Applying RAGA-based PPE model to evaluate agricultural production sensitivity to climate change
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DOI:10.7606/j.issn.1000-7601.2009.02.09
Key Words: PPE  RAGA  evaluation  agricultural production sensitivity  climate change
Author NameAffiliation
HAO Lu School of Geography and Remote Sensing Beijing Normal UniversityBeijing 100875ChinaKey L aboratory of Regional Geography Beijing Normal UniversityBeijing 100875ChinaEcological and Agricultural Meteorology Centre of Inner MongoliaHuhhot 010051China 
WANG Jingai School of Geography and Remote Sensing Beijing Normal UniversityBeijing 100875ChinaKey L aboratory of Regional Geography Beijing Normal UniversityBeijing 100875ChinaKey Laboratory of Environmental Change and National Disaster of Ministry of Education of China Beijing Normal UniversityBeijing 100875China 
ZHANG Hua Ecological and Agricultural Meteorology Centre of Inner MongoliaHuhhot 010051China 
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Abstract:
      The research on classification and evaluation of agricultural production sensitivity to climate change is often based on fuzzy theory or analytical hierarchy process(AHP) which has an inevitable problem about weight matrix from experts and its results may also be influenced by artificial factors.A new technique of falling dimension named projection pursuit is applied to agricultural production sensitivity study through using improved rea-l coding-based accelerating genetic algorithm to optimize the projection direction.Thus it can transfer mult-i dimension data into one dimension data through searching for the optimum projection direction to realize agricultural sensitivity classification and its grade evaluation.The method can avoid artificial disturb and overcome the shortcomings of large computation amount and difficulty of computer programming in traditional projection pursuit method and acquire preferably effect.A projection pursuit model is presented for comprehensive evaluation of agricultural production sensitivity to climate.Thus it provides a new method to the research on agricultural production sensitivity classification and grade evaluation.