Aiming at poor adaptability to illumination variation and single learning rate in traditional Gaussian mixture model, an improved moving object detection algorithm based on adaptive Gaussian mixture model is proposed in this paper, so as to achieve the goal of a self-adaptive background updating model. In this paper, we analyze the existed algorithms and put forward the method to make use of co...

In this paper, novel techniques in increasing the accuracy and speed of convergence of a Feed forward Back propagation Artificial Neural Network (FFBPNN) with polynomial activation function reported in literature is presented. These technique was subsequently used to determine the coefficients of Autoregressive Moving Average (ARMA) and Autoregressive (AR) system. The results obtained by introd...

This work proposes a novel strategy for social learning by introducing the critical feature of adaptation. In learning, several distributed agents update continually their belief about phenomenon interest through: i) direct observation streaming data that they gather locally; and ii) diffusion beliefs through local cooperation with neighbors. Traditional implementations are known to learn well ...

The feature map represented by the set of weight vectors of the basic SOM (Self-Organizing Map) provides a good approximation to the input space from which the sample vectors come. But the timedecreasing learning rate and neighborhood function of the basic SOM algorithm reduce its capability to adapt weights for a varied environment. In dealing with non-stationary input distributions and changi...

HTTP Adaptive Streaming (HAS) is the de-facto solution for video delivery over Internet. In HAS, each encoded at multiple quality levels and resolutions (i.e., representations) to enable adaptation of streaming session viewing network conditions client. This requirement brings encoding challenges along with it, e.g., a source should be efficiently bitrates resolutions. Fast multi-rate approache...

The present research aimed to analyze instructional design,workplace learning, and selecting the optimum model of learning for human resources training in petrochemical industry.The previous roles have become faint and new opportunities have appeared in petrochemical industry by starting the process of privatization and changing the nature of the company from holding to a governance and develop...

This paper offers a fuzzy balance management scheme between exploration and exploitation, which can be implemented in any critic-only fuzzy reinforcement learning method. The paper, however, focuses on a newly developed continuous reinforcement learning method, called fuzzy Sarsa learning (FSL) due to its advantages. Establishing balance greatly depends on the accuracy of action value function ...

The basic idea of this paper is to increase the learning rate of a artificial neural network without affecting the accuracy of the system. The new algorithms for dynamically reducing the number of input samples presented to the ANN (Artificial Neural Network) are given thus increasing the rate of learning. This method is called as Adaptive skipping. This can be used along with any supervised Le...