As an eco-friendly agricultural model, traditional rice-fish symbiosis system suffers from low outputefficiency. Further improving the input-outputefficiency of rice-fish symbiosis system is conductive to the sustai...
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As an eco-friendly agricultural model, traditional rice-fish symbiosis system suffers from low outputefficiency. Further improving the input-outputefficiency of rice-fish symbiosis system is conductive to the sustainable mountain development. Taking rice-fish symbiosis system in Qingtian as an example, we analyzed redundant input, output deficiencies throughout the life-cycle of production and verified the improved benefits. Results showed that (1) Planting, harvesting and straw treatment had the greatest input redundancy rate, while field management and field fish breeding were most important for the economic output. Field fish output value was the key to improving the outputefficiency. (2) The government and farmers can reduce the redundant inputs mentioned above and improve the outputs through measures such as selective breeding and branding of field fish, renting of farm machinery, straw feedification, scientific terrace layout and water level management. (3) After the implementation of the measures, total economic output value of rice-fish symbiosis system in Qingtian can reach 130,117.05 RMB/hm2, 2.76 times and 2.08 times higher than the rice monoculture model and the traditional rice-fish model. This paper demonstrates the potential for optimizing the modern rice-fish symbiosis system, which has implications for the replication of the rice-fish symbiosis system in other mountainous regions.
By linear programming system identification, we mean the problem of estimating the objective function coefficient vector pi and the technological coefficient matrix A for a linear programming system that best explains...
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By linear programming system identification, we mean the problem of estimating the objective function coefficient vector pi and the technological coefficient matrix A for a linear programming system that best explains a set of input-output vectors. input vectors are regarded as available resources. output vectors are compared to imputed optimal ones by a decisional efficiency measure and a likelihood function is constructed. In an earlier paper, we obtained results for a simplified version of the problem. In this paper, we propose a genetic algorithm approach for the general case in which pi and A are of arbitrary finite dimensions and have nonnegative components. A method based on Householder transformations and Monte Carlo integration is used as an alternative to combinatorial algorithms for the extreme points and volumes of certain required convex polyhedral sets. The method exhibits excellent face validity for a published test data set in data envelopment analysis. (c) 2007 Elsevier B.V. All rights reserved.
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