A differentialevolution (DE) algorithm for determining 16 advanced turning model parameters of a 1.2 million industrial fluid catalytic cracking (FCC) unit modeling by HYSYS 8.4 is presented. Industrial data from a C...
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A differentialevolution (DE) algorithm for determining 16 advanced turning model parameters of a 1.2 million industrial fluid catalytic cracking (FCC) unit modeling by HYSYS 8.4 is presented. Industrial data from a Chinese petroleum refinery were used to develop, train and check the model. Due to FCC complexity, the proposed model is capable of predicting the yield of products based on main operating conditions. The optimized FCC model is used for further optimized analysis of the FCC unit operating conditions based on the maximum of economic benefits. Prediction of the economic benefit of FCC unit increases 917 yuan/h at the optimized operating conditions.
In this work, a novel identification method based on differential evolution algorithm has been applied to bilinear systems and its performance has been compared to that of genetic algorithm. Box Jenkins system and dif...
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In this work, a novel identification method based on differential evolution algorithm has been applied to bilinear systems and its performance has been compared to that of genetic algorithm. Box Jenkins system and different type bilinear systems have been identified using differentialevolution and genetic algorithms. The simulation results have shown that bilinear systems can be successfully and efficiently identified using these algorithms.
In this paper, we present a new morphology-based homomorphic filtering technique for feature enhancement in medical images. The proposed method is based on decomposing an image into morphological subbands. The homomor...
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In this paper, we present a new morphology-based homomorphic filtering technique for feature enhancement in medical images. The proposed method is based on decomposing an image into morphological subbands. The homomorphic filtering is performed using the morphological subbands. The differential evolution algorithm is applied to find an optimal gain and structuring element for each subband. Simulations show that the proposed filter improves the contrast of the features in medical images.
In this paper, a new adaptive differential evolution algorithm ( ADEA) is proposed for multiobjective optimization problems. In ADEA, the variable parameter F based on the number of the current Pareto-front and the di...
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In this paper, a new adaptive differential evolution algorithm ( ADEA) is proposed for multiobjective optimization problems. In ADEA, the variable parameter F based on the number of the current Pareto-front and the diversity of the current solutions is given for adjusting search size in every generation to find Pareto solutions in mutation operator, and the select operator combines the advantages of DE with the mechanisms of Pareto-based ranking and crowding distance sorting. ADEA is implemented on five classical multiobjective problems, the results illustrate that ADEA efficiently achieves two goals of multiobjective optimization problems:find the solutions converge to the true Pareto-front and uniform spread along the front. (c) 2008 Elsevier Inc. All rights reserved.
Since the concept of discrete memristor was proposed, more and more scholars began to study this topic. At present, most of works on the discrete memristor are devoted to the mathematical modeling and digital circuit ...
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Since the concept of discrete memristor was proposed, more and more scholars began to study this topic. At present, most of works on the discrete memristor are devoted to the mathematical modeling and digital circuit implementation, but the research on its synchronization control has not received much attention. This paper focuses on the parameter identification for the discrete memristive chaotic map, and a modified intelligent optimization algorithm named adaptive differential evolution algorithm is proposed. To deal with the complex behaviors of hyperchaos and coexisting attractors of the considered discrete memristive chaotic maps, the identification objective function adopts two special parts: time sequences and return maps. Numerical simulations demonstrate that the proposed algorithm has the best performance among six existing algorithms, and it can still accurately identify the parameters of the original system under noise interference.
In the present day, design of engineering systems appears as a line of research of great interest due the many applications that can be found in different areas of science and engineering. In this setting, design of i...
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In the present day, design of engineering systems appears as a line of research of great interest due the many applications that can be found in different areas of science and engineering. In this setting, design of induction motor, whose functions base are induce alternating currents in the rotor circuit, by the magnetic field rotating produced the stator coils, appears as an interesting theme research already which is directly related to manufacturing costs motors. In this context, this work aims the design of a three-phase induction motor using the differential evolution algorithm. For this purpose considered minimizing loss and cost on motor by determining the geometric variables vector characterizing the model mathematical presented. To solve these problems is used the MODE algorithm (Multiobjective Optimization differentialevolution) and the outcome is compared to the NSGA II algorithm (Non-dominated Sorting Genetic algorithm II).
