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DAE-BRNS National Laser Symposium

作者： Hazra, L. N. Reza, N. Univ Calcutta Dept Appl Opt & Photon Kolkata 700009 India

Resolution capability of any optical imaging system is limited by residual aberrations as well as diffraction effects. Overcoming this fundamental limit is called super-resolution. Several new paradigms for super-resolution in optical systems use 'a posteriori' digital image processing. In these ventures the three-dimensional point spread function (PSF) of the lens plays a key role in image acquisition. A straightforward tailoring of the PSF can be performed by appropriate pupil plane filtering. With a brief review of the state-of-art in this research area, this paper dwells upon the inverse problem of global optimization of the pupil function by phase filtering in accordance with the desired PSF.

关键词： Super-resolution high-resolution imaging pupil plane filtering phase filters global optimization evolutionary programming genetic algorithm

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A novel approach for structural synthesis of zoom systems

A novel approach for structural synthesis of zoom systems

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Conference on Current Developments in Lens Design and Optical Engineering XI - and Advances in Thin Film Coatings VI

作者： Hazra, L. N. Pal, S. Univ Calcutta Dept Appl Opt & Photon Kolkata India

ISBN: (纸本)9780819482822

A new approach for 'ab initio' synthesis of thin lens structure of zoom lenses is reported. This is accomplished by an implementation of evolutionary programming, based on Genetic Algorithm, which explores the available configuration space formed by powers of individual components and inter-component separations. Normalization of the variables is carried out to get an insight on the optimum structures. The method has been successfully used to get thin lens structures of mechanically compensated, optically compensated, and linearly compensated zoom lens systems by suitable formulation of merit function of optimization. Investigations have been carried out on three component and four component zoom lens structures. Illustrative numerical results are presented.

关键词： Optically compensated zoom lenses mechanically compensated zoom lenses evolutionary programming genetic algorithm thin lens design

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Optimal Design of Toraldo Super Resolving Filters

Optimal Design of Toraldo Super Resolving Filters

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Conference on Novel Optical Systems Design and Optimization XIII

作者： Hazra, L. N. Reza, N. Univ Calcutta Dept Appl Opt & Photon Kolkata 700009 W Bengal India

ISBN: (纸本)9780819482839

Pupil plane filtering provides a convenient technique for modifying the point spread function. Such modifications are used in many practical applications that require enhancement of selective frequency band in images. Also, in many new imaging paradigms, acquisition of 3D image information calls for tailoring of the 3D point spread function. This can be achieved by suitable pupil plane filtering, preferably by phase filters. By using a pupil plane filter with an array of concentric annuli, the point spread function can be tailored in a fashion such that a narrow central lobe is surrounded by neighboring lobes of low amplitude, with one or more lobes of high amplitude spaced far away from the center. In our study we intend to explore the use of phase annuli as pupil filters in tailoring of both transverse and axial resolution. Determination of such phase filters in accordance with a set of prespecified requirements for amplitude/intensity distribution around the focus constitutes a problem of nonlinear optimization. This paper reports some results of our preliminary investigations on an application of evolutionary programming in solving this problem to obtain globally or quasi-globally optimum solutions.

关键词： Superresolution High resolution imaging Pupil plane Filtering Phase Filters Global Optimization evolutionary programming Genetic Algorithm

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Tailored excitations for structural health monitoring via evolutionary programming

Tailored excitations for structural health monitoring via ev...

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Conference on Health Monitoring and Smart Nondestructive Evaluation of Structural and Biological Systems V

作者： Olson, Colin C. Todd, M. D. Univ Calif San Diego Dept Struct Engn La Jolla CA 92093 USA

ISBN: (纸本)0819462306

Dynamic interrogation of structures for the purposes of damage identification is an active area of research within the field of structural health monitoring with recent work focusing on the use of chaotic excitations and state-space analyses for improved damage detection. Inherent in this overall approach is the specific interaction between the chaotic input and the structure's eigenstate. The sensitivity to damage is theoretically enhanced by special tailoring of the input in terms of stability interaction with the structure. This work outlines the use of an evolutionary program to search the parameter space of a chaotic excitation for those parameters that are best suited to appropriately couple the excitation with the structure for enhanced damage detection. State-space damage identification metrics are used to detect damage in a computational model driven by excitations produced via the evolutionary program with non-optimized excitations used as comparison cases.

