Hadi Sadoghi Yazdi

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Classifying non-stationary and imbalanced data streams encompasses two important challenges, namely concept drift and class imbalance. ''Concept drift'' (or non-stationarity) is changes in the underlying function being learnt, and class imbalance is vast difference between the numbers of instances in different classes of data. Class imbalance is an obstacle(More)
Falls are a major health hazard for the elderly and a serious obstacle for independent living. Since falling causes dramatic physical-psychological consequences, development of intelligent video surveillance systems is so important due to providing safe environments. To this end, this paper proposes a novel approach for human fall detection based on(More)
This paper presents an alternative and efficient method for solving a class of constraint parametric optimization problems using particle swarm optimization algorithm (PSO). In this paper, for the first time PSO is used for solving convex parametric programming, but PSO must be adaptive for doing it. So, for obtaining particles velocities, adaptation weight(More)
In most cases authors are permitted to post their version of the article (e.g. in Word or Tex form) to their personal website or institutional repository. Authors requiring further information regarding Elsevier's archiving and manuscript policies are encouraged to visit: Artificial neural network is a favorable technique to solve optimization problems(More)
Falls are a major health hazard for the elderly and a serious obstacle for independent living. Since falling causes dramatic physical-psychological consequences, development of intelligent video surveillance systems is so important due to providing safe environments. To this end, this paper proposes a novel approach for human fall detection based on(More)
Genetic Algorithm approaches. First, twenty two features from electrocardiogram signal are extracted. These features are obtained semiautomatically from time-voltage of R, S, T, P, Q features of an Electro Cardiagram signals. Genetic algorithm is used to improve the generalization performance of the SVM classifier. In order to do this, the design of the SVM(More)
Concept drift (non-stationarity) and class imbalance are two important challenges for supervised classifiers. " Concept drift " (or non-stationarity) refers to changes in the underlying function being learnt, and class imbalance is a vast difference between the numbers of instances in different classes of data. Class imbalance is an obstacle for the(More)
Keywords: Unsupervised learning Kernel least mean square Ordinary differential equation Neuro-fuzzy approach a b s t r a c t In this paper a novel method is introduced based on the use of an unsupervised version of kernel least mean square (KLMS) algorithm for solving ordinary differential equations (ODEs). The algorithm is unsupervised because here no(More)