• 关键词：富营养化  综合评价  综合指数  粒子群算法  优化算法

• 基金项目：国家重点基础研究发展规划(973)项目(No2002CB412301);国家自然科学基金项目(No50779042)

• 李祚泳
• 成都信息工程学院, 成都 610041

• 汪嘉杨
• 成都信息工程学院, 成都 610041

• 赵晓莉
• 成都信息工程学院, 成都 610041

• 徐婷婷
• 成都信息工程学院, 成都 610041

• 摘要：提出了一个用幂函数加和型表示湖泊富营养化评价的综合指数公式,并采用粒子群算法优化公式中的参数,得出优化后适用于多指标的富营养化综合评价的普适指数公式,该公式的特例也可作为单项指标的富营养化评价指数公式.将优化好的湖泊富营养化评价公式用于我国不同地域和不同类型的65个湖泊的实例评价,其评价结果与用修正卡森指数公式TSI_m和我国营养状态指数公式TSI_c及其它方法的评价结果基本一致,并与实况相符,从而为水体富营养化评价提供了一种新的有效途径.

• Abstract：This paper proposes a comprehensive index formula based on a power function of weighted sums for evaluation of the eutrophication level of lakes. Particle swarm optimization (PSO) is used to optimize the parameters in the formula and an optimized universal multi-index formula for comprehensive eutrophication evaluation, a special case of which can also be suited for single index evaluation, is thus set up. By applying this formula to the practical eutrophication evaluation of sixty-five lakes of various kinds in different regions in China, the results of this evaluation, which correspond with the real conditions, are basically in accord with those obtained by other evaluation methods, such as the revised Carlson index formula (TSI_m) and China′s eutrophic state index formula (TSI_c). In this way, a new effective approach to eutrophication evaluation for water bodies is suggested.

• Key words：eutrophication  comprehensive evaluation  comprehensive index  particle swarm optimization  optimal algorithm

• 
  摘要点击次数： 2845 全文下载次数： 3054