In this paper,we consider the knot placement problem in B-spline curve approximation.A novel two-stage framework is proposed for addressing this *** the first step,the l_(∞,1)-norm model is introduced for the sparse ...
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In this paper,we consider the knot placement problem in B-spline curve approximation.A novel two-stage framework is proposed for addressing this *** the first step,the l_(∞,1)-norm model is introduced for the sparse selection of candidate knots from an initial knot *** this step,the knot number is *** the second step,knot positions are formulated into a nonlinear optimization problem and optimized by a global optimization algorithm—the differential evolution algorithm(DE).The candidate knots selected in the first step are served for initial values of the DE *** the candidate knots provide a good guess of knot positions,the DE algorithm can quickly *** advantage of the proposed algorithm is that the knot number and knot positions are determined *** with the current existing algorithms,the proposed algorithm finds approximations with smaller fitting error when the knot number is fixed in ***,the proposed algorithm is robust to noisy data and can handle with few data *** illustrate with some examples and applications.
In this paper, a type-2 fuzzy logic power system stabilizer with differential evolution algorithm is proposed. As an extension of type-1 fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the contro...
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In this paper, a type-2 fuzzy logic power system stabilizer with differential evolution algorithm is proposed. As an extension of type-1 fuzzy logic theory, type-2 fuzzy logic theory can effectively improve the control performance by uncertainty of membership function especially when we have to confront with less expert knowledge or unpredicted external disturbances. The corresponding parameters and rule base of type-2 fuzzy logic power system stabilizer are optimally tuned by using differential evolution algorithm for multi-machine power system. Through simulation under different operational conditions, the results demonstrate the effectiveness of the proposed approach for damping the power system electromechanical oscillations. (C) 2014 Elsevier Ltd. All rights reserved.
In this paper, the mathematical model of Vehicle Routing Problem with Time Windows (VRPTW) is established based on the directed graph, and a 3-stage multi-modal multi-objective differential evolution algorithm (3S-MMD...
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In this paper, the mathematical model of Vehicle Routing Problem with Time Windows (VRPTW) is established based on the directed graph, and a 3-stage multi-modal multi-objective differential evolution algorithm (3S-MMDEA) is proposed. In the first stage, in order to expand the range of individuals to be selected, a generalized opposition-based learning (GOBL) strategy is used to generate a reverse population. In the second stage, a search strategy of reachable distribution area is proposed, which divides the population with the selected individual as the center point to improve the convergence of the solution set. In the third stage, an improved individual variation strategy is proposed to legalize the mutant individuals, so that the individual after variation still falls within the range of the population, further improving the diversity of individuals to ensure the diversity of the solution set. Based on the synergy of the above three stages of strategies, the diversity of individuals is ensured, so as to improve the diversity of solution sets, and multiple equivalent optimal paths are obtained to meet the planning needs of different decision-makers. Finally, the performance of the proposed method is evaluated on the standard benchmark datasets of the problem. The experimental results show that the proposed 3S-MMDEA can improve the efficiency of logistics distribution and obtain multiple equivalent optimal paths. The method achieves good performance, superior to the most advanced VRPTW solution methods, and has great potential in practical projects.
Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DG...
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Distributed generators (DGs) are defined as generators that are connected to a distribution network. The direction of the power flow and short-circuit current in a network could be changed compared with one without DGs. The conventional protective relay scheme does not meet the requirement in this emerging situation. As the number and capacity of DGs in the distribution network increase, the problem of coordinating protective relays becomes more challenging. Given this background, the protective relay coordination problem in distribution systems is investigated, with directional overcurrent relays taken as an example, and formulated as a mixed integer nonlinear programming problem. A mathematical model describing this problem is first developed, and the well-developed differential evolution algorithm is then used to solve it. Finally, a sample system is used to demonstrate the feasibility and efficiency of the developed method. Copyright (c) 2011 John Wiley & Sons, Ltd.
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