Track: Artificial Intelligence

Abstract

Regional development can be defined as the development of a region or a province in terms of socio-economic indicators. Socio-economic development as indicated by differences between countries in the same country varies in different regions and provinces. Development cannot be balanced according to the delivery of natural and communal resources which are not already equal.

Also, it is important to know socio-economical inequality of development gap between cities from the point of which plans of policy maker and making investment decision of which aims to provide services throughout the country such as retailing, banking etc.

The socio-economic inequality index of development affects the plans of policy makers, investment decisions and services throughout the country such as retailing and banking sectors. Thus, to know the gap between regions or cities becomes a more crucial fact for governments.

For this purpose, different institutions such as TUIK (Turkish Statistical Institute), DPT (State Planning Organization) and banks conduct and publish annual socio-economic development indexes for cities in Turkey. This study aims to provide a projection related to socio-economical situation of Turkey and development level of each city in terms of socio-economic development in future. In this context, various classification methods as Artificial Neural Network-ANN, Bayes Network and Support Vector Machine-SVM algorithm are used on WEKA which is a collection of machine learning algorithms for data mining tools. Besides, K-Means method, a clustering technique, is utilized to provide insight about progressed areas in Turkey.