Yantian District in Shenzhen is a water deficient area. Water shortage has become a major obstacle to its further economic progress. Consequently, rational exploitation of nontraditional water resources(NWR)has been n...Yantian District in Shenzhen is a water deficient area. Water shortage has become a major obstacle to its further economic progress. Consequently, rational exploitation of nontraditional water resources(NWR)has been naturally adopted to increase local available water volume. The purpose of this paper is to analyse the exploitation of two kinds of NWR, namely wastewater reuse and seawater utilization, in Yantian District, and assess the contribution of each mode to deal with the water crisis. Two different nontraditional water supply systems respectively based on the reclaimed water and sea water were presented, and the effects of each system were evaluated in terms of technology, economy and environment. The result shows that both wastewater reclamation and reuse (WRR) and direct utilization of seawater (DUS) are of great importance to cope with the tight water resource situation in the district. The data indicate that the fresh water saved by WRR system and DUS system is 29 and 17 million m3/a respectively. Moreover, the BOD, COD, NH3-N and T-P reduced by the WRR system are 870, 2900, 725 and 87 t/a, respectively. Considering the integrated effectiveness, the development of WRR system, which is of specific significance to exploiting new water resource and save natural fresh water supplied from distant water diversion project, is the preferred methods used to solve the water shortage problem in Yantian District and recover the water environment as well as maintain the sustainable development of the city zone.展开更多
Several conflicting objectives are considered in decision-making. MCDA （multi-criteria decision analysis） methods are developed to facilitate better decision making by decision-makers. Water supply problems are comp...Several conflicting objectives are considered in decision-making. MCDA （multi-criteria decision analysis） methods are developed to facilitate better decision making by decision-makers. Water supply problems are complex problems with multiple decision making and criteria. Hence, the use of multi-criteria decision analysis is very appropriate for solving these problems. Multi-criteria decision analysis can be divided into three main groups： value measurement models, goals, aspiration and reference level models and outranking models. The methods listed have been applied to water supply problems, especially in the evaluation of alternative water supply strategies. Each method has its advantages and limitations. A good alternative for concluding a better-suited method for water supply problems is to apply more than one method, either in combination to make use of the strengths of both methods, or in parallel to obtain a broader decision basis for the decision maker. Previous studies of MCDA in water supply planning have usually considered water supply networks with only one water service delivery. Advanced water supply sources with multiple water service delivery systems have been neglected. This is an on-going study in which analytical hierarchical multi-criteria decision analysis methods are proposed for solving water supply problems and a framework for improved rainwater harvesting systems will be developed.展开更多
Nutrition diagnosis plays a key role in the crop＇s growth, which has mainly been car- ried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in th...Nutrition diagnosis plays a key role in the crop＇s growth, which has mainly been car- ried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in this field. A procedure is proposed in this paper to diagnose nitrogen nutrition non-destructively for rapeseed qualitatively based on the multifractal theory. Twelve texture parameters are given by the method of multifractal detrended fluctuation （MF-DFA）, which contains six generalized Hurst exponents and six relative multifractal parameters that are used as features of the rapeseed leaf images for identifying the two nitrogen levels, namely, the N-mezzo and the N-wane. For the base leaves, central leaves and top leaves of the rapeseed plant and the three-section mixed samples, three parameters combinations are selected to conduct the work. Five classifiers of Fisher＇s linear discriminant algorithm （LDA）, extreme learning machine （ELM）, support vector machine and kernel method （SVMKM）, random decision forests （RF） and K-nearest neighbor algorithm （KNN） are employed to calculate the diagno- sis accuracy. An interesting finding is that the best diagnose accuracy is from the base leaves of the rapeseed plant. It is explained that the base leaf is the most sensitive to the nitrogen deficiency. The diagnose effect by the base leaves samples is outshining the existing result significantly for the same leaves samples. For the mixed samples, the aver- aged discriminant accuracy reaches 97.12% and 97.56% by SVMKM and RF methods with the 10-fold cross-validation respectively. The resulting high accuracy on N-levels identification shows the feasibility and efficiency of our method.展开更多
文摘Yantian District in Shenzhen is a water deficient area. Water shortage has become a major obstacle to its further economic progress. Consequently, rational exploitation of nontraditional water resources(NWR)has been naturally adopted to increase local available water volume. The purpose of this paper is to analyse the exploitation of two kinds of NWR, namely wastewater reuse and seawater utilization, in Yantian District, and assess the contribution of each mode to deal with the water crisis. Two different nontraditional water supply systems respectively based on the reclaimed water and sea water were presented, and the effects of each system were evaluated in terms of technology, economy and environment. The result shows that both wastewater reclamation and reuse (WRR) and direct utilization of seawater (DUS) are of great importance to cope with the tight water resource situation in the district. The data indicate that the fresh water saved by WRR system and DUS system is 29 and 17 million m3/a respectively. Moreover, the BOD, COD, NH3-N and T-P reduced by the WRR system are 870, 2900, 725 and 87 t/a, respectively. Considering the integrated effectiveness, the development of WRR system, which is of specific significance to exploiting new water resource and save natural fresh water supplied from distant water diversion project, is the preferred methods used to solve the water shortage problem in Yantian District and recover the water environment as well as maintain the sustainable development of the city zone.
文摘Several conflicting objectives are considered in decision-making. MCDA （multi-criteria decision analysis） methods are developed to facilitate better decision making by decision-makers. Water supply problems are complex problems with multiple decision making and criteria. Hence, the use of multi-criteria decision analysis is very appropriate for solving these problems. Multi-criteria decision analysis can be divided into three main groups： value measurement models, goals, aspiration and reference level models and outranking models. The methods listed have been applied to water supply problems, especially in the evaluation of alternative water supply strategies. Each method has its advantages and limitations. A good alternative for concluding a better-suited method for water supply problems is to apply more than one method, either in combination to make use of the strengths of both methods, or in parallel to obtain a broader decision basis for the decision maker. Previous studies of MCDA in water supply planning have usually considered water supply networks with only one water service delivery. Advanced water supply sources with multiple water service delivery systems have been neglected. This is an on-going study in which analytical hierarchical multi-criteria decision analysis methods are proposed for solving water supply problems and a framework for improved rainwater harvesting systems will be developed.
基金This work was supported by National Natural Science Foundation of China （Grant No. 31501227）, the Key R＆D Project Funds of Hunan Province, China （Grant No. 2015JC3098） and the Young Scholar Project and Key Project Funds of the Department of Education of Hunan Province, China （Grant No. 14B087, 151083）.
文摘Nutrition diagnosis plays a key role in the crop＇s growth, which has mainly been car- ried out in the field by agricultural workers. Currently, automatic nutrition recognition technologies have been widely used in this field. A procedure is proposed in this paper to diagnose nitrogen nutrition non-destructively for rapeseed qualitatively based on the multifractal theory. Twelve texture parameters are given by the method of multifractal detrended fluctuation （MF-DFA）, which contains six generalized Hurst exponents and six relative multifractal parameters that are used as features of the rapeseed leaf images for identifying the two nitrogen levels, namely, the N-mezzo and the N-wane. For the base leaves, central leaves and top leaves of the rapeseed plant and the three-section mixed samples, three parameters combinations are selected to conduct the work. Five classifiers of Fisher＇s linear discriminant algorithm （LDA）, extreme learning machine （ELM）, support vector machine and kernel method （SVMKM）, random decision forests （RF） and K-nearest neighbor algorithm （KNN） are employed to calculate the diagno- sis accuracy. An interesting finding is that the best diagnose accuracy is from the base leaves of the rapeseed plant. It is explained that the base leaf is the most sensitive to the nitrogen deficiency. The diagnose effect by the base leaves samples is outshining the existing result significantly for the same leaves samples. For the mixed samples, the aver- aged discriminant accuracy reaches 97.12% and 97.56% by SVMKM and RF methods with the 10-fold cross-validation respectively. The resulting high accuracy on N-levels identification shows the feasibility and efficiency of our method.
