Applied-Information Technology with Using Bayesian Belief Network for Strategy Selection of Developing Mountainous Areas

Abstract:

strategy selection of developing mountainous areas is an important topic in recent years, usually we believe the financial support is the most relevant factor to the development, under the condition of lack of enough money, we should first choose the best strategy which is an optimal choice for the development of economy. In this paper, we proposed to use the Bayesian belief network for the strategy selection. The optimal selection can be treated as an important guidance to consider the development of local economy.

• Periodical: Advanced Materials Research (Volume 910)
• Pages: 429-432
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.910.429
• Online since: March 2014
• Authors: Jie Zhu*
• Keywords: Applied-Information Technology, Bayesian Belief Network, Development of Mountainous Areas, Optimal Selection, Relevance, Strategy Selection

References

[1] Harden C P. Soil erosion and sustainable mountain development: experiments, observations, and recommendations from the Ecuadorian Andes[J]. Mountain Research and Development, 2001, 21(1): 77-83.

DOI: 10.1659/0276-4741(2001)021[0077:seasmd]2.0.co;2

[2] Harden C P. Soil erosion and sustainable mountain development: experiments, observations, and recommendations from the Ecuadorian Andes[J]. Mountain Research and Development, 2001, 21(1): 77-83.

DOI: 10.1659/0276-4741(2001)021[0077:seasmd]2.0.co;2

[3] Dax T. Endogenous development in Austria's mountain regions: From a source of irritation to a mainstream movement[J]. Mountain research and development, 2001, 21(3): 231-235.

DOI: 10.1659/0276-4741(2001)021[0231:ediamr]2.0.co;2

[4] Godde, Pamela M., Martin F. Price, and F. Friedrich M. Zimmerman, eds. Tourism and development in mountain regions [electronic resource]. CABI, (2000).

[5] Dax T. Research on mountain development in Europe, Overview of issues and priorities[C]/Innovative Structures for the Sustainable Development of Mountainous Areas, Proceedings of the ISDEMA Conference in Thessaloniki, Greece. 2002, 2: 66-76.

[6] Zheng, Du, Qingsong Zhang, and Wu Shaohong Wu, eds. Mountain geoecology and sustainable development of the Tibetan Plateau. Vol. 57. Springer, (2000).

[7] Kisioglu P, Topcu Y I. Applying Bayesian Belief Network approach to customer churn analysis: A case study on the telecom industry of Turkey[J]. Expert Systems with Applications, 2011, 38(6): 7151-7157.

DOI: 10.1016/j.eswa.2010.12.045

[8] Farmani R, Henriksen H J, Savic D, et al. An evolutionary Bayesian belief network methodology for participatory decision making under uncertainty: An application to groundwater management[J]. Integrated Environmental Assessment and Management, 2012, 8(3): 456-461.

DOI: 10.1002/ieam.192

[9] Stojadinovic A, Eberhardt J S, Ward E B, et al. Clinical Decision Support and Individualized Prediction of Survival in Colon Cancer: Bayesian Belief Network Model[J]. Annals of surgical oncology, 2013, 20(1): 161-174.

DOI: 10.1245/s10434-012-2555-4

[10] Liao Y, Wang J, Guo Y, et al. Risk assessment of human neural tube defects using a Bayesian belief network[J]. Stochastic Environmental Research and Risk Assessment, 2010, 24(1): 93-100.

DOI: 10.1007/s00477-009-0303-5