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The load saturation estimation helps to quantify the final load consumption of a given area, and avoid unnecessary investment to the transmission and distribution facilities. There are generally two methods to estimate the saturated load, based on the load curve and the spacial load distribution respectively. With the historical load instead of load classification data, the Logistic curve, i.e. the...
Genetic algorithm is suitable for the complex and non-linear problem that can not be solved by traditional method, which has been widely used in many areas, and it will become one of main techniques in intelligent computation. This article takes the dynamic series of number of printed books in during several years as example, discussing modeling method of succession forecast model based on GA and...
Distribution demand forecast is one of the core of the logistics system planning. In this paper, to forecast distribution demand, a Grey Markov Model is presented by means of combining Grey system theory with dispersed Markov Chains theory. The model overcomes the influence of random fluctuation data on forecasting precision and widens the application scope of the grey forecasting. Results show that...
Combination prediction is an effective method to improve prediction precision for logistics demand. On the basis of least square support vector machine (LS-SVM), a combination prediction model for logistics demand is proposed. Firstly, according to the historical data of logistics demand, grey model (GM), auto regression moving average (ARMA) model and polynomial prediction model are established respectively...
In this paper, we present a scheme of steganalysis of JPEG images with the use of polynomial fitting and computational intelligence techniques. Based on the Generalized Gaussian Distribution (GGD) model in the quantized DCT coefficients, the errors between the logarithmic domain of the histogram of the DCT coefficients and the polynomial fitting are extracted as features to detect the adulterated...
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