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用灰色聚类方法综合评价地下水水质 总被引:7,自引:0,他引:7
本文提出了用灰色聚类进行地下水水质综合评价的方法。结合实例与模糊数学方法进行了对比,得到满意的结果。 相似文献
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Waste wood recovery by thermal treatment with energy recovery or by recycling allows the substitution and conservation of primary resources. Swiss government notes the potential presence of tensions between policies which simultaneously encourage the cascade use of wood, the recycling or the energy recovery by thermal treatment of waste wood. The aim of the present research is to assess the coherence of waste wood management in Switzerland by a quantitative and qualitative approach. First, a material flow analysis allows to model the wood resources and waste wood metabolism over one century. The simulation results of various scenarios of waste wood management establish that the additional impacts of the immediate thermal treatment are less significant for the reduction of CO2eq emissions but more significant for the energy production than its cascade treatments on Swiss territory. Secondly, a documentary analysis examines the determinants of the current waste wood treatments prevailing in Switzerland. Thus, the causes of the strong presence on Swiss territory of the sector of thermal treatment, the export of almost half of waste wood generated and the sub-exploitation of Swiss forest act as barriers or drivers that result in introducing a crowding-out effect where no amount of waste wood is available for recycling in Switzerland. The comparison of the results of the two approaches leads to the conclusion that the current waste wood management is coherent in relation to the various goals of the Swiss federal policies but the waste wood potential for energy production is not fully exploited. The recommendations on the waste wood management and the possibilities to use the model for other case studies are given in the conclusion. 相似文献
816.
通过2018年4月、7月和11月在清水河流域布设32个采样点,监测F-、TN、TP等6项水质指标,应用单因子评价法、综合污染指数法、灰色关联法、模糊综合评价法对该河水质状况作综合评价,并分析F-是否参与评价时水质的变化情况.结果表明:当F-不参与水质评价时,清水河各月水质污染程度为7月>11月>4月;当F-参与水质评价... 相似文献
817.
Identification of the leakage of hazardous gases plays an important role in the environment protection, human health and safety of industry production. However, lots of current optimization algorithms, such as particle swarm optimization (PSO) and Grey Wolf Optimizer (GWO), suffer from poor global optimization capability and estimation accuracy. In this work, a hybrid differential evolutionary and GWO (DE-GWO) algorithm is proposed. Tested by simulation cases and Prairie Grass emission experimental data, DE-GWO shows higher estimation accuracy than GWO. Compared with the other four optimization algorithms, DE-GWO exhibits finer robust stability under different population sizes, fewer iterations, as well as higher estimation accuracy with fewer search agents. Importantly, simulation results demonstrate that DE-GWO is more suitable to apply in the scene with a small number of sensors. Therefore, the proposed in this paper outperforms other optimization algorithms for the gas emission inverse problem. DE-GWO can provide reliable estimation towards gas emission identification and positioning, which shows huge potential as the data analysis module of real-time monitoring and early warning system. 相似文献