Earticle

초록

영어

This paper attempts to build an artificial neural network that can estimate the median price of a home in a neighborhood described by forty demographic attributes in areas of Dhaka City namely Dhanmondi, Baridhara, Gulshan, Mirpur, Uttara and Old Dhaka. A structured questionnaire was used to collect the relevant data and the housing data sets was used to develop constant quality price indices using traditional econometric techniques and using neural networks incorporating genetic algorithms. Factors including house size, house age, house type, number of bedrooms, number of bathrooms, number of garages, amenities around the house and geographical location are considered. The analysis indicates that neural networks act as real alternative to the econometric methods. In this paper thirteen conditional attributes have been considered to estimate the house rent. This paper provides some indicative policy guidelines to handle the house rent problem in the Dhaka City and suggests that a rent controller should be appointed for each ward and maximum rents for particular areas should be gazette and the rents should be paid through banks.

목차

Abstract
 1. Introduction
 2. Background Study
 3. Literature Review
 4. Proposed Methodology
 5. Experiment and Results
 6. Discussion and Limitations
 7. Conclusion
 References

키워드

저자

• Samsuddin Ahmed [ Dept. of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh ]
• Md.Mahbubur Rahman [ Dept. of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh ]
• Sabirah Islam [ Dept. of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of u- and e- Service, Science and Technology

• 간기

  격월간

• pISSN

  2005-4246

• 수록기간

  2008~2016

• 십진분류

  KDC 505 DDC 605