This paper presents a wire antenna for multi-band WLAN application, designed using the Structure-Based evolutionary programming, and having a very simple geometry. The antenna has been analysed with NEC-2 during the e...
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ISBN:
(纸本)9781467322331
This paper presents a wire antenna for multi-band WLAN application, designed using the Structure-Based evolutionary programming, and having a very simple geometry. The antenna has been analysed with NEC-2 during the evolutionary process, and the outcome of the procedure shows a very good performance, with a -10dB bandwidth that covers the required frequencies for multi-band WLAN applications (2.4/5.2/5.8 GHz) and beyond, and an end-fire gain greater than 11 dB.
This paper proposes an algorithm to determine the optimal bidding parameters for aday-ahead energy market. The algorithm is developed from the viewpoint of the generation company, which has two main objectives. The fi...
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This paper proposes an algorithm to determine the optimal bidding parameters for aday-ahead energy market. The algorithm is developed from the viewpoint of the generation company, which has two main objectives. The first objective is to maximize profit while the second objective is to reduce the risk that is induced by the uncertain information. The energy market based clearing price auction will be considered in this paper. The uncertainties of rivals' bidding parameters and forecasted demand are represented using triangular fuzzy number. The evolutionary programming is applied to solve this optimization problem and the results are compared with those obtained from deterministic approach.
This paper presents both application and comparison of the metaheuristic techniques to multi-area economic dispatch(MAED)problem with tie line constraints considering transmission losses,multiple fuels,valve-point loa...
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This paper presents both application and comparison of the metaheuristic techniques to multi-area economic dispatch(MAED)problem with tie line constraints considering transmission losses,multiple fuels,valve-point loading and prohibited operating *** metaheuristic techniques such as differential evolution,evolutionary programming,genetic algorithm and simulated annealing are applied to solve MAED *** metaheuristic techniques for MAED problem are evaluated on three different test systems,both small and large,involving varying degree of complexity and the results are compared against each other.
A hybrid algorithm to design the multi layer feedforward neural network was proposed. evolutionary programming is used to design the network that makes the training process tending to global optima. Artificial immunol...
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A hybrid algorithm to design the multi layer feedforward neural network was proposed. evolutionary programming is used to design the network that makes the training process tending to global optima. Artificial immunology combined with simulated annealing algorithm is used to specify the initial weight vectors, therefore improves the probabiligy of training algorithm to converge to global optima. The applications of the neural network in the modulation style recognition of analog modulated rader signals demonstrate the good performance of the network.
This paper presents an Improved Particle Swarm Optimization (IPSO) to solve the Economic Dispatch (ED) problem with line flow constraints, bus voltage limits and generator operating constraints. In the proposed IPSO m...
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This paper presents an Improved Particle Swarm Optimization (IPSO) to solve the Economic Dispatch (ED) problem with line flow constraints, bus voltage limits and generator operating constraints. In the proposed IPSO method, a new velocity strategy equation is formulated suitable for large scale system and the features of the Constriction Factor Approach (CFA) are also incorporated into the proposed approach. Different evolutionary programming (EP) techniques such as Classical EP (CEP), Fast-EP (FEP) and Mean of Classical and Fast EP (MFEP) have different features and their combination with PSO may become more effective to find the optimal solution. Combining the advantages of CEP, FEP and MFEP in the PSO method called hybrid PSO. The proposed approach compares the results obtained from hybrid PSO, Conventional Particle Swarm Optimization (PSO), evolutionary programming (EP) techniques such as CEP, FEP and MFEP. In this paper, the proposed IPSO, hybrid PSO, PSO and EP techniques such as CEP, FEP, MFEP methods have been tested on IEEE-14, 30, 118-bus and also on 66-bus Indian utility system. Results show that the proposed method is very competent in solving ED problem in comparison with other existing methods.
A number of applications use DNA as a storage mechanism. Because processes in these applications may cause errors in the data, the information must be encoded as one of a chosen set of words that are well separated fr...
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A number of applications use DNA as a storage mechanism. Because processes in these applications may cause errors in the data, the information must be encoded as one of a chosen set of words that are well separated from one another - a DNA error-correcting code. Typically, the types of errors that may occur include insertions, deletions and substitutions of symbols, making the edit metric the most suitable choice to measure the distance between strings. Decoding, the process of recovering the original word when errors occur, is complicated by biological restrictions combined with a high cost to calculate edit *** effect machines (SEMs), an extension of finite state machines, can provide efficient decoding algorithms for such codes. Several codes of varying lengths are used to study the effectiveness of evolutionary programming (EP) as a general approach for finding SEMs for edit metric decoding. Two classification methods (direct and fuzzy classification) are compared, and different EP settings are examined to observe how decoding accuracy is affected. Regardless of code length, the best results are found using fuzzy classification. The best accuracy is seen for codes of length 10, for which a maximum accuracy of up to 99.4% is achieved for distance 1 and distance 2 and 3 achieve up to 97.1% and 85.9%, respectively. Additionally, the SEMs are examined for potential bloat by comparing the number of reachable states against the total number of states. Bloat is seen more in larger machines than in smaller machines. Furthermore, the results are analysed to find potential trends and relationships among the parameters, with the most consistent trend being that, when allowed, the longer codes generally show a propensity for larger machines.
The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be ...
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The decomposition of high-dimensional multivariate time series (MTS) into a number of low-dimensional MTS is a useful but challenging task because the number of possible dependencies between variables is likely to be huge. This paper is about a systematic study of the "variable groupings" problem in MTS. In particular, we investigate different methods of utilizing the information regarding correlations among MTS variables. This type of method does not appear to have been studied before. In all, 15 methods are suggested and applied to six datasets where there are identifiable mixed groupings of MTS variables. This paper describes the general methodology, reports extensive experimental results, and concludes with useful insights on the strength and weakness of this type of grouping method.
Fuzzy Two-Phase evolutionary programming (FTPEP) is proposed in this paper based on augmented Lagrange multiplier for constrained optimization comparing to the lack of classic evolutionary algorithm applied in nonline...
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ISBN:
(纸本)0780372689
Fuzzy Two-Phase evolutionary programming (FTPEP) is proposed in this paper based on augmented Lagrange multiplier for constrained optimization comparing to the lack of classic evolutionary algorithm applied in nonlinear constrained optimization. FTPEP based on augmented Lagrange multiplier has two steps: the first phase uses the standard fuzzy evolutionary programming to find a near global solution, which is employed in second phase;thought the use of augmented Lagrange multiplier in the second phase and by gradually place emphasis on violated constraints in the objective function, the trial solutions are drove to the optimal point. FTPEP has two phases in the global optimization, the algorithm is proved to be reliable and effective, and it is especially employed in heavily nonlinear constraint problems. Computation examples are given in the end of this paper, the simulation result proves the characters of FTPEP, and can be applied in the constrained optimization of robot track planning.
作者：
R. SimutisProcess Control Department
Kaunas University of Technology Studentu 50 LT-3031 Kaunas Lithuania phone: (+370 7) 35-15-39 fax: (+370 7) 75-43-29
In stock markets, the relationships between process variables are generally too complex to make grounded decisions using classical system theory. The goal of this study was to build and to evaluate a human skill based...
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In stock markets, the relationships between process variables are generally too complex to make grounded decisions using classical system theory. The goal of this study was to build and to evaluate a human skill based expert system for decision making support in stock trading process. Our focus was concentrated on computer software that is capable to reproduce the knowledge from the skilled stock trader. Using classical technique and soft computing methods the expert system STRASS ( S tock TRA ding S upport S ystem) was developed. The proposed expert system yielded about 23% annual “paper profit” for the historical collection of NASDAQ, NYSE and AMAX stocks records. At present, it is being tested by “ KOLEGU ” mutual fund in a real stock trading process.
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