Numerical Solution of First-Order differential equation based Z-numbers using Neural Network
محل انتشار: سومین کنفرانس سیستم های تصمیم گیری هوشمند
سال انتشار: 1397
نوع سند: مقاله کنفرانسی
زبان: انگلیسی
مشاهده: 511
فایل این مقاله در 9 صفحه با فرمت PDF قابل دریافت می باشد
- صدور گواهی نمایه سازی
- من نویسنده این مقاله هستم
این مقاله در بخشهای موضوعی زیر دسته بندی شده است:
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
IDS03_065
تاریخ نمایه سازی: 31 اردیبهشت 1398
چکیده مقاله:
In this work, we have the general form of a First-Order differential equation based Z-Valuations. Then a new method for solving these equations using generalized neural networks offer. The proposed method consists of a function is based on Z-Valuations. that s mean, ??(Z Tt)=(?AT?(?t),?BT ?(?t)), The first component,BT(?t), is a restriction (constraint) on the values which a real-valued uncertain variable,AT (?t ), is allowed to take. The second componentis a measure of reliability (certainty) of the first component. Since the function values and are fuzzy. We use the technique of α- cutting, both the above functions will be converted to real functions. that s mean, ?ZT?(t)=((AT1?1(?t),?AT2?2(t)),(BT1(t),B T2(?t))). Then, using the method of least squares error, we trained neural network so that the solution proposed is a convenient approximation of the exact answer. An example is shown in a proposed method, an appropriate method to approximate the original answer.
کلیدواژه ها:
نویسندگان
Nader Biranvand
Department of Mathematics, Faculty of Basic Sciences Imam Ali University, Tehran, Iran
Somayeh Ezadi
Department of statistics, Tehran North Branch, Islamic Azad University, Tehran, Iran
Ashkan Moradi
Department of Mathematics, Islamic Azad University of Sama Kermanshah Branch, Kermanshah, Iran