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Peoples’ Perception and Conservation of Dactylorhiza hatagirea (D. Don) Soóin Manaslu Conservation Area, Central Nepal
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作者 Bikram Pandey Arbindra Timilsina +6 位作者 Binita Pandey Chhabi Lal Thapa Kamal Bahadur Nepali Pradeep Neupane Resham Thapa Sunil Kumar Gaire Mohan Siwakoti 《American Journal of Plant Sciences》 2016年第12期1662-1672,共11页
The present study analyzes the information and perception of the local community of Samagaun VDC, Manaslu Conservation Area Project (MCAP) regarding Dactylorhiza hatagirea (D. Don) Soó (Orchidaceae). We assessed ... The present study analyzes the information and perception of the local community of Samagaun VDC, Manaslu Conservation Area Project (MCAP) regarding Dactylorhiza hatagirea (D. Don) Soó (Orchidaceae). We assessed the local peoples’ perception on its population status, its availability, factors causing its decline and management practices of this terrestrial orchids. A pre-designed questionnaire was used to gather information targeting the age group between 25 and 60 years (n = 75, 45 male and 30 female). Most of the informants (76%) believe that the abundance of this orchid is declining. Over grazing of domestic animals, over harvesting and lack of awareness among the local community were determined to be the major causes of decline of D. hatagirea in the study area. Protection measures as prescribed by the informants were control grazing, raising awareness among the individuals and sustainable harvestings for the long-term conservation of the species. Systematic management plans that incorporate the participation of local individuals and prioritization of their views will be applicable for the proper conservation of the species. 展开更多
关键词 local perceptions Conservation and Management ORCHID Dactylorhiza hatagirea Samagaun VDC Manaslu Conservation Area
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基于AER模型的Multi-Agent遗传算法 被引量:7
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作者 钟伟才 薛明志 +1 位作者 刘静 焦李成 《模式识别与人工智能》 EI CSCD 北大核心 2003年第4期390-396,共7页
本文在分析标准遗传算法的优点和不足的基础上,基于AER模型提出了一种新的遗传算法——Multi-A-gent遗传算法.它利用Agent的局部感知、竞争协同和自学习等特性来实现生物对环境的自适应,从而实现全局优化计算.理论分析证明这种算法是以... 本文在分析标准遗传算法的优点和不足的基础上,基于AER模型提出了一种新的遗传算法——Multi-A-gent遗传算法.它利用Agent的局部感知、竞争协同和自学习等特性来实现生物对环境的自适应,从而实现全局优化计算.理论分析证明这种算法是以概率1收敛的.在实验中,我们首先用10个维数为30的标准测试函数来全面测试算法的性能,然后用50~200维的Rastrigin函数来测试算法处理高维函数的能力.结果表明本文算法具有较强的全局优化能力,鲁棒性强,且具有良好的处理高维函数的能力. 展开更多
关键词 AER模型 Multi-Agent遗传算法 自学习 概率 全局优化计算
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