On Proper Handling of Multi-collinear Inputs and Errors-in-Variables with Explicit and Implicit Neural Models
نویسندگان
چکیده
When model input variables appear redundant, it is common practice to simply drop some of them until the redundancy is removed, prior to model identification. As a result, the final model has forgotten the interdependency in the original input data, which may be an essential condition for
منابع مشابه
Pareto Optimization of Two-element Wing Models with Morphing Flap Using Computational Fluid Dynamics, Grouped Method of Data handling Artificial Neural Networks and Genetic Algorithms
A multi-objective optimization (MOO) of two-element wing models with morphing flap by using computational fluid dynamics (CFD) techniques, artificial neural networks (ANN), and non-dominated sorting genetic algorithms (NSGA II), is performed in this paper. At first, the domain is solved numerically in various two-element wing models with morphing flap using CFD techniques and lift (L) and drag ...
متن کاملThe Effect of Explicit and Implicit Corrective Feedback on Segmental Word-Level Pronunciation Errors
Over the last few years, the realm of foreign language learning has witnessed an abundance of research concerning the effectiveness of corrective feedback on the acquisition of grammatical features, with the study of other target language subsystems, such as pronunciation, being few and far between. In order to bridge this gap, the present study intended to investigate and compare the immediate...
متن کاملThe Impact of Explicit and Implicit Recasts on the Grammatical Accuracy of Iranian EFL Learners’ Writing Performance
The present study aimed at investigating the effects of explicit and implicit recasts on Iranian EFL learners' acquisition of English relative clauses. For this purpose, 64 participants were selected out of 94 intermediate level EFL learners at Falagh language Institute, Rasht, Iran. To have homogenized groups, the researcher administered a language proficiency test (TOEFL). Then, the researche...
متن کاملArtificial neural network technique for rainfall temporal distribu-tion simulation (Case study: Kechik region)
Artificial neural networks (ANNs) have become one of the most promising tools for rainfall simulation since a few years ago. However, most of the researchers have focused on rainfall intensity records as well as on watersheds, which generally are utilized as input records of other hydro-meteorological variables. The present study was conducted in Kechik station, Golestan Province (northern Iran...
متن کاملThe efficiency of Artificial Neural Network, Neuro-Fuzzy and Multivariate Regression models for runoff and erosion simulation using rainfall simulator
1- INTRODUCTION According to the complexity of environmental factors related to erosion and runoff, correct simulation of these variables find importance under rain intensity domain of watershed areas. Although modeling of erosion and runoff by Artificial Neural Network and Neuro-Fuzzy based on rainfall-runoff and discharge-sediment models were widely applied by researchers, scrutinizing Arti...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
دوره شماره
صفحات -
تاریخ انتشار 2003