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In this study we explore the feasibility of applying Artificial Neural Networks (ANN) and Support Vector Machines (SVM) to the prediction of incipient power transformer faults. A clonal selection algorithm (CSA) is introduced for the first time in the literature to select optimal input features and RBF kernel parameters. CSA is shown to be capable of improving the speed and accuracy of classification...
The calorific value of coal is an important factor for the economic operation of coal fired power plant. However calorific value is tremendous difference between the different coal, and even if coal is from the same mine. Restricted by the coal market, most of coal fired power plants can not burn the designed-coal by now in China. The properties of coal as received are changing so frequently that...
The calorific value of coal is an important factor for the economic operation of coal fired power plant. However calorific value is tremendous difference between the different coal, and even if coal is from the same mine. Restricted by the coal market, most of coal fired power plants can not burn the designed-coal by now in China. The properties of coal as received are changing so frequently that...
Reconstructing meshes from 3D medical images is an important but complicated task, which provides a fundamental data structure for bio-medical applications. In this paper, a novel and easily implemental solution is proposed. Instead of following the popular methods, we sample on the medical images with centroidal Voronoi tessellations, and then build the Delaunay mesh from the sampled points directly...
The ground resistance, the ground potential rise, touches and step voltages are the basic design quantities of the grounding grids. Such quantities greatly depend on the safety of grounding system. The aim being pursued is to minimize these mentioned quantities, while the safety restrictions required by the standard regulations are met. The innovative aspect of the proposed approach is the influences...
This paper presents the optimization and implementation of a relaxed dynamic programming (RDP) algorithm to generate a daily control scheduling for optimal or near-optimal air conditioner loads (ACLs). The conventional control mode for ACL includes demand control, cycling control, and timer control, to assist customers for saving electricity costs. The proposed load control scheduler (LCS) scheme...
We study the problem of dynamically scheduling a set of period stage control tasks controlling a set of large air conditioner loads (ACLs). To be able to solve the scheduling problem for realistic on-line cases, we utilize the technique of relaxed dynamic programming (RDP) algorithm to generate an optimal or near optimal daily control scheduling for ACLs with relaxing bounds. Field tests of controlling...
This paper addresses the problem of optimal settings of reactive power compensation and bus voltage regulation. To be able to solve the problem for real-world cases, the artificial immune algorithm (AIA) technique is used to generate an optimal or near-optimal control strategy for reactive power compensation and bus voltage regulation. Two real-world cases are tested to demonstrate the effectiveness...
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