A Time Series Based Prediction Model For
Urban Development Plans Using An Artificial
Neural Network: Koya In 2020
Author(s)
S. M. Abdullah
Abstract
Urban development plans always designed based on two important factors;
population growth and city’s expansion. In many cases, the size of expansion of
a city depends on the rate of population growth. The expansion process for a city
may include many types of projects, such as building new residential and
commercial areas, opening internal and access roads, constructing new service
buildings (schools, hospitals, etc.) with providing many types of services such as
electricity power, communication access points and towers, and sewerage with
water net systems. In this project, an accurate prediction model with prediction
function is proposed. The model depends on a time series based Artificial Neural
Network to achieve the work. The input data for this model will be the number
of families, number of students, and number of registered cars to get fuel in
Koya petrol stations. These records that are distributed over different spans of
years (from 2000 to 2013) were collected in Koya city. This work has general
and specific aims. The specific aim of this work is to support some governmental
service departments in Koya through providing a correct prediction about the
size of requirements for this city in 2020. This case could be generalized to other
cities similar to Koya, which is the general aim of this work.
Keywords
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