RMSE value of 288.332 for 6 hour interval time, while input 6+1 had the highest NSC value of 0.977 with RMSE value of 134.801 for 3 hour interval time. In conclusion, this research contributes toward the development of forecasting using Artificial Neural Network for flood problems | |
| 610 | 2 | 0 |
_aFaculty of Civil Engineering and Earth Resources _xDissertations |
| 650 | 0 |
_aUniversities and Colleges _xDissertations |
|
| 650 | 0 | _aTheses | |
| 856 | 4 | 0 |
_uhttp://ecollib.ump.edu.my/id/eprint/25922 _zAccess in library only |
| 999 |
_aVIRTUA40 _c6054 _d6060 |
||
| 999 | _aVTLSSORT0080*0200*0400*0900*1000*2450*2600*3000*5000*5020*5040*5200*6100*6500*6501*8560*9992 | ||