Employing Artificial Neural Networks into Achieving Parameter Optimization of Multi-Response Problem with Different Importance Degree Consideration
نویسندگان
چکیده
منابع مشابه
Multi-parameter estimating photometric redshifts with artificial neural networks
We calculate photometric redshifts from the Sloan Digital Sky Survey Data Release 2 Galaxy Sample using artificial neural networks (ANNs). Different input patterns based on various parameters (e.g. magnitude, color index, flux information) are explored and their performances for redshift prediction are compared. For ANN technique, any parameter may be easily incorporated as input, but our resul...
متن کاملsolution of security constrained unit commitment problem by a new multi-objective optimization method
چکیده-پخش بار بهینه به عنوان یکی از ابزار زیر بنایی برای تحلیل سیستم های قدرت پیچیده ،برای مدت طولانی مورد بررسی قرار گرفته است.پخش بار بهینه توابع هدف یک سیستم قدرت از جمله تابع هزینه سوخت ،آلودگی ،تلفات را بهینه می کند،و هم زمان قیود سیستم قدرت را نیز برآورده می کند.در کلی ترین حالتopf یک مساله بهینه سازی غیر خطی ،غیر محدب،مقیاس بزرگ،و ایستا می باشد که می تواند شامل متغیرهای کنترلی پیوسته و گ...
Optimizing Multiple Response Problem Using Artificial Neural Networks and Genetic Algorithm
This paper proposes a new intelligent approach for solving multi-response statistical optimization problems. In most real world optimization problems, we are encountered adjusting process variables to achieve optimal levels of output variables (response variables). Usual optimization methods often begin with estimating the relation function between the response variable and the control variab...
متن کاملKun-Lin Hsieh and Lee-Ing Tong: Parameter Optimization for Quality Response with Linguistic Ordered Category by Employing Artificial Neural Networks: A Case Study
Most studies of parameter optimization focus on the quantitative quality response. The parameter optimization of the qualitative (or linguistic) quality response is seldom mentioned. For the proposed approaches, only the optimum categorical level settings of factors can be determined even though the control factors have the continuous values. Artificial neural networks (ANN) have been successfu...
متن کاملEvolutionary artificial neural networks by multi-dimensional particle swarm optimization
In this paper, we propose a novel technique for the automatic design of Artificial Neural Networks (ANNs) by evolving to the optimal network configuration(s) within an architecture space. It is entirely based on a multi-dimensional Particle Swarm Optimization (MD PSO) technique, which re-forms the native structure of swarm particles in such a way that they can make inter-dimensional passes with...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Information Technology Journal
سال: 2010
ISSN: 1812-5638
DOI: 10.3923/itj.2010.918.926