[PDF] Top 20 A hybrid least squares support vector machines and GMDH approach for river flow forecasting
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A hybrid least squares support vector machines and GMDH approach for river flow forecasting
... of forecasting models are shown in Tables 2 and ...monthly river flow time series. The training and testing data were normalized in the range zero to ... See full document
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River flow time series using least squares support vector machines
... novel hybrid forecast- ing model known as GLSSVM, which combines the group method of data handling (GMDH) and the least squares sup- port vector machine ...The GMDH is ... See full document
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Electricity load demand forecasting in Portugal using least-squares support vector machines
... tested and the Radial Basis Function Artificial Neural Network (RBF ANN) was up to now one of the most tested approaches with satisfactory ...this approach, led demand for new ways to make the prediction, ... See full document
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A Survey on Potential of the Support Vector Machines in Solving Classification and Regression Problems
... Generalizations and improvements have been recently proposed by many ...subsets and then simultaneously runs multiple CPU processors to deal with each of the partitions data ...an approach to ... See full document
12
Deformation analysis with Total Least Squares
... classical approach, transformation parameters are es- timated by the LS adjustment of the observation equations where only the observations are considered as ...classical least squares and ... See full document
7
Rev. bras. linguist. apl. vol.11 número2
... occurrence and co- occurrence frequencies come into play in human classification behavior as compared to machine ...occurs, and how often it co-occurs with other ...McClelland and Rumelhart (1981); ... See full document
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Artificial Intelligence Techniques for river flow forecasting in the Seyhan River Catchment, Turkey
... models and observations were compared and evaluated based on their performance in training and testing ...antecedent flow variables was selected as the best fit river forecasting ... See full document
38
Parallelization of multicategory support vector machines (PMC-SVM) for classifying microarray data
... We received submissions both from the presenters at the symposium as well as non-presenters. Submitted manuscripts were rigorously reviewed by at least two referees. The quality of each paper was evaluated on the ... See full document
2
A comparison of four data selection methods for artificial neural networks and support vector machines
... learning and data mining problems two basic tasks have to be considered: feature selection and instance ...output and yields improved model ...wrapper and filter ... See full document
6
Auction econometrics by least squares
... Hong and Tamer (2003) show that this is in fact true; if u is double exponential, than one can accomo- date error-in-variables in a standard method of moments procedure without validation data by adding a ... See full document
37
Partial least squares for face hashing
... results and they require twice the space requirement since the indexes of subjects that were learned with +1 target re- sponse in the PLS model need to be stored to allow them to receive the votes in the ...not ... See full document
100
Classificação automática de páginas Web Multi-label via MDL e Support Vector Machines
... por Support Vector Machines de até 7 pontos percentuais, simplesmente por marcar diferentemente as palavras provenientes dos títulos das páginas ... See full document
124
Data mining in HIV-AIDS surveillance system
... retrieve and gather knowledge from an exhaustive assem- blage of data and facts ...biomedical and health care knowledge for clinical and administrative decision making as well as generate ... See full document
15
Applying feature transformation using Relative Frequency with Power Transformation and Lemmatization in automatic Spam Filtering
... During the experiments two classifiers were used. These are k-Nearest Neighbors and Support- vector Machines. We decided to use these two methods because of the advantages with which each one ... See full document
7
A novel support vector machine-based approach for rare variant detection.
... Although common variants (CVs) that contribute to complex genetic diseases have been successfully identified from genome- wide association studies (GWAS), only a portion of heritability is explained by the identified ... See full document
9
Forecasting the Prices of TAIEX Options by Using Genetic Programming and Support Vector Regression
... the forecasting models for the prices of stock call options where the predictors comprise the six basic factors in the B-S model and the other factors, including the opening price, closing price, highest ... See full document
6
Entrepreneurship failure: is culture to blame?
... measurable and accepted as valid by most of the Scientific Community (currently there are 6 Cultural Dimensions, but Long Term Orientation ...1991 and Indulgence Versus Restraint (IVR) added on 2001 will ... See full document
60
Recursive Least Squares using sequential Givens rotations
... left), and for the long 24-hour period (at right) of orbit determination on November 19, ...mean and standard deviation, for the three models of forces considered in this analysis, and for the short ... See full document
8
A brief look at the least-squares approach as a classifier applied to restricted-vocabulary speech recognition
... the least-squares method (LSM) [1] to solve incompatible systems of linear equations (ISLE) is explored in order to create a technique for speech recognition ...input vector into a scalar ... See full document
5
An Algorithm to Solve Separable Nonlinear Least Square Problem
... The existing special algorithms for these problems are derived from the variable projections scheme proposed by Golub and Pereyra [1]. However, when the linear part of variables has some bounded constraints, the ... See full document
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