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Biogeography-based optimization (BBO) is a new biogeography inspired algorithm for global optimization, which has shown impressive performance on many popular benchmarks. However, there are still some open research aspects that need to be addressed for BBO. In this paper, we extend the original BBO to iCPBBOCO algorithm (an improved Cosine-Probability chaotic BBO). Furthermore, in order to further...
MicroRNAs (miRNAs) are a class of small non-coding RNAs, which play key roles in gene regulation. Previous studies have revealed that they are likely to work together to regulate their common target genes. Discovery of the underlying combinatorial regulation between miRNAs and genes can provide useful information for understanding their functions as well as their close relevance to cancer. In this...
Accurate forecasting of some economic indicators such as GDP is very useful. Aiming at the problem of modeling and forecasting of the nonlinear and complex economic system, an improved least square support machine model is proposed in this paper. A multi-scale chaotic search algorithm combined with GA is proposed for the optimum selection of model parameters. Time series data of the indicator to be...
Biological wastewater treatment is a nonlinear, time-varying and time-delay process. It is difficult to achieve precise control. In order to solve the instability problem of dissolved oxygen (DO) control, a method of DO generic model control (GMC) based on immune optimization least squares support vector machine (LS-SVM) is proposed. The method doesn't require model simplification and linearization...
With respect to the existing problems of artificial neural network (ANN) methods for economic modeling and forecasting, an adaptive ANN algorithm is proposed after a brief introduction to the features of macroeconomic system. The training data set of the ANN was enlarged by using a chain style data recombination method first. Then the increasing rates of the input items and the so called time window...
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