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CO Pollutant Evaluation Using Two Artificial NeuralNetwork Algorithms in Tehran

عنوان مقاله: CO Pollutant Evaluation Using Two Artificial NeuralNetwork Algorithms in Tehran
شناسه ملی مقاله: NCSAC07_194
منتشر شده در دومین همایش بین المللی و هفتمین همایش ملی معماری و شهر پایدار در سال 1401
مشخصات نویسندگان مقاله:

Saeed Behzadi - Assistant Professor in Surveying Engineering, Department of Civil Engineering, Shahid Rajaee TeacherTraining University, Tehran, Iran,

خلاصه مقاله:
Air pollution is one of the most important environmental problems of the last century that threatens human health. Air pollution is the presence of one or more pollutants in the open air that are harmful to humans, animals, plants and property. Air pollution unacceptably disturbs the comfortable use of life. In this paper, the CO pollutant city was evaluated in Tehran using two artificial neural network algorithms BFGS Quasi-Newton and Resilient Backpropagation. The result indicated that the Resilient Backpropagation algorithm has less error with five hidden layers, and its root mean square is equal to ۱.۱۱۳۰.

کلمات کلیدی:
Air pollution, Artificial Neural Network,CO,RS

صفحه اختصاصی مقاله و دریافت فایل کامل: https://civilica.com/doc/1733626/