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检索条件"主题词=EVOLUTIONARY PROGRAMMING"

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Robust Image Registration for Multiple Exposure High Dynamic Range Image Synthesis

Robust Image Registration for Multiple Exposure High Dynamic...

引用

Conference on Image Processing: Algorithms and Systems IX

作者： Yao, Susu ASTAR Inst Infocomm Res Singapore 138632 Singapore

ISBN: (纸本)9780819484079

Image registration is an important preprocessing technique in high dynamic range (HDR) image synthesis. This paper proposed a robust image registration method for aligning a group of low dynamic range images (LDR) that are captured with different exposure times. Illumination change and photometric distortion between two images would result in inaccurate registration. We propose to transform intensity image data into phase congruency to eliminate the effect of the changes in image brightness and use phase cross correlation in the Fourier transform domain to perform image registration. Considering the presence of non-overlapped regions due to photometric distortion, evolutionary programming is applied to search for the accurate translation parameters so that the accuracy of registration is able to be achieved at a hundredth of a pixel level. The proposed algorithm works well for under and over-exposed image registration. It has been applied to align LDR images for synthesizing high quality HDR images.

关键词： Image registration phase correlation phase congruency evolutionary programming HDR imaging

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Cyber-Secure UAV Communications using Heuristically Inferred Stochastic Grammars and Hard Real-Time Adaptive Waveform Synthesis and Evolution 18

Cyber-Secure UAV Communications using Heuristically Inferred...

引用

IEEE 18th International Conference on Information Reuse and Integration (IRI)

作者： Rubin, Stuart H. Grefe, William K. Bouabana-Tebibel, Thouraya Chen, Shu-Ching Shyu, Mei-Ling Simonsen, Kenneth S. Space & Naval Warfare Syst Ctr Pacific San Diego CA 92152 USA Ecole Natl Super Informat LCSI Lab Bab Ezzouar Algeria Florida Int Univ Sch Comp & Informat Sci Miami FL 33199 USA Univ Miami Dept Elect & Comp Engn Coral Gables FL 33124 USA

ISBN: (纸本)9781538615621

This paper initially describes how an inferred context-free (stochastic) grammar can be used to verify command transmissions and serve as a hedge against a successful cyber-attack. The remainder of the paper addresses a computational problem not amenable to closed-form solution;namely, the hard real-time (similar to 57 usec) synthesis of a desired waveform through the adaptive modification of a carrier wave. This effectively increases the signal to noise ratio - ensuring better UAV communications. Here, the modulation of the primary waveform is under user control and is of strictly positive amplitude. The primary waveform induces a secondary waveform having delayed leading and trailing edges and expanded rise and fall times. There is, in general, a direct relation between the period of the primary waveform and the amplitude of the secondary waveform. The relation between the primary and secondary waveforms may be characterized by trigonometric functions or even interpolating polynomials. However, response time will be minimized where the primary waveforms are discretized and stored in the form of array-based cases. The tertiary (target) wave may be any periodic trigonometric function, but is taken to be a simple sine wave without loss of generality. The task of the adaptive program is to minimize parallel to s(t) - g(t)parallel to 2, where f(t) -> g(t) and f(t) is the primary waveform at time t, g(t) is the secondary waveform at time t, and s(t) is the tertiary waveform at time t. A computationally efficient algorithm is provided for solving this task in real time. Moreover, an evolutionary program (EP) is provided for automatic case acquisition. Primary waveforms are mutated in accordance with a normal distribution.

关键词： Adaptive programming Case-Based Reasoning evolutionary programming Expectation-Driven Receiver Grammatical Inference Hard Real-Time Systems Waveform Analysis and Synthesis

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An Effective Intrusion Detection Algorithm Based on Improved Semi-supervised Fuzzy Clustering

An Effective Intrusion Detection Algorithm Based on Improved...

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International Conference on Intelligent Computing and Information Science

作者： Li, Xueyong Zhang, Baojian Sun, Jiaxia Yan, Shitao Henan Inst Sci & Technol Sch Informat Engn Xinxiang 453003 Peoples R China

ISBN: (纸本)9783642181337

An algorithm for intrusion detection based on improved evolutionary semi-supervised fuzzy clustering is proposed which is suited for situation that gaining labeled data is more difficulty than unlabeled data in intrusion detection systems. The algorithm requires a small number of labeled data only and a large number of unlabeled data and class labels information provided by labeled data is used to guide the evolution process of each fuzzy partition on unlabeled data, which plays the role of chromosome. This algorithm can deal with fuzzy label, uneasily plunges locally optima and is suited to implement on parallel architecture. Experiments show that the algorithm can improve classification accuracy and has high detection efficiency.