关键词： structural health monitoring chaos evolutionary programming gene expression programming

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A sequential evolutionary programming approach to profit-based unit commitment

A sequential evolutionary programming approach to profit-bas...

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IEEE/PES Transmission and Distribution Conference and Exposition Latin America

作者： Contreras-Hernandez, E. J. Cedeno-Maldonado, J. R. Univ Puerto Rico Dept Elect & Comp Engn Mayaguez PR 00681 USA

ISBN: (纸本)9781424402878

This paper presents the application of a Sequential evolutionary programming (SEP) approach for solving the Profit-Based Unit Commitment problem (PBUC). The PBUC problem is a variant of the traditional Unit Commitment (UC) that has arisen as a result of the deregulation of power system markets. Specifically, PBUC is used for Generation Companies (Genco's) in order to maximize their own profits without the responsibility of satisfying necessary the forecasted demand. The PBUC is a highly dimensional mixed-integer optimization problem, which might be very difficult to solve. The SEP approach introduced in this paper offers a good balance between accuracy and computational effort while solving the PBUC problem. For its implementation, the PBUC problem is decomposed into three sub-problems that are solved in a sequential way. The proposed method is suitable for a wide variety of power system market rules. In this paper, two case studies are considered, each with different sets of power system market rules. The obtained results were compared with those available in the literature, and they showed the effectiveness of the proposed method for reaching optimal PBUC solutions.

关键词： energy markets evolutionary programming mixed-integer variables optimization problem profit-based unit commitment reserve markets

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Optimal placement of distributed generators networks using evolutionary programming

Optimal placement of distributed generators networks using e...

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IEEE/PES Transmission and Distribution Conference and Exposition Latin America

作者： de Souza, Benemar A. de Albuquerque, Joao M. C. Univ Fed Campina Grande Av Aprigio Veloso882 BR-58109970 Campina Grande Paraiba Brazil

ISBN: (纸本)9781424402878

An algorithm is presented for the allocation and sizing of generators in radial distribution networks in order to maximize the reduction on the load supply costs. In addition, it is given the operational schedule for each installed generator for all feeder load levels. The evolutionary programming is used as the optimization technique. The applicability of the method was evaluated using a feeder with high losses index and the proposed allocation provided a considerable reduction on total costs.

关键词： distributed generation distribution system planning evolutionary programming

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A new mutation operator based on the T probability distribution in evolutionary programming

A new mutation operator based on the T probability distribut...

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5th IEEE International Conference on Cognitive Informatics (ICCI 2006)

作者： Gong, Wenyin Cai, Zhihua Lu, Xinwei Jiang, Siwei China Univ Geosci Sch Comp Sci Wuhan 430070 Peoples R China

ISBN: (纸本)9781424404759

A new mutation operator based on the T probability distribution is studied. The T probability distribution is stable and can generate an offspring that is farther away from its parent than the commonly employed Gaussian mutation. Moreover, it has a better fine-tuning ability than the Cauchy mutation. In this paper, evolutionary programming (EP) with mutations based on the T probability distribution is studied. The new algorithm is tested on 23 benchmark functions and compared with the conventional EP and the fast ER The experimental results demonstrate that the performance of the proposed algorithm outperforms the conventional EP and the fast EP.

关键词： evolutionary programming T probability distribution T mutation function optimization

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Solving dynamic economic dispatch using evolutionary programming

Solving dynamic economic dispatch using evolutionary program...

