Forecasting: Adopting the Methodology of Support Vector Machines to Nursing Research
نویسندگان
چکیده
منابع مشابه
Forecasting: Adopting the methodology of support vector machines to nursing research.
In nursing studies, linear statistical methods are commonly used to analyze data on subjective perceptions. Most of the collected data include participants’ subjective perceptions and are usually not collected in a controlled environment. For linear regression analyses, there is a common understanding that the distributions of some studied variables might not be close to linear in nature. Howev...
متن کاملSTAGE-DISCHARGE MODELING USING SUPPORT VECTOR MACHINES
Establishment of rating curves are often required by the hydrologists for flow estimates in the streams, rivers etc. Measurement of discharge in a river is a time-consuming, expensive, and difficult process and the conventional approach of regression analysis of stage-discharge relation does not provide encouraging results especially during the floods. P
متن کاملApplication of support vector machines in !nancial time series forecasting
This paper deals with the application of a novel neural network technique, support vector machine (SVM), in !nancial time series forecasting. The objective of this paper is to examine the feasibility of SVM in !nancial time series forecasting by comparing it with a multi-layer back-propagation (BP) neural network. Five real futures contracts that are collated from the Chicago Mercantile Market ...
متن کاملStreamflow Forecasting at Ungaged Sites Using Support Vector Machines
Developing reliable estimates of streamflow prediction are crucial for water resources management and flood forecasting purposes. The objectives of this study are to investigate the potential of support vector machines (SVM) model for streamflow forecasting at ungaged sites, and to compare its performance with other statistical method of multiple linear regression (MLR). Three quantitative stan...
متن کاملLoad Forecasting with Support Vector Machines and Semi-parametric Method
A new approach to short-term electrical load forecasting is investigated in this paper. As electrical load data are highly non-linear in nature, in the proposed approach, we first separate out the linear and the non-linear parts, and then forecast using the non-linear part only. Semi-parametric spectral estimation method is used to decompose a load data signal into a harmonic linear signal mode...
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: Worldviews on Evidence-Based Nursing
سال: 2006
ISSN: 1545-102X,1741-6787
DOI: 10.1111/j.1741-6787.2006.00062.x