An improved algorithm is developed based on support vector regression (SVR) to estimate horizonal water vapor transport integrated through the depth of the atmosphere (Θ) over the global ocean from observations of surface wind-stress vector by QuikSCAT, cloud drift wind vector derived from the Multi-angle Imaging SpectroRadiometer (MISR) and geostationary satellites, and precipitable water from...

This paper uses support vector regression (SVR) to predict short-term traffic flow, and studies the feasibility of SVR in flow prediction. The short-time has many influencing factors, which are characterized by nonlinearity, randomness periodicity. Therefore, algorithm advantages dealing with such problems. In order improve prediction accuracy SVR, this genetic (GA) optimize other parameters ob...

Budgeting planning plays an important role in coordinating activities in organizations. An accurate sales volume forecasting is the key to the entire budgeting process. All of the other parts of the master budget are dependent on the sales volume forecasting in some way. If the sales volume forecasting is sloppily done, then the rest of the budgeting process is largely a waste of time. Therefor...

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In this paper, robust fuzzy neural networks (FNNs) are proposed to identify chaotic systems. In the proposed FNNs, integrating support vector regression (SVR) and annealing robust time-varying learning algorithm (ARTVLA) is adopted to optimize the structure of neural networks. In the evolutionary procedure, first, SVR is adopted to determine the number of hidden layer nodes and the initial stru...

This paper presents dynamic available transfer capability (DATC) determination in power system restructuring environment using support vector regression (SVR). Dynamic available transfer capability is first determined based on the conventional method of potential energy boundary surface transient energy function. Simulations were carried out on a WSCC 3-machine 9-bus system and a Practical Sout...

This paper demonstrates different types support vector regression (SVR) for annealing robust fuzzy neural networks (ARFNNs) to identification of nonlinear magneto-rheological (MR) damper with outliers. A SVR has the good performances to determine the number of rule in the simplified fuzzy inference system and initial weights for the fuzzy neural networks. In this paper, we independently propose...

A reinforcement learning algorithm is proposed to improve the accuracy of short-term load forecasting (STLF) in this article. The proposed model integrates radial basis function neural network (RBFNN), support vector regression (SVR), and adaptive annealing learning algorithm (AALA). In the proposed methodology, firstly, the initial structure of RBFNN is determined by using an SVR. Then, an AAL...