关键词： intrusion detection semi-supervised learning clustering evolutionary programming

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Differential Evolution based OPF with Conventional and Non-Conventional Cost Characteristics

Differential Evolution based OPF with Conventional and Non-C...

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Joint International Conference on Power Systems Technology (POWERCON)/IEEE Power India Conference

作者： Vaisakh, K. Srinivas, L. R. Andhra Univ Dept Elect Engn Autonomous Coll Engn Visakhapatnam 530003 Andhra Pradesh India SRKR Engn Dept Elect Engn Bhimavaram 534204 AP India

ISBN: (纸本)9781424417636

An efficient evolutionary-based approach, termed as Differential Evolution (DE), is presented for the solution of Optimal Power Flow (OPF) with the continuous variables. The continuous control variables are unit-active power outputs and generator-bus voltage magnitudes, transformer tap settings and switchable shunt devices. The differential evolution is illustrated for two case studies of IEEE-30 bus system. Both conventional and non-conventional cost characteristics are considered for the optimal power flow solution. The feasibility of the proposed method is compared with a simple evolutionary, programming algorithm. The algorithm is computationally faster, in terms of the number of load flows executed, and provides better results than other heuristic techniques.

关键词： Conventional and non-conventional cost characteristics differential evolution evolutionary programming optimal power flow

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Research and New Development of Application of the Estimation of Distribution Algorithms

Research and New Development of Application of the Estimatio...

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2nd International Conference on Information and Computing Science

作者： Wang, Dandan Jiang, Yong Li, Jianliang Nanjing Univ Sci & Technol Dept Informat & Comp Sci Nanjing 210094 Peoples R China

ISBN: (纸本)9780769536347

The Estimation of Distribution Algorithms (EDAs) is a novel class of evolutionary algorithms which is motivated by the idea of building probabilistic graphical model of promising solutions to represent linkage information between variables in chromosome. Through learning of and sampling from probabilistic graphical model, new population is generated and optimization procedure is repeated until the stopping criteria are met. In this paper, the mechanism of the Estimation of Distribution Algorithms is analyzed. Currently existing EDAs are surveyed and categorized according to the probabilistic model they used.

关键词： genetic algorithm evolutionary programming estimation of distribution algorithms

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Turbulent Crazy Particle swarm Optimization Technique for Optimal Reactive Power Dispatch

Turbulent Crazy Particle swarm Optimization Technique for Op...

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World Congress on Nature and Biologically Inspired Computing

作者： Roy, P. K. Ghoshal, S. P. Thakur, S. S. Dr BC Roy Engn Coll Dept Elect Engn Durgapur W Bengal India Natl Inst Technol Dept Elect Engn Durgapur W Bengal India

ISBN: (纸本)9781424450534

In this paper, a new particle swarm optimization (PSO) algorithm namely Turbulent Crazy Particle swarm Optimization (TRPSO) is introduced to solve multi-constrained optimal reactive power dispatch in power system. Optimal reactive power dispatch problem is a multi-objective optimization problem that minimizes bus voltage deviations and transmission loss. The feasibility of the proposed algorithm is demonstrated for IEEE 30-bus system and it is compared to other well established population based optimization techniques like conventional PSO, general passive congregation PSO (GPAC), local passive congregation PSO (LPAC), coordinated aggregation (CA) and Interior point based OPF (IP-OPF). A comparison of simulation results indicates that the proposed algorithm can produce better solution than other optimization techniques.

关键词： Optimal reactive power Flow Particle Swarm Optimization evolutionary programming turbulence passive congregation

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Application of evolutionary computation in ECAD problems

Application of evolutionary computation in ECAD problems

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Conference on Applications and Science of Neural Networks, Fuzzy Systems, and evolutionary Computation

作者： Lee, DH Hwang, SH Korea Adv Inst Sci & Technol Dept Elect Engn Yusong Gu Taejon 305701 South Korea

ISBN: (纸本)0819429104

Design of modern electronic systems is a complicated task which demands the use of computer-aided design(CAD) tools. Since a lot of problems in ECAD are combinatorial optimization problems, evolutionary computations such as genetic algorithms and evolutionary programming have been widely employeed to solve those problems. We have applied evolutionary computation techniques to serve ECAD problems such as technology mapping, microcode-bit optimization, data path ordering and peak power estimation, where their benefits are well observed. This paper presents experiences and discusses issues in those applications.

关键词： evolutionary computation genetic algorithm evolutionary programming electronic computer-aided design technology mapping microcode-bit optimization data path ordering peak power estimation

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Decision support system for breast cancer diagnosis by a meta-learning approach based on grammar evolution

Decision support system for breast cancer diagnosis by a met...

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8th International Conference on Enterprise Information Systems (ICEIS 2006)

作者： Fornells-Herrera, Albert Golobardes-Ribe, Elisabet Bernado-Mansilla, Ester Marti-Bonmati, Joan Ramon Llull Univ Res Grp Intelligent Syst Barcelona 08022 Spain

ISBN: (纸本)9728865422

The incidence of breast cancer varies greatly among countries, but statistics show that every year 720,000 new cases will be diagnosed world-wide. However, a low percentage of women who suffer it can be detected using mammography methods. Therefore, it is necessary to develop new strategies to detect its formation in early stages. Many machine learning techniques have been applied in order to help doctors in the diagnosis decision process, but its definition and application are complex, getting results which are not often the desired. In this article we present an automatic way to build decision support systems by means of the combination of several machine learning techniques using a Meta-learning approach based on Grammar Evolution (MGE). We will study its application over different mammographic datasets to assess the improvement of the results.

关键词： breast cancer diagnosis strategic decision support systems evolutionary programming meta-learning application of artificial intelligence on medicine

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Comparison of Intelligent Techniques to Solve Economic Load Dispatch with Bilateral and Multilateral Transactions

Comparison of Intelligent Techniques to Solve Economic Load ...

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IEEE Region 10 Conference (TENCON 2008)

作者： Raglend, I. Jacob Karthikeyan, P. Sudheera Sailaja Sowjanya Kothari, D. P. Vellore Inst Technol Sch Elect Sci Vellore 632014 Tamil Nadu India Vellore Inst Technol FNAE FNASC SMIEEE Vellore 632014 Tamil Nadu India

ISBN: (纸本)9781424424085

One of the most challenging operational aspects in restructured systems with open transmission access is the power management of the grid. With the trend of an increasing number of bilateral and multilateral transactions submitted to the Independent System Operator (ISO), the possibility of insufficient resources in the transmission system may be unavoidable. In this paper, evolutionary computation techniques such as Genetic Algorithm (GA), evolutionary programming (EP), Particle Swarm Optimization (PSO), Differential Evolution (DE), are applied to solve the economic load dispatch problem with bilateral and multilateral transactions. Different evolutionary Computation methods are applied to obtain ELD solutions for IEEE 30-bus system. The results obtained by this approaches are compared with respect to solution time, production cost and convergence criteria. The solutions obtained are quite encouraging and useful in the economic environment. The algorithm and simulation are carried using Matlab software.

关键词： Economic Load Dispatch Genetic Algorithm evolutionary programming Particle Swarm Optimization and Differential Evolution Bilateral Multilateral Transactions

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Natural Computation for Optimal Scheduling with ILP Modeling in High Level Synthesis

Natural Computation for Optimal Scheduling with ILP Modeling...

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International Conference on Information and Communication Technologies (ICICT)

作者： Shilpa, K. C. LakshmiNarayana, C. Visvesvaraya Technol Univ Dept Elect Engn Sci BMSCE Bangalore 560019 Karnataka India

The concept of the natural computation for optimal scheduling in high level synthesis, for resource constraint and time constraint scheduling problem in automated integrated circuit synthesis using Integer Linear programming (ILP) modeling is presented in this paper. This paper compares three natural computations paradigms: (i) evolution optimizer technique genetic algorithm, (ii) evolutionary programming, and (iii) swarm intelligence based particle swarm optimization. Experimental results indicate that evolution based Genetic Algorithm search is more powerful search compared to evolutionary programming and Particle Swam Optimization. (C) 2015 The Authors. Published by Elsevier B.V.

关键词： High Level Synthesis Data Flow Graph evolutionary programming Genetic Algorithm Particle Swarm Optimization Very Large Scale Integration Integer Linear programming

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