Mobile Tracking Based on Support Vector Regressors Ensemble and Game Theory
نویسندگان
چکیده
منابع مشابه
Ensemble Kernel Learning Model for Prediction of Time Series Based on the Support Vector Regression and Meta Heuristic Search
In this paper, a method for predicting time series is presented. Time series prediction is a process which predicted future system values based on information obtained from past and present data points. Time series prediction models are widely used in various fields of engineering, economics, etc. The main purpose of using different models for time series prediction is to make the forecast with...
متن کاملActive set training of support vector regressors
In our previous work we have discussed the training method of a support vector classifier by active set training allowing the solution to be infeasible during training. In this paper, we extend this method to training a support vector regressor (SVR). We use the dual form of the SVR where variables take real values and in the objective function the weighted linear sum of absolute values of the ...
متن کاملModeling Pricing Strategies Using Game Theory and Support Vector Machines
Data Mining is a widely used discipline with methods that are heavily supported by statistical theory. Game theory, instead, develops models with solid economical foundations but with low applicability in companies so far. This work attempts to unify both approaches, presenting a model of price competition in the credit industry. Based on game theory and sustained by the robustness of Support V...
متن کاملConstructing support vector machine ensemble
Even the support vector machine (SVM) has been proposed to provide a good generalization performance, the classi6cation result of the practically implemented SVM is often far from the theoretically expected level because their implementations are based on the approximated algorithms due to the high complexity of time and space. To improve the limited classi6cation performance of the real SVM, w...
متن کاملPredicting cardiac arrhythmia on ECG signal using an ensemble of optimal multicore support vector machines
The use of artificial intelligence in the process of diagnosing heart disease has been considered by researchers for many years. In this paper, an efficient method for selecting appropriate features extracted from electrocardiogram (ECG) signals, based on a genetic algorithm for use in an ensemble multi-kernel support vector machine classifiers, each of which is based on an optimized genetic al...
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: International Journal of Distributed Sensor Networks
سال: 2014
ISSN: 1550-1477,1550-1477
DOI: 10.1155/2014/403927