نتایج جستجو برای: rmse regression model

تعداد نتایج: 2331037  

2004
Sridhar Krishna Nemala Partha Pratim Talukdar Kalika Bali A. G. Ramakrishnan

This paper reports preliminary results of data-driven modeling of segmental (phoneme) duration for Hindi. Classification and Regression Tree (CART) based datadriven duration modeling for segmental duration prediction is presented. A number of features are considered and their usefulness and relative contribution for segmental duration prediction is assessed. Objective evaluation of the duration...

Journal: :Journal of radiation research 2010
Wei Long Peixun Liu

This paper provides quantitative structure activity relationship (QSAR) models for predicting the radiosensitization effectiveness of nitroimidazole compounds. A new method, combining a heuristic method and projection pursuit regression, was used to build an advanced QSAR model. Compared to the conventional multi-linear regression model, this model showed better predictive ability and reliabili...

2016
Rehana Delair Rutal Mahajan

Personality Recognition from the author’s source code is a task organized by PR-SOCO team in conjunction with the FIRE 2016 Forum for Information Retrieval Evaluation. The aim is to identify author’s personality traits from source code collection of a programmer. We have used various supervised learning approaches to train the regression model with different set of features extracted using stat...

2012
Michael Lee Branham Edward Allen Ross Thirumala Govender

A novel method for predicting maximum recommended therapeutic dose (MRTD) is presented using quantitative structure property relationships (QSPRs) and artificial neural networks (ANNs). MRTD data of 31 structurally diverse Antiretroviral drugs (ARVs) were collected from FDA MRTD Database or package inserts. Molecular property descriptors of each compound, that is, molecular mass, aqueous solubi...

2013
Miguel Marabel Flor Álvarez-Taboada

Aboveground biomass (AGB) is one of the strategic biophysical variables of interest in vegetation studies. The main objective of this study was to evaluate the Support Vector Machine (SVM) and Partial Least Squares Regression (PLSR) for estimating the AGB of grasslands from field spectrometer data and to find out which data pre-processing approach was the most suitable. The most accurate model ...

2016
Esteban Morales John Mark S. de Leon Niloufar Abdollahi Fei Yu Kouros Nouri-Mahdavi Joseph Caprioli

PURPOSE The study was conducted to evaluate threshold smoothing algorithms to enhance prediction of the rates of visual field (VF) worsening in glaucoma. METHODS We studied 798 patients with primary open-angle glaucoma and 6 or more years of follow-up who underwent 8 or more VF examinations. Thresholds at each VF location for the first 4 years or first half of the follow-up time (whichever wa...

دستورانی, محمدتقی, زرعی, محمدمهدی, عشقی زاده, مسعود, مصداقی, منصور,

Rainfall-runoff models are used in the field of hydrology and runoff estimation for many years, but despite existing numerous models, the regular release of new models shows that there is still not a model that can provide sophisticated estimations with high accuracy and performance. In order to achieve the best results, modeling and identification of factors affecting the output of the model i...

Journal: :Remote Sensing 2017
Daewon Kim Hanlim Lee Hyunkee Hong Wonei Choi Yun Gon Lee Jun-Sung Park

Surface NO2 volume mixing ratio (VMR) at a specific time (13:45 Local time) (NO2 VMRST) and monthly mean surface NO2 VMR (NO2 VMRM) are estimated for the first time using three regression models with Ozone Monitoring Instrument (OMI) data in four metropolitan cities in South Korea: Seoul, Gyeonggi, Daejeon, and Gwangju. Relationships between the surface NO2 VMR obtained from in situ measurement...

Journal: :Remote Sensing 2017
Wangfei Zhang Zengyuan Li Erxue Chen Yahong Zhang Hao Yang Lei Zhao Yongjie Ji

Growth parameters like biomass, leaf area index (LAI) and stem height play an import role for crop monitoring and yield prediction. Compact polarimetric (CP) SAR has shown great potential and similar performance to fully-polarimetric (FP) SAR in crop mapping and phenology retrieval, but its potential in growth parameters inversion has not been fully explored. In this paper, a time series of ima...

2016
Zhaoxuan Li SM Mahbobur Rahman Rolando Vega Bing Dong Guido Carpinelli

We evaluate and compare two common methods, artificial neural networks (ANN) and support vector regression (SVR), for predicting energy productions from a solar photovoltaic (PV) system in Florida 15 min, 1 h and 24 h ahead of time. A hierarchical approach is proposed based on the machine learning algorithms tested. The production data used in this work corresponds to 15 min averaged power meas...

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