TY  - JOUR
T1  - Optimal Rural Clinic Location Determination using Scientific Modelling
AU - Alex Dandadzi, Tichavasia AU - Masilela, Jabulile AU - Mathiba, Ntsoka AU - Mafike, Senate AU - Violet Ndobe, Tsakani AU - Hungwe, Taurai 
JO  - Journal of Engineering and Applied Sciences
VL  - 15
IS  - 21
SP  - 3574
EP  - 3580
PY  - 2020
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2020.3574.3580
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2020.3574.3580
KW  - Rural clinic location
KW  -statistical probability of misclassfication
KW  -artificial intelligence
KW  -technology innovation
KW  -optimal scientific modelling
KW  -decision making
AB  - Rural communities are to a larger extent
marginalised resulting in huge populations migrating to
urban areas. This study looked at the poor rural people of
Vezubuhle with their struggle of poor healthcare facilities.
The region has three sections with two clinics situated in
sections with the least population. How that decision on
the two clinics was reached has no scientific basis as
section with the largest population has none. A mixed
research method was followed and scientific modelling
based on statistical and artificial intelligence methods
used. This resulted in an innovative software solution
developed giving optimal results free of bias, corruption,
or favouritism that can be adopted to any other
environment (s) with easy. Authorities in position of
power are therefore, advised to embrace use of
technology, not only does it bring about efficiency, it can
be a huge driving force in attracting investments for the
development of rural areas. There must also be
community involvement if any project affecting its
livelihoodis to be a success.
ER  -