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Showing 2 results for Nourpour
Mohammad Mazidi Sharfabadi, Mansour Alizadeh, Leila Nourpour,
Volume 17, Issue 11 (1-2018)
Abstract
In this study, the inverse heat transfer problem of the estimation of unknown heat flux imposed on the boundary of a one-dimensional slab is solved by the genetic algorithm and two modified versions of this algorithm and the results obtained from different versions of the genetic algorithm are compared with each other. These two modified versions are developed based upon genes rearrangement approach. In this approach, an additional cost function is added to the conventional genetic algorithm to increase its computational efficiency. The results obtained by using errorless simulated temperature measurements show that modified genetic algorithms can improve the convergence and accuracy of the inverse solution in comparison with the conventional genetic algorithm and they give accurate estimations for the supposed heat flux even by using a small number of generations and moderate population size. The results show that modified genetic algorithm (2) provides better response to all the parameters of the solution evaluation in comparison with the conventional genetic algorithm and other modified version. In addition, in this study, the effect of adding Tikhonov regularization term to the objective function on the stability of the solution is investigated. Although only a simple one-dimensional problem has been solved in this study to demonstrate the approach of genes rearrangement, but this approach is expected to succeed in the inverse solution of complicated multidimensional problems.
Volume 26, Issue 5 (9-2024)
Abstract
One of the most important decisions that farmers make is the allocation of resources in an optimal manner, which is often done by determining the optimal cropping pattern. The purpose of this study was to present a cultivation model compatible with the agricultural ecosystem of Shiraz Plain, Fars Province, Iran, by quantifying the environmental effects of agricultural production using the Life Cycle Assessment (LCA) approach. The results of LCA showed that cultivation of crops such as lentils, onions, and tomatoes had the most negative environmental effects. The ecosystem quality index for crops in this plain varied between 0.03 and 3.64 PT. The highest negative impact of crop cultivation on the quality of the ecosystem was attributed to onion, tomato, and rain-fed lentils. The results of multi-objective planning showed that farmers can achieve their economic objectives and policymakers’ environmental goals through reducing the area under cultivation. By changing the cropping pattern towards the suggested pattern for Shiraz Plain, an average decrease of 5.60% in profit was expected. However, this change is an effective step in controlling consumption of water, chemical fertilizers, and pesticides. Achieving sustainable agriculture in terms of economic and environmental indicators is possible by reducing the cropland area and economic profit by 18.05% and 11.43%, respectively.
