نتایج جستجو برای: support vector machine model
تعداد نتایج: 2899838 فیلتر نتایج به سال:
In this paper, we present a methodology for combining acoustic-phonetic knowledge with statistical learning for automatic segmentation and classification of continuous speech. At present we focus on the recognition of broad classes vowel, stop, fricative, sonorant consonant and silence. Judicious use is made of 13 knowledge-based acoustic parameters (APs) and support vector machines (SVMs). It ...
We present a novel classification method for splice sites prediction using support vector machine (SVM). The method first represents input sequences by sequence-based features, including the information of the distribution of tri-nucleotides and the conserved features surrounding the splice sites characterized by Markov model. An F-score based feature selection method is then used to select inf...
Accurate simulation runoff process can have a significant role in water resources management and related issues. The inherent complexity of this process makes difficult the use of physical and numerical models. In recent years, application of intelligent models is increased a powerful tool in hydrological modeling. The aim of this study was the application of the Gamma test to select the optim...
Human action recognition is a task of analyzing human action that occurs in a video. This paper investigates action recognition by using two classification techniques, namely Relevance Vector Machine (RVM) and Support Vector Machine (SVM). SVM is a technique for supervised classification that used in statistics and machine learning. By separating the distinct class with a maximum possible wide ...
Abstract—the purpose of this paper is to compare two artificial intelligence algorithms for forecasting supply chain demand. In first step data are prepared for entering into forecasting models. In next step, the modeling step, an artificial neural network and support vector machine is presented. The structure of artificial neural network is selected based on previous researchers' results. For ...
Article history: Received 1 November 2011 Received in revised form 1 January 2013 Accepted 3 February 2013 Available online 20 February 2013
Porosity is considered as an important petrophysical parameter in characterizing reservoirs, calculating in-situ oil reserves, and production evaluation. Nowadays, using intelligent techniques has become a popular method for porosity estimation. Support vector machine (SVM) a new intelligent method with a great generalization potential of modeling non-linear relationships has been introduced fo...
Rainfall and runoff estimation play a fundamental and effective role in the management and proper operation of the watershed, dams and reservoirs management, minimizing the damage caused by floods and droughts, and water resources management. The optimal performance of intelligent models has increased their use to predict various hydrological phenomena. Therefore, in this study, two intelligent...
The importance of supplier selection is nowadays highlighted more than ever as companies have realized that efficient supplier selection can significantly improve the performance of their supply chain. In this paper, an integrated model that applies Data Envelopment Analysis (DEA) and Support Vector Machine (SVM) is developed to select efficient suppliers based on their predicted efficiency sco...
Support Vector Machines (SVMs) have become a popular classification tool. Because of their theoretical robustness they offer improvements in pattern classification applications. This paper describes an approach of producing a N-best list of hypotheses for the needs of phoneme recognition, using a Least Squares Support Vector Machine classifier (LS-SVM) and generate the corresponding N-best list...
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