Title :
Green House Demand Forecasting Model Based on Markov Chains
Author :
Xiaojian, Guo ; Rong, Liu
Author_Institution :
Sch. of Econ. & Manage., Jiangxi Univ. of Sci. & Technol., Ganzhou, China
Abstract :
Deeply influenced by the concept of sustainable development, people begin to pay more and more attention to the problems of resource drain and environment pollution on the earth on which they live. As a result, green revolutions are booming all over the world and building green house actively is the inevitable choice for real estate industry to take the path of sustainable development. Based on the theory of Markov Chains, this paper sets up a green house demand forecasting model, by which the demand for green house is forecasted and decision making basis on housing product development for Real Estate Development Enterprise is provided.
Keywords :
Markov processes; building societies; decision making; demand forecasting; greenhouses; sustainable development; Markov chain; decision making; demand forecasting; environment pollution; green house; green revolution; housing product development; real estate development enterprise; sustainable development; Architecture; Biological system modeling; Demand forecasting; Economic forecasting; Environmental economics; Humans; Pollution; Power generation economics; Predictive models; Sustainable development; Markov Chains; demand forecast; green house; sustainable development;
Conference_Titel :
Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-7279-6
Electronic_ISBN :
978-1-4244-7280-2
DOI :
10.1109/ICICTA.2010.58