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1st International Power and Energy Conference (PECon 2006)

作者： Joned, Azmi Murad Abdul Aziz Musirin, Ismail Rahman, Titik Khawa Abdul IEEE Repair and Maintenance (REMACO) Coal Stockyard Manjung Perak Malaysia Faculty of Electrical Engineering Universiti Teknologi MARA Shah Alam Selangor Malaysia Faculty of Electrical Engineering Universiti Teknologi MARA Malaysia IEEE Malaysia Section

ISBN: (纸本)9781424402731

Ensuring a smooth electrical energy to the consumer has been identified as the main role of electric supply utility. In doing so, the power utility needs to ensure that the electrical power is generated with minimum cost. Hence, for economic operation of the system, the total demand must be appropriately shared among the generating units with an objective to minimize the total generation cost for the system with the voltage level maintained at the secure operating limit. Dynamic economic dispatch (DED) is one of the main functions of power generation, operation and control. DED is an improvement of the conventional economic dispatch. This paper proposes an optimization technique to solve dynamic economic dispatch (DED) in the electric power system using Ant Colony Optimization (ACO) technique. Prior to the DED scheme, static economic dispatch (SED) was conducted for the purpose of comparison. Implementation on an IEEE test system highlighted the merit of the proposed EP technique for the DED implementation

关键词： evolutionary programming dynamic economic dispatch optimization technique

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An evolutionary programming based tabu search method for unit commitment problem with cooling-banking constraints

An evolutionary programming based tabu search method for uni...

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IEEE Power India Conference 2006

作者： Rajan, C. Christober Asir Pondicherry Coll Dept Elect Engn Pondicherry 605014 India

ISBN: (纸本)9780780395251

This paper presents a new approach to solve the short-term unit commitment problem using An evolutionary programming Based tabu search Method with cooling and banking constraints. The objective of this paper is to find the generation scheduling such that the total operating cost can be minimized, when subjected to a variety of constraints. This also means that it is desirable to rind the optimal generating unit commitment in the power system for the next H hours. evolutionary programming, which happens to be a Global Optimization technique for solving Unit Commitment Problem, operates on a system, which is designed to encode each unit's operating schedule with regard to its minimum up/down time. In this, the unit commitment schedule is coded as a string of symbols. An initial population of parent solutions is generated at random. Here, each schedule is formed by committing all the units according to their initial status ("flat start"). Here the parents are obtained from a pre-defined set of solution's i.e. each and every solution is adjusted to meet the requirements. Then, a random decommitment is carried out with respect to the unit's minimum down times. And TS improves the status by avoiding entrapment in local minima. The best population is selected by evolutionary strategy. Numerical results are shown comparing the cost solutions and computation time obtained by using the evolutionary programming method and other conventional methods like Dynamic programming, Legrangian Relaxation.

关键词： dynamic programming evolutionary programming Legrangian relaxation tabu search unit commitment

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Automatic Induction of Projection Pursuit Indices

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IEEE TRANSACTIONS ON NEURAL NETWORKS 2010年第8期21卷 1281-1295页

作者： Rodriguez-Martinez, E. Goulermas, John Yannis Mu, Tingting Ralph, Jason F. Univ Liverpool Dept Elect Engn & Elect Liverpool L69 4GJ Merseyside England Univ Manchester Natl Ctr Text Min Sch Comp Sci Manchester M1 7DN Lancs England

Projection techniques are frequently used as the principal means for the implementation of feature extraction and dimensionality reduction for machine learning applications. A well established and broad class of such projection techniques is the projection pursuit (PP). Its core design parameter is a projection index, which is the driving force in obtaining the transformation function via optimization, and represents in an explicit or implicit way the user's perception of the useful information contained within the datasets. This paper seeks to address the problem related to the design of PP index functions for the linear feature extraction case. We achieve this using an evolutionary search framework, capable of building new indices to fit the properties of the available datasets. The high expressive power of this framework is sustained by a rich set of function primitives. The performance of several PP indices previously proposed by human experts is compared with these automatically generated indices for the task of classification, and results show a decrease in the classification errors.

关键词： Classification evolutionary programming feature transformation projection pursuit

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