The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluatio...The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.展开更多
An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variat...An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.展开更多
Aquifers can be defined as complex ecological systems. Their description is closely influenced by geometrical and geological parameters, which portray the hydrogeological behaviour of underground systems. This paper r...Aquifers can be defined as complex ecological systems. Their description is closely influenced by geometrical and geological parameters, which portray the hydrogeological behaviour of underground systems. This paper reports a con<span>tribution to assess</span></span><span style="font-family:"">ing</span><span style="font-family:""> groundwater contamination risk in a particular Sicily sector, where deterministic approaches have methodically assessed and mappe</span><span style="font-family:"">d vulnerability and quality of groundwater. In detail, in the coastal area of Acqued<span>olci (Northern Sicily), already intensely surveyed in the frame of interdisciplinary projects on geological risk, implementing models and systems ha</span>ve been experimented, also considering fuzzy logic. Cartography issues are he<span>re presented and compared, with particular regard to the effect of stoc</span>h<span>astic hydrogeo</span><span>logical elements (<i>i.e.</i> “depth to water”), locally characterized by variability for simultaneous climate, overdraft, irrigation and sea encroachm</span>ent. </span><span style="font-family:"">Th<span>e </span></span><span style="font-family:"">authors show how fuzzy logic, applied to vulnerability settings, contributes to a better comprehension of the passive scenery offered by aquifers in</span><span style="font-family:""> Acquedolci Sicily area.展开更多
基金supported by the National Key Research and Development Program of China (No. 2017YFC0405006)the Innovative Research Groups of the National Natural Science Foundation of China (No. 51621092)the Natural Science Foundation of Tianjin (No. 16JCYBJC23100)
文摘The complex relationships between indicators and water conditions cause fuzzy and gray uncertainties in evaluation of water quality. Compared to conventional single-factor evaluation methods, the combination evaluation method can consider these two uncertainties to produce more objective and reasonable evaluation results. In this paper, we propose a combination evaluation method with two main parts:(1) the use of fuzzy comprehensive evaluation and gray correlation analysis as submodels with which to consider the fuzzy and gray uncertainties and(2) the establishment of a combination model based on minimum bias squares. In addition, using this method, we evaluate the water quality of a ditch in a typical rice–wheat system of Yixing city in the Taihu Lake Basin during three rainfall events. The results show that the ditch water quality is not good and we found the chemical oxygen demand to be the key indicator that affects water quality most significantly. The proposed combination evaluation method is more accurate and practical than single-factor evaluation methods in that it considers the uncertainties of fuzziness and grayness.
基金The National Natural Science Foundation of China under contract No.51379002the Fundamental Research Funds for the Central Universities of China under contract Nos 3132016322 and 3132016314the Applied Basic Research Project Fund of the Chinese Ministry of Transport of China under contract No.2014329225010
文摘An efficient and accurate prediction of a precise tidal level in estuaries and coastal areas is indispensable for the management and decision-making of human activity in the field wok of marine engineering. The variation of the tidal level is a time-varying process. The time-varying factors including interference from the external environment that cause the change of tides are fairly complicated. Furthermore, tidal variations are affected not only by periodic movement of celestial bodies but also by time-varying interference from the external environment. Consequently, for the efficient and precise tidal level prediction, a neuro-fuzzy hybrid technology based on the combination of harmonic analysis and adaptive network-based fuzzy inference system（ANFIS）model is utilized to construct a precise tidal level prediction system, which takes both advantages of the harmonic analysis method and the ANFIS network. The proposed prediction model is composed of two modules： the astronomical tide module caused by celestial bodies’ movement and the non-astronomical tide module caused by various meteorological and other environmental factors. To generate a fuzzy inference system（FIS） structure,three approaches which include grid partition（GP）, fuzzy c-means（FCM） and sub-clustering（SC） are used in the ANFIS network constructing process. Furthermore, to obtain the optimal ANFIS based prediction model, large numbers of simulation experiments are implemented for each FIS generating approach. In this tidal prediction study, the optimal ANFIS model is used to predict the non-astronomical tide module, while the conventional harmonic analysis model is used to predict the astronomical tide module. The final prediction result is performed by combining the estimation outputs of the harmonious analysis model and the optimal ANFIS model. To demonstrate the applicability and capability of the proposed novel prediction model, measured tidal level samples of Fort Pulaski tidal station are selected as the testing database. Simulation and experimental results confirm that the proposed prediction approach can achieve precise predictions for the tidal level with high accuracy, satisfactory convergence and stability.
文摘Aquifers can be defined as complex ecological systems. Their description is closely influenced by geometrical and geological parameters, which portray the hydrogeological behaviour of underground systems. This paper reports a con<span>tribution to assess</span></span><span style="font-family:"">ing</span><span style="font-family:""> groundwater contamination risk in a particular Sicily sector, where deterministic approaches have methodically assessed and mappe</span><span style="font-family:"">d vulnerability and quality of groundwater. In detail, in the coastal area of Acqued<span>olci (Northern Sicily), already intensely surveyed in the frame of interdisciplinary projects on geological risk, implementing models and systems ha</span>ve been experimented, also considering fuzzy logic. Cartography issues are he<span>re presented and compared, with particular regard to the effect of stoc</span>h<span>astic hydrogeo</span><span>logical elements (<i>i.e.</i> “depth to water”), locally characterized by variability for simultaneous climate, overdraft, irrigation and sea encroachm</span>ent. </span><span style="font-family:"">Th<span>e </span></span><span style="font-family:"">authors show how fuzzy logic, applied to vulnerability settings, contributes to a better comprehension of the passive scenery offered by aquifers in</span><span style="font-family:""> Acquedolci Sicily area.
