TY  - JOUR
T1  - Hybrid Neural Network: A Computational Intelligent Model for Solid Waste Landfilling Suitability Mapping
AU - Abujayyab, Sohaib K.M. AU - Omar, Najat Qader AU - Aziz, Hamidi Abdul AU - Ahamad, Mohd Sanusi S. AU - Yahya, Ahmad Shukri AU - Alkhasawneh, Mutasem Sh. AU - Ahmad, Siti Zubaidah 
JO  - Journal of Engineering and Applied Sciences
VL  - 12
IS  - 11
SP  - 2788
EP  - 2794
PY  - 2017
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2017.2788.2794
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2017.2788.2794
KW  - Computational intelligent modelling
KW  -artificial neural networks
KW  -solid waste landfil suitability mapping
KW  -performance exposed
KW  -GIS
AB  - This research introduce hybrid network (HRCFNN) for solid waste landfilling suitability mapping. It is a grouping between the recurrent neural network and cascade forward neural network. The optimum structure chosen search via several use cases. Moreover, the accomplished performance exposed that the HRCFNN has no overfitting problem. The suitability index map produced using final structure of the trained HRCFNN. The last outcomes of HRCFNN prove its robustness and the applicability of it for further application in the long-term plan developments of solid waste landfill sites.
ER  -