Hopf bifurcation in power systems leads to oscillatory instability, and it is desirable to operate the system with sufficiently large loading margin to Hopf bifurcation. A new technique to determine the shortest dista...
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Hopf bifurcation in power systems leads to oscillatory instability, and it is desirable to operate the system with sufficiently large loading margin to Hopf bifurcation. A new technique to determine the shortest distance to Hopf bifurcation is developed. The problem of determining the closest Hopf bifurcation point is formulated as an optimisation problem and solved using real-coded genetic algorithm. The advantage of this method is that it is capable of handling various operational constraints and can determine the closest Hopf bifurcation point accurately even if the hypersurface is not smooth. The proposed approach has been applied on two-area and IEEE 14-bus test systems. The details of implementation and simulation results are presented. The effect of load modelling on closest Hopf bifurcation point is also investigated for various loading patterns.
In this paper a new crossover operator called the double distribution crossover (DDX) is proposed. The performance of DDX is compared with existing real-coded crossover operator namely Laplace crossover (LX). DDX is u...
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ISBN:
(纸本)9789811004513;9789811004506
In this paper a new crossover operator called the double distribution crossover (DDX) is proposed. The performance of DDX is compared with existing real-coded crossover operator namely Laplace crossover (LX). DDX is used in conjunction with a well-known mutation operator;Power mutation (PM) to obtain a new generational real-coded genetic algorithm called DDX-PM. DDX-PM is compared with the existing LX-PM. The performance of both the geneticalgorithms is compared on the basis of success rate, average function evaluation, average error and computational time, and the preeminence of the proposed crossover operator is established.
This work presents an integrated real-coded genetic algorithm and particle swarm optimization with a penalty function method (RGA-PSO) to solve constrained global optimization (CGO) problems. An outer RCA is used to o...
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ISBN:
(纸本)9783642224171
This work presents an integrated real-coded genetic algorithm and particle swarm optimization with a penalty function method (RGA-PSO) to solve constrained global optimization (CGO) problems. An outer RCA is used to optimize the parameter settings of an inner PSO algorithm, which includes the constriction coefficient, cognitive parameter, social parameter, penalty parameter and mutation probability. To increase the diversity of particles, the inner PSO method uses a multi-non-uniform operator. Performance of the proposed RGA-PSO algorithm is evaluated using a set of benchmark COO problems. Additionally, this work compares the numerical results obtained using the proposed RGA-PSO algorithm with those of GAs and artificial immune algorithms (AIAs). Experimental results indicate that the proposed RGA-PSO algorithm converges to a global optimum solution to a CGO problem, and that the performance of the proposed RGA-PSO algorithm is competitive with those of GAs and AIAs. Although a hybrid method increases the complexity of an algorithm, the proposed RGA-PSO algorithm can obtain the optimum parameter settings for the inner PSO algorithm by using the outer RGA and can find a global optimum solution to a COO problem by using the inner PSO algorithm, simultaneously. Hence, the proposed RGA-PSO algorithm can be considered as an alternative stochastic global optimization method for solving CGO problems.
Dental caries is the most common infectious disease in humans, which affects 97% of the population in their lifetimes. In this article, fuzzy cognitive maps (FCMs) are applied to classify patients in terms of their pe...
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ISBN:
(纸本)9781538649169
Dental caries is the most common infectious disease in humans, which affects 97% of the population in their lifetimes. In this article, fuzzy cognitive maps (FCMs) are applied to classify patients in terms of their personal risk of dental caries. Two approaches are discussed for developing FCMs. At first, causal relations between concepts and their weights are defined based on the domain experts. Then, these causal weights are determined by means of the real-coded genetic algorithm (RCGA) and historical data, without the intervention of experts. These two FCMs have been compared by categorizing 86 sample patients into two classes: 'carious' and 'healthy'. Although the conventional FCM has successfully categorized 67.44% of the cases in correct classes, the RCGA based FCM hits the 83.72% correct classification rate. Results show the efficiency of RCGA based FCM in comparison with the conventional FCM.
Cold-formed steel portal frames are a popular form of construction for single-storey buildings of spans of up to 30 m. Such buildings typically use cold-formed steel channel-sections for the columns and rafters, with ...
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Cold-formed steel portal frames are a popular form of construction for single-storey buildings of spans of up to 30 m. Such buildings typically use cold-formed steel channel-sections for the columns and rafters, with joints formed through back-to-back gusset plates bolted to the webs of the channel-sections. For such buildings, for frames of a given topography (where the span, height, pitch and frame spacing are all known) the choice of the cold-formed steel channel-section that results in either the minimum weight or minimum cost for the building can be determined easily for a given cold-formed steel manufacturer. This is because a typical cold-formed steel manufacturer would typically only have a finite number of discrete sections in their catalogue, and so in conjunction with frame analysis and design member checks, all the different permutations of sections can be considered. However, it is well-known that the minimum weight or minimum cost of a frame will not necessarily yield the most economical solution of the whole of building. In this paper, a study is conducted to investigate effects of frame topography on either the frame weight or cost per meter length of building. Thereafter, an optimization technique that uses a real-coded genetic algorithm is applied to search for the optimum topography of steel portal frame for a building. The advantage of using a real-coded genetic algorithm is that a high precision optimum solution can be achieved easily when the optimization process works in the continuous search space. The result of a parametric study that investigates the effect of typical wind zones in Australia on the optimum parameters of building geometry is presented.
In this paper, a novel and efficient real-coded genetic algorithm (RCGA) for process optimization is developed. The proposed RCGA is equipped with Ranking Selection (RS), Direction-Based Crossover (DBX) and Dynamic Ra...
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ISBN:
(纸本)9781424478354
In this paper, a novel and efficient real-coded genetic algorithm (RCGA) for process optimization is developed. The proposed RCGA is equipped with Ranking Selection (RS), Direction-Based Crossover (DBX) and Dynamic Random Mutation (DRM) operators. The RS operator is used to eliminate the bad solutions and reproduce good solutions, making the whole population to achieve a better average fitness. The DBX operator uses relative fitness information to direct the crossover toward a direction that significantly improves the objective fitness. The DRM operator prevents the premature convergence of RCGA and at the same time increases the precision of the searched solution. The effectiveness and application of the proposed RCGA are demonstrated through a variety of single-objective optimization benchmark problems. For comparative study, other existing RCGAs with different evolution operators are also performed to the same problem set. Extensive experiment results reveal that the proposed RCGA provides a significantly faster convergence speed and much better search performance than comparative methods.
Cold-formed steel portal frames are a popular form of construction for single-storey buildings of spans of up to 30 m. Such buildings typically use cold-formed steel channel-sections for the columns and rafters, with ...
详细信息
Cold-formed steel portal frames are a popular form of construction for single-storey buildings of spans of up to 30 m. Such buildings typically use cold-formed steel channel-sections for the columns and rafters, with joints formed through back-to-back gusset plates bolted to the webs of the channel-sections. For such buildings, for frames of a given topography (where the span, height, pitch and frame spacing are all known) the choice of the cold-formed steel channel-section that results in either the minimum weight or minimum cost for the building can be determined easily for a given cold-formed steel manufacturer. This is because a typical cold-formed steel manufacturer would typically only have a finite number of discrete sections in their catalogue, and so in conjunction with frame analysis and design member checks, all the different permutations of sections can be considered. However, it is well-known that the minimum weight or minimum cost of a frame will not necessarily yield the most economical solution of the whole of building. In this paper, a study is conducted to investigate effects of frame topography on either the frame weight or cost per meter length of building. Thereafter, an optimization technique that uses a real-coded genetic algorithm is applied to search for the optimum topography of steel portal frame for a building. The advantage of using a realcodedgeneticalgorithm is that a high precision optimum solution can be achieved easily when the optimization process works in the continuous search space. The result of a parametric study that investigates the effect of typical wind zones in Australia on the optimum parameters of building geometry is presented.
In this study, new infinite impulse response (IIR) digital differentiators of second, third and fourth orders based on optimising the L-1-error fitness function using the bat algorithm (BA) are proposed. The coefficie...
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In this study, new infinite impulse response (IIR) digital differentiators of second, third and fourth orders based on optimising the L-1-error fitness function using the bat algorithm (BA) are proposed. The coefficients of numerator and denominator of the differentiators are computed by minimising the L-1-norm of the error fitness function along with imposing the constraint for the location of poles and zeros within the unit circle to ensure minimum phase. The transfer function of the differentiators are inverted and transformed into the digital integrators of the same orders. The results obtained for the solutions by the proposed L-1-based BA (L-1-BA) are superior to the designs using other techniques such as particle swarm optimisation and real-coded genetic algorithm. The designed optimal differentiator and integrator are compared with the existing models and are found to be of high accuracy and flatness in a wide frequency range along with minimum absolute magnitude error. The mean relative error (dB) is obtained as low as -67dB and -73dB for the proposed differentiators and integrators, respectively.
In steel portal frames, cold-formed steel channel sections are increasingly used as the primary framing components, in addition to the secondary members e.g. purlins and side rails. For such framing systems, the stiff...
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In steel portal frames, cold-formed steel channel sections are increasingly used as the primary framing components, in addition to the secondary members e.g. purlins and side rails. For such framing systems, the stiffness of the joints at the eaves and apex affects the bending moment distribution, as well as the frame deflections. This paper investigates the influence of two joint configurations having full rigidity and semi-rigidity, respectively, on the optimum design of cold-formed steel portal frames. A real-coded genetic algorithm is used to search for the most cost-effective design. It is shown that through incorporating joint effects explicitly into the design process, a more appropriate balance between the joints and the member properties can be obtained, thus optimizing material use. The study then investigates the effect of secondary members on the optimum design. It is shown that incorporating the secondary members is important for portal frames having spans shorter than 12 m. For example, for a frame spacing less than 6 m, the material cost of the primary members can be reduced by up to 15%.
In this paper, a modified backpropagation neural network is combined with a chaos-search geneticalgorithm and simulated annealing algorithm for very short term electrical energy demand prediction in deregulated power...
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In this paper, a modified backpropagation neural network is combined with a chaos-search geneticalgorithm and simulated annealing algorithm for very short term electrical energy demand prediction in deregulated power industry. Multiple modifications are carried out on the conventional backpropagation algorithm such as improvements in the momentum factor and adaptive learning rate. In the hybrid scheme, the initial parameters of the modified neural network are optimized by using the global search ability of geneticalgorithm, improved by cat chaotic mapping to enrich its optimization capability. The solution set provided by the optimized geneticalgorithm is further improved by using the strong local search ability of simulated annealing algorithm. The real data of New South Wales, Australian grid, is used in the experimentation for 1-h-ahead forecast with an emphasis on data analysis and preprocessing framework. The correlation analysis is used for the identification and selection of the most influential input variables. The simulation results reveal that the proposed combination technique effectively enhanced the prediction accuracy as compared to the available conventional methods. The prediction of 1-h-ahead load demand is critically important for decision-making response of the modern smart grid system. The acceptable precision of the proposed model concludes that it can be applied in the smart grid to enhance its demand responsiveness and other intelligent features.
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