Fuzzy similarity measures, which are used to judge the closeness of two fuzzy sets, are presented to evaluate the water quality of the Haihe River. Based on the membership functions and coefficient of variation as the weights, four fuzzy similarity measures (including Lattice similarity measure, Hamming similarity measure, Euclidean similarity measure and the max-min similarity measure) are used to classify the 299 samples into the proper water quality standard ranks. The results are compared with the traditional distance discriminant methods. The calculation of two traditional distance discriminant methods (both Euclidean distance and absolute value distance) is also based on the use of coefficients of variation as the weights. Without the Lattice similarity measure, for this method loses some information, the correct assignment of samples classified into the same water quality ranks is 75.92% with the other three similarity measures and two distance discriminant methods. This result shows the reliability of the five methods. Only considering the three similarity measures, there were only 1.01% of the samples that did not classify to the same ranks, while the corresponding ratio of the two distance discriminant methods was 5.69%. The results of leave-one-out cross validation show that more than 88% of the samples are classified to the proper ranks, which demonstrates that the similarity measures are suitable to evaluate the water quality of the Haihe River. 相似文献
Currently, the correlation between ambient temperature and systemic lupus erythematosus (SLE) hospital admissions remains not determined. The aim of this study was to explore the correlation between ambient temperature and SLE hospital admissions in Hefei City, China. An ecological study design was adopted. Daily data on SLE hospital admissions in Hefei City, from January 1, 2007, to December 31, 2017, were obtained from the two largest tertiary hospitals in Hefei, and the daily meteorological data at the same period were retrieved from China Meteorological Data Network. The generalized additive model (GAM) combined with distributed lag nonlinear model (DLNM) with Poisson link was applied to evaluate the influence of ambient temperature on SLE hospital admissions after controlling for potential confounding factors, including seasonality, relative humidity, day of week, and long-term trend. There were 1658 SLE hospital admissions from 2007 to 2017, including 370 first admissions and 1192 re-admissions (there were 96 admissions with admission status not stated). No correlation was observed between ambient temperature and SLE first admissions, but a correlation was found between low ambient temperature and SLE re-admissions (RR: 2.53, 95% CI: 1.11, 5.77) (3.5 °C vs 21 °C). The effect of ambient temperature on SLE re-admissions remained for 2 weeks but disappeared in 3 weeks. Exposure to low ambient temperature may increase hospital re-admissions for SLE, and thus it is important for SLE patients to maintain a warm living environment and avoid exposure to lower ambient temperature.
This paper presents a methodology for quantifying the effectiveness of water-trading under uncertainty, by developing an optimization model based on the interval-parameter two-stage stochastic program (TSP) technique. In the study, the effectiveness of a water-trading program is measured by the water volume that can be released through trading from a statistical point of view. The methodology can also deal with recourse water allocation problems generated by randomness in water availability and, at the same time, tackle uncertainties expressed as intervals in the trading system. The developed methodology was tested with a hypothetical water-trading program in an agricultural system in the Swift Current Creek watershed, Canada. Study results indicate that the methodology can effectively measure the effectiveness of a trading program through estimating the water volume being released through trading in a long-term view. A sensitivity analysis was also conducted to analyze the effects of different trading costs on the trading program. It shows that the trading efforts would become ineffective when the trading costs are too high. The case study also demonstrates that the trading program is more effective in a dry season when total water availability is in shortage. 相似文献
•CeOx/GF-EP process had the better degradation efficiency than GF-EP process.•CeOx/GF-EP process had the flexible application in the pH range from 5.0 to 9.0.•CeOx could enhance surface hydrophilicity and reduce the charge-transfer resistance.•The interfacial electron transfer process was revealed. E-peroxone (EP) was one of the most attractive AOPs for removing refractory organic compounds from water, but the high energy consumption for in situ generating H2O2 and its low reaction efficiency for activating O3 under acidic conditions made the obstacles for its practical application. In this study, cerium oxide was loaded on the surface of graphite felt (GF) by the hydrothermal method to construct the efficient electrode (CeOx/GF) for mineralizing carbamazepine (CBZ) via EP process. CeOx/GF was an efficient cathode, which led to 69.4% TOC removal in CeOx/GF-EP process with current intensity of 10 mA in 60 min. Moreover, CeOx/GF had the flexible application in the pH range from 5.0 to 9.0, TOC removal had no obvious decline with decrease of pH. Comparative characterizations showed that CeOx could enhance surface hydrophilicity and reduce the charge-transfer resistance of GF. About 5.4 mg/L H2O2 generated in CeOx/GF-EP process, which was 2.1 times as that in GF-EP process. The greater ozone utility was also found in CeOx/GF-EP process. More O3 was activated into hydroxyl radicals, which accounted for the mineralization of CBZ. An interfacial electron transfer process was revealed, which involved the function of oxygen vacancies and Ce3+/Ce4+ redox cycle. CeOx/GF had the good recycling property in fifth times’ use. 相似文献
Poor biodegradability and insufficient carbon source are discovered from influent.Influent indices presented positively normal distribution or skewed distribution.Average energy consumption of WWTPs in Taihu Basin was as high as 0.458 kWh/m3.Energy consumption increases with the increase in influent volume and COD reduction.The total energy consumption decreases with the NH3-N reduction. The water quality and energy consumption of wastewater treatment plants (WWTPs) in Taihu Basin were evaluated on the basis of the operation data from 204 municipal WWTPs in the basin by using various statistical methods. The influent ammonia nitrogen (NH3-N) and total nitrogen (TN) of WWTPs in Taihu Basin showed normal distribution, whereas chemical oxygen demand (COD), biochemical oxygen demand (BOD5), suspended solid (SS), and total phosphorus (TP) showed positively skewed distribution. The influent BOD5/COD was 0.4%–0.6%, only 39.2% SS/BOD5 exceeded the standard by 36.3%, the average BOD5/TN was 3.82, and the probability of influent BOD5/TP>20 was 82.8%. The average energy consumption of WWTPs in Taihu Basin in 2017 was 0.458 kWh/m3. The specific energy consumption of WWTPs with a daily treatment capacity of more than 5 × 104 m3 in Taihu Basin was stable at 0.33 kWh/m3. A power function relationship was observed between the reduction in COD and NH3-N and the specific energy consumption of pollutant reduction, and the higher the pollutant reduction is, the lower the specific energy consumption of pollutant reduction presents. In addition, a linear relationship existed between the energy consumption of WWTPs and the specific energy consumption of influent volume and pollutant reduction. Therefore, upgrading and operation with less energy consumption of WWTPs is imperative and the suggestions for Taihu WWTPs based on stringent discharge standard are proposed in detail. 相似文献
An optimized nonlinear grey Bernoulli model was proposed by using a particle swarm optimization algorithm to solve the parameter optimization problem. In addition, each item in the first-order accumulated generating sequence was set in turn as an initial condition to determine which alternative would yield the highest forecasting accuracy. To test the forecasting performance, the optimized models with different initial conditions were then used to simulate dissolved oxygen concentrations in the Guanting reservoir inlet and outlet (China). The empirical results show that the optimized model can remarkably improve forecasting accuracy, and the particle swarm optimization technique is a good tool to solve parameter optimization problems. What's more, the optimized model with an initial condition that performs well in in-sample simulation may not do as well as in out-of-sample forecasting. 相似文献