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Parameter optimization of an on-chip voltage reference circuit using evolutionary programming

IEEE TRANSACTIONS ON evolutionary COMPUTATION 2001年第4期5卷 414-421页

作者： Nam, D Seo, YD Park, LJ Park, CH Kim, B Korea Adv Inst Sci & Technol Dept Elect Engn & Comp Sci Taejon 305701 South Korea Korea Adv Inst Sci & Technol Dept Elect Engn & Comp Sci Taejon 305701 South Korea

This paper presents an application of evolutionary programming to parameter optimization in the design of a voltage reference circuit Designing circuits consists of two steps: topological design and parameter determination. After designing a topology suitable for the circuit, the designer selects an appropriate value for each circuit element from a circuit analysis and his experience. This step is difficult and time consuming because the designer must consider many factors simultaneously. As more precise circuits are required, parameter optimization becomes more complex. The voltage reference circuit, which requires a precise reference voltage independent of power fluctuation and temperature change, is such an example. In this paper, evolutionary programming is used as an effective method of finding good parameter values for the elements of the voltage reference circuit. Simulation results show that this method provides good performance and can be used as an effective method for circuit design.

关键词： evolutionary programming parameter optimization voltage reference circuit

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Solving Unit Commitment Problem Using Multi-agent evolutionary programming Incorporating Priority List

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ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2015年第11期40卷 3247-3261页

作者： Othman, M. N. C. Rahman, T. K. A. Mokhlis, H. Aman, M. M. Univ Tenaga Nas Dept Elect Power Engn Coll Engn Kajang 43000 Selangor Malaysia King Abdulaziz Univ Fac Engn Dept Elect & Comp Engn Jeddah 21413 Saudi Arabia Univ Malaya Dept Elect Engn Fac Engn Kuala Lumpur 50603 Malaysia

This paper presents an approach to solve the unit commitment problem using a newly developed Multi-agent evolutionary programming incorporating Priority List optimisation technique (MAEP-PL). The objective of this study is to search for generation scheduling such that the total operating cost can be minimised when subjected to a variety of constraints, while at the same time reducing its computational time. The proposed technique assimilates the concepts of Priority Listing (PL), Multi-agent System (MAS) and evolutionary programming (EP) as its basis. In the proposed technique, deterministic PL technique is applied to produce a population of initial solutions. The search process is refined using heuristic EP-based algorithm with multi-agent approach to produce the final solution. The developed technique is tested on ten generating units test system for a 24-h scheduling period, and the results are compared with the standard evolutionary programming (EP), evolutionary programming with Priority Listing (EP-PL) and Multi-agent evolutionary programming (MAEP) optimisation techniques. From the obtained results and the comparative studies, it was found that the proposed MAEP-PL optimisation technique is able to solve the unit commitment problem where the total daily generation cost is effectively minimised and the computation time is reduced as compared to other techniques.

关键词： Unit commitment Multi-agent evolutionary programming Priority list

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Designing multilayer perceptrons using a Guided Saw-tooth evolutionary programming Algorithm

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SOFT COMPUTING 2010年第6期14卷 599-613页

作者： Antonio Gutierrez, Pedro Hervas, Cesar Lozano, Manuel Univ Cordoba Dept Numer Anal & Comp Sci E-14071 Cordoba Spain Univ Granada E-18071 Granada Spain

In this paper, a diversity generating mechanism is proposed for an evolutionary programming (EP) algorithm that determines the basic structure of Multilayer Perceptron classifiers and simultaneously estimates the coefficients of the models. We apply a modified version of a saw-tooth diversity enhancement mechanism recently presented for Genetic Algorithms, which uses a variable population size and periodic partial reinitializations of the population in the form of a saw-tooth function. Our improvement on this standard scheme consists of guiding saw-tooth reinitializations by considering the variance of the best individuals in the population. The population restarts are performed when the difference of variance between two consecutive generations is lower than a percentage of the previous variance. From the analysis of the results over ten benchmark datasets, it can be concluded that the computational cost of the EP algorithm with a constant population size is reduced by using the original saw-tooth scheme. Moreover, the guided saw-tooth mechanism involves a significantly lower computer time demand than the original scheme. Finally, both saw-tooth schemes do not involve an accuracy decrease and, in general, they obtain a better or similar precision.

关键词： Artificial neural networks Multilayer perceptrons evolutionary algorithms evolutionary programming Population reinitializations Saw-tooth algorithm

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Network anomaly detection by continuous hidden markov models: An evolutionary programming approach

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INTELLIGENT DATA ANALYSIS 2015年第2期19卷 391-412页

作者： Flores, Juan J. Calderon, Felix Antolino, Anastacio Garcia, Juan M. Univ Michoacana Fac Ingn Elect Div Estudios Posgrad Morelia Michoacan Mexico Inst Tecnol Morelia Dept Sistemas & Comp Morelia Michoacan Mexico

Information security is an important and growing need. The most common schemes used for detection systems include pattern-or signature-based and anomaly-based. Anomaly-based schemes use a set of metrics, which outline the normal system behavior and any significant deviation from the established profile will be treated as an anomaly. This paper contributes with an anomaly-based scheme that monitors the bandwidth consumption of a subnetwork, at the Universidad Michoacana, in Mexico. A normal behavior model is based on bandwidth consumption of the subnetwork. The presence of an anomaly indicates that something is misusing the network (viruses, worms, denial of service, or any other kind of attack). This work also presents a scheme for an automatic architecture design and parameters optimization of Hidden Markov Models (HMMs), based on evolutionary programming (EP). The variables to be used by the HMMs are: the bandwidth consumption of network (IN and OUT), and the associated time where the network activity occurs. The system was tested with univariate and bivariate observation sequences to analyze and detect anomaly behavior. The HMMs, designed and trained by EP, were compared against semi-random HMMs trained by the Baum-Welch algorithm. On a second experiment, the HMMs, designed and trained by EP, were compared against HMMs created by an expert user. The HMMs outperformed the other methods in all cases. Finally, we made the HMMs time-aware, by including time as another variable. This inclusion made the HMMs capable of detecting activity patterns that are normal during a period of time but anomalous at other times. For instance, a heavy load on the network may be completely normal during working times, but anomalous at nights or weekends.

关键词： HMMs evolutionary programming genetic algorithms anomaly detection Baum-Welch

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Comparison and application of evolutionary programming techniques to combined economic emission dispatch with line flow constraints

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IEEE TRANSACTIONS ON POWER SYSTEMS 2003年第2期18卷 688-697页

作者： Venkatesh, P Gnanadass, R Padhy, NP Thiagarajar Coll Engn Dept Elect & Elect Engn Madurai 625015 Tamil Nadu India Pondicherry Engn Coll Dept Elect & Elect Engn Pondicherry 605014 India Indian Inst Technol Dept Elect Engn Roorkee 247667 Uttar Pradesh India

Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuelcost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. This biobjective CEED problem is converted into a single objective function using a price penalty factor approach. A novel modified price penalty factor is proposed to solve the CEED problem. In this paper, evolutionary computation (EC) methods such as genetic algorithm (GA), micro GA, (NIGA), and evolutionary programming (EP) are applied to obtain ELD solutions for three-, six-, and 13-unit systems. Investigations showed that EP? was better arnong EC methods in solving the ELD problem. EP-based CEED. problem has been tested on IEEE 14-, 30-, and 118-bus systems with and without line flow constraints. A nonlinear scaling factor is also included in EP algorithm to improve the convergence performance for the 13 units and IEEE test systems. The solutions obtained are quite encouraging and useful in the economic emission environment.

关键词： combined cycle cogeneration plant combined economic emission dispatch economic load dispatch evolutionary programming price penalty factor

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Generalized early-time/late-time evolutionary programming-based clean

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MICROWAVE AND OPTICAL TECHNOLOGY LETTERS 2008年第1期50卷 208-210页

作者： Choi, In-Sik Kim, Hyo-Tae Hannam Univ Dept Elect Engn Taejon 306791 South Korea Pohang Univ Sci & Technol Dept Elect & Elect Engn Pohang 790784 Kyungbuk South Korea

A novel method, which is called generalized early-time/late-time evolutionary programming (EP)-based CLEAN algorithm, is proposed for simultaneous extraction of the scattering centers and natural resonance frequencies of a radar target. This algorithm uses a duality between the temporal late-time response and spectral early-time response. (c) 2007 Wiley Periodicals, Inc.

关键词： evolutionary programming scattering centers natural resonance frequencies duality

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One-dimensional evolutionary programming-based CLEAN

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ELECTRONICS LETTERS 2001年第6期37卷 400-401页

作者： Choi, IS Kim, HT Pohang Univ Sci & Technol Dept Elect & Elect Engn Nam Gu Pohang 790784 Kyungbuk South Korea

A novel one-dimensional scattering centre extraction method using an evolutionary programming and undamped exponential model is proposed. The method is robust and fast. Moreover. no resolution problems appeared in FFT-based CLEAN. Experimental results show that the proposed algorithm can be successfully applied to one-dimensional scattering centre extraction.

关键词： fast Fourier transforms ideal point scatterers backscattered signals Integral transforms in numerical analysis Optimisation techniques evolutionary computation radar signal processing undamped exponential model radar target recognition backscatter one-dimensional scattering centre extraction method Signal processing and detection FFT-based CLEAN Radar theory evolutionary programming

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Fast computation evolutionary programming algorithm for the economic dispatch problem

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EUROPEAN TRANSACTIONS ON ELECTRICAL POWER 2006年第1期16卷 35-47页

作者： Somasundaram, P Kuppusamy, K Devi, RPK Anna Univ Dept Elect & Elect Engn Power Syst Engn Div Madras 600025 Tamil Nadu India

This paper essentially aims to propose a new EP based algorithm for solving the ED problem. The ED problem is solved using EP with system lambda as decision variable and power mismatch as fitness function. The algorithm is made fast through judicious modifications in initialization of the parent population, offspring generation and selection of the normal distribution curve. The proposed modifications reduce the search region progressively and generate only effective offsprings. The proposed algorithm is tested on a number of sample systems with quadratic cost function and also on a 10-unit system with piecewise quadratic cost function. The computational results reveal that the proposed algorithm has an excellent convergence characteristic and is superior to other EP based methods in many respects. Copyright (c) 2005 John Wiley & Sons, Ltd.

关键词： evolutionary programming economic dispatch piecewise quadratic cost function

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A novel optimal reactive power dispatch method based on an improved hybrid evolutionary programming technique

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IEEE TRANSACTIONS ON POWER SYSTEMS 2004年第2期19卷 913-918页

作者： Yan, W Lu, S Yu, DC Chongqing Univ Elect Power Dept Elect Engn Coll Chongqing 400044 Peoples R China Univ Wisconsin Dept Elect Engn Milwaukee WI 53211 USA

This paper proposes an improved evolutionary programming (IEP) and its hybrid version combined with the nonlinear interior point (IP) technique to solve the optimal reactive power dispatch (ORPD) problems. In an IEP method, the common practices in regulating reactive power are followed in adjusting the mutation direction of control variables in order to increase the possibility of keeping state variables within bounds. The IEP is also hybridized with the IP method to obtain a fast initial solution, which is then used as a highly evolved individual in the initial population of the improved EP method. Numerical tests of the proposed algorithm on the IEEE 118-bus system and a realistic power system in Western China are very encouraging compared with the existing ORPD algorithms in term of computational efficiency and optimality.

关键词： evolutionary programming interior point method optimal power flow optimal reactive power dispatch

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Composing photomosaic images using clustering based evolutionary programming

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MULTIMEDIA TOOLS AND APPLICATIONS 2019年第18期78卷 25919-25936页

作者： He, Yaodong Zhou, Jianfeng Yuen, Shiu Yin City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

Photomosaic images are a type of images consisting of various tiny images. In the past, many approaches have been proposed trying to automatically compose photomosaic images. To obtain a better visual sense and satisfy some commercial requirements, a constraint that a tiny image should not be repeatedly used many times is usually added. With the constraint, algorithms using greedy mechanism fail to solve it. In this paper, we present an approach called clustering based evolutionary programming to deal with the problem. Our new approach has a similar mechanism to that of evolutionary programming (we adopt mutation, selection and fitness evaluation) and uses the normalized color histogram information as the prior information. The two characteristics make our approach converges fast and performs well. In our experiment, the proposed algorithm is compared with the state of the art algorithms and software. The results indicate that our algorithm is able to generate higher quality photomosaic images.

关键词： Photomosaic evolutionary algorithm evolutionary programming Combinatorial optimization

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