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   Optimization of Reservoir Operation Using A Bioinspired Metaheuristic Based on the Covid-19 Propagation Model  
   
نویسنده Donyaii Alireza ,Sarraf Amirpouya
منبع Numerical Methods In Civil Engineering - 2020 - دوره : 5 - شماره : 1 - صفحه:15 -28
چکیده    Recently, global warming problems with rapid population growth and socioeconomic development have intensified the demand for water and increased tensions on water supplies. this research evolves the multiobjective coronavirus optimization algorithm (mocvoa) to obtain operational optimum rules of voshmgir dam reservoir under the climate change conditions. the climatic variables downscaled and predicted by the bias correction spatial disaggregation (bcsd) method of mirocesm model, was introduced into the extreme learning machine (elm) modelto evaluate the future runoff flowing into the reservoir. the model objective functions included minimizing vulnerability and enhancing reliability indices during baseline and climate change periods. results revealed that under climate change conditions, the river flow would decrease by 0.17%, increase the temperature up to 2 °c and decrease the rainfall by 23.8%, corresponding to the baseline period. moreover, the extent of vulnerability index variations in the baseline and climate change conditions were also determined as 2038% and 1340%, respectively. the reliability index changes under the baseline and climate change conditions obtained were, 5785% and 4091%. therefore, the vulnerability index was also measured at 33% and 30% for baseline and climate change conditions, respectively, with 80% of reliability index. finally, the comparison of reservoir performance in meeting the water needs of downstream lands at the pareto point of 80% reliability under both conditions indicated that the reservoir release rate would be more in line with the demand in the climate change conditions.
کلیدواژه Bias Correction Spatial Disaggregation ,Climate Change ,Coronavirus Optimization Algorithm ,Extreme Learning Machine ,Miroc-Esm ,Voshmgir Dam Reservoir.
آدرس Golestan Regional Water Company, Iran, Islamic Azad University, Roudehen Branch, Assistant Professor Of Civil Engineering Department, Iran
پست الکترونیکی sarraf@riau.ac.ir
 
     
   
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