The Research of Key Factors Influencing Ecological Civilization Consciousness of College Students Based on Ant Colony Clustering Algorithm

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Ecological civilization construction is related to not only peoples well-being, but also the long term plan of a countrys development and revitalization. This research applied ant colony clustering algorithm to study the feasibility and key factors of ecological civilization promotion in the college students It is the first time that quantitative method was introduced into the human consciousness research. The results show that college students have known the situation of resources and environmental problems well, which is a advantage for the promotion of ecological civilization concept. However, the role that colleges play in ecological civilization promotion has not performed fully. And above two items are the key factors to promote ecological civilization promotion.

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894-898

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January 2014

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© 2014 Trans Tech Publications Ltd. All Rights Reserved

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[1] Arnaud Buchsa, Odile Blancharda. Exploring the Concept of Sustainable Development Through Role-Playing. The Journal of Economic Education, Vol 4 (2011), pp.388-394.

Google Scholar

[2] Gary P. Hampson. Eco-logical education for the long emergency. Futures, Vol 44 (2012), pp.71-80.

DOI: 10.1016/j.futures.2011.08.009

Google Scholar

[3] Zhang Wei. Ecological Civilization Construction is the Fundamental Way to Develop Low-carbon Economy. Energy Procedia, Vol 5 (2011), pp.839-843.

DOI: 10.1016/j.egypro.2011.03.148

Google Scholar

[4] Qi Wen Jiang, Jing Wang. Applied Research of Ant Colony Clustering Algorithms in Healthcare Consumer Segments . Communications in Computer and Information Science, Vol 210 (2011), pp.335-342.

DOI: 10.1007/978-3-642-23065-3_49

Google Scholar

[5] Pablo Loyola, Pablo E Roma, Juan D Velasquez. Predicting web user behavior using learning-based ant colony optimization . Engineering Applications of Artificial Intelligence, Vol 25 (2012), p.889–897.

DOI: 10.1016/j.engappai.2011.10.008

Google Scholar

[6] B Biswal, P K Dash, S Mishra. A hybrid ant colony optimization technique for power signal pattern classification. Expert Systems with Applications, Vol 38 (2011), p.6368–6375.

DOI: 10.1016/j.eswa.2010.11.102

Google Scholar

[7] M. Dorigo. Optimization learning and natural algorithms. Thesis, Department of Electronics, Politecnico diMilano, (1992).

Google Scholar

[8] E D Lumer, B Faieta. Diversity and adaptation in populations of clustering ants. Proceedings of the third international conference on simulation of adaptive behabior: from animals to animals, (1994), pp.499-508.

Google Scholar

[9] Abdolreza Hatamlou, Salwani Abdullah, Hossein Nezamabadi-pour. A combined approach for clustering based on K-means and gravitational search algorithms. Swarm and Evolutionary Computation, Vol 6 (2012), p.47–52.

DOI: 10.1016/j.swevo.2012.02.003

Google Scholar