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Review of harmony search with respect to algorithm structure

SWARM AND EVOLUTIONARY COMPUTATION 2019年 48卷 31-43页

作者： Zhang, Tonghua Geem, Zong Woo Swinburne Univ Technol Dept Math Hawthorn Vic 3122 Australia Gachon Univ Dept Energy IT Seongnam 13120 South Korea

Harmony Search (HS) is a metaheuristic optimisation algorithm inspired by musical improvisation. So far it has been applied to various optimisation problems, and there are several application-oriented review papers. However, this review paper tries to focus on the historical development of algorithm structure instead of applications. This paper explains the original HS algorithm along with a selection of modified and hybrid HS methods: adaption of original operators of the basic harmony search, parameter adaption, hybrid methods, handling multi objective optimisation problems and constraint handling.

关键词： Harmony search Optimisation Hybrid method algorithm structure Metaheuristic optimisation algorithm

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Fractal artistic algorithm structure and image production

Fractal artistic algorithm structure and image production

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International Conference on Advanced Materials and Computer Science

作者： Duan Ai-ling Duan Qiong-bo Beinjing Univ Posts & Telecommun Century Coll Beijing Peoples R China Tech Univ Dept Comp Sci Zhengzhou Henan Peoples R China Armed Police Force Xian Engn Coll Xian Shaanxi Peoples R China

ISBN: (纸本)9783037850978

The fractal art graphic is one of the main manifestations of fractal art, which can be produced through mathematical models and programming on a computer. The paper investigates the designing concept of fractal art based on its self similarity and the iterative method, elaborates in detail the algorithms and steps of several kind of typical fractal graphics, and by properly inserting some controlling variables, has generated a large number of exquisite and inspiring fractal graphics using the JAVA programming language, confirming the validity and usability of presented algorithm's.

关键词： Fractal art image algorithm structure JAVA

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Fractal artistic algorithm structure and image production

Fractal artistic algorithm structure and image production

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2011 International Conference on Advanced Materials and Computer Science(ICAMCS 2011)

作者： Duan ai-ling duan qiong-bo Century college Beijing University of posts and telecommunication Department of Computer Science of Technology University of Henan Engineering College of the Armed Police Force Xi'an

The fractal art graphic is one of the main manifestations of fractal art,which can be produced through mathematical models and programming on a computerThe paper investigates the designing concept of fractal art based on its self similarity and the iterative method,elaborates in detail the algorithms and steps of several kind of typical fractal graphics,and by properly inserting some controlling variables,has generated a large number of exquisite and inspiring fractal graphics using the JAVA programming language,confirming the validity and usability of presented algorithm's

关键词： Fractal art image algorithm structure JAVA

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Novel Approach to Minimize the Memory Requirements of Frequent Subgraph Mining Techniques

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Chinese Journal of Electronics 2021年第2期30卷 258-267页

作者： B?LG?N Turgay Tugay O?UZ Murat Department of Computer Engineering Bursa Technical University Microsoft Corporation Turkey Branch

Frequent subgraph mining(FSM) is a subset of the graph mining domain that is extensively used for graph classification and clustering. Over the past decade, many efficient FSM algorithms have been developed with improvements generally focused on reducing the time complexity by changing the algorithm structure or using parallel programming techniques. FSM algorithms also require high memory consumption, which is another problem that should be solved. In this paper, we propose a new approach called Predictive dynamic sized structure packing(PDSSP) to minimize the memory needs of FSM algorithms. Our approach redesigns the internal data structures of FSM algorithms without making algorithmic modifications. PDSSP offers two contributions. The first is the Dynamic Sized Integer Type, a newly designed unsigned integer data type, and the second is a data structure packing technique to change the behavior of the compiler. We examined the effectiveness and efficiency of the PDSSP approach by experimentally embedding it into two state-of-the-art algorithms, g Span and *** compared our implementations to the performance of the originals. Nearly all results show that our proposed implementation consumes less memory at each support level, suggesting that PDSSP extensions could save memory, with peak memory usage decreasing up to 38% depending on the dataset.

关键词： data structures algorithmic modifications high memory consumption graph mining domain Dynamic Sized Integer Type Predictive dynamic sized structure packing internal data structures graph classification parallel programming peak memory usage memory requirements PDSSP extensions finite state machines graph theory PDSSP approach algorithm structure newly designed unsigned integer data type data mining data structure packing technique efficient FSM algorithms clustering frequent subgraph mining techniques

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Towards LST split-window algorithm FPGA implementation for CubeSats on-board computations purposes

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INTERNATIONAL JOURNAL OF REMOTE SENSING 2019年第5-6期40卷 2435-2450页

作者： Raissouni, N. El Adib, S. Sobrino, J. A. Ben Achhab, N. Chahboun, A. Azyat, A. Lahraoua, M. Univ Abdelmalek Essaadi ENSA Tetuan Remote Sensing & Geog Informat Syst Unit RS&GIS Tetouan Morocco Univ Valencia IPL GCU Valencia Spain

Nano, pico, and the so-called CubeSat satellites are taking place due to the emergent improvements in both high-performance nano and pico electronics and computational technologies. More than 1600 nanosats and CubeSats exist nowadays (i.e. 685 nanosats launched, 613 CubeSats launched, 405 nanosatellites in orbit, 321 operational nanosatellites, 71 nanosats destroyed on launch, etc.), with an incredible panoply of different constellations, governmental and non-governmental, high and easy to reach technologies, instruments in miniatures and missions from the military to universities and schools. This paper describes an approach to the implementation of the land surface temperature split-window (LST-SW) (Sobrino and Raissouni, IJRS 2000) algorithm structure based on the field programmable gate array (FPGA) technology. Due to the ever-increasing integrated circuit fabrication capabilