This paper introduces a non-iterative algorithmic procedure to design water utilization networks with multiple contaminants in process plants. According to the water pinch analysis rules, the processes in water utiliz...This paper introduces a non-iterative algorithmic procedure to design water utilization networks with multiple contaminants in process plants. According to the water pinch analysis rules, the processes in water utilization systems were first divided into three groups, then water-supply priority algorithm was proposed. The results of case studies showed that the water networks designed by this method gave water consumption lower than that estimated by other approaches. In addition, the procedure was subject to no limitation on the problem scale.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This paper introduces a non-iterative algorithmic procedure to design water utilization networks with multiple contaminants in process plants. According to the water pinch analysis rules, the processes in water utilization systems were first divided into three groups, then water-supply priority algorithm was proposed. The results of case studies showed that the water networks designed by this method gave water consumption lower than that estimated by other approaches. In addition, the procedure was subject to no limitation on the problem scale.
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.
