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In recent years, piecewise linearization has developed as an attractive tool for the representation of various complex nonlinear systems. The piecewise linearization of individual functions provide a platform for the piecewise affine approximation of nonlinear systems containing a large number of scaler valued nonlinear functions. Inspite of the wide application of piecewise linearization, the optimal...
Problems with hybrid indices are common, but the performance of previous methods in solving these problems needs to be further improved. We propose an adaptive evolutionary optimization algorithm of solving the above problems effectively in this study. First, the convergence rate of a population is calculated based on the distance between the optimal individuals with adjacent generations; then the...
The cooling system is one of the most important systems in a plastic injection mould. It affects the quality and productivity of the molded part. In this paper, we extend our previous research on the automatic plastic injection cooling system layout design to multiple inlet and outlet systems, and propose an evolutionary approach with ad hoc operators to concurrently optimize the topological connection...
A two-step identification method for nonlinear polynomial model using Evolutionary Algorithm (EA) is proposed in this paper, and the method has the ability to select a parsimonious structure from a very large pool of model terms. In a nonlinear polynomial model, the number of candidate monomial terms increases drastically as the order of polynomial model increases, and it is impossible to obtain the...
In this paper, we apply an evolutionary optimization classifier, referred to as genetic algorithm-based multiple classifier (GaMC), to the long-range contacts prediction. As a result, about 44.1% contacts between long-range residues (with a sequence separation of at least 24 amino acids) are founded around the sequence profile (SP) centre when evaluating the top L/5 (L is the sequence length of protein)...
The use of distributed generators (DGs), especially renewables like wind and solar photovoltaics, depends upon inverter technology to provide compatibility between multiple DGs on a local bus. It is becoming more common to group dissimilar DGs together to form microgrids, and desirable to allow DGs to be connected or disconnected without detrimental effects upon the stability of the microgrid. This...
Traditional methods using for the design of tobacco leaf groups blending depend mostly on expert experiences. But they are lack control of the product quality and proved inefficient in practice. In this paper, we use the modified GA and PSO algorithms to help to optimize the leaf groups. The experimental results demonstrated that the modified GA and PSO algorithms are faster and more accurate when...
In this paper, the authors propose a new evolutionary optimization i.e. synchronous bacterial foraging optimization (SBFO). The SBFO can be used for optimization of multimodal and high dimensional functions. It also enhances computational throughput and global search capability. The convergence of original BFO to the optimum value is very slow and its performance is also heavily affected with increased...
Much of the computational complexity in employing evolutionary algorithms as optimization tool is due to the fitness function evaluation that may either not exist or be computationally very expensive. With the proposed approach, the expensive fitness evaluation step is replaced by an approximate model. An intelligent guided technique via an adaptive fuzzy similarity analysis for fitness granulation...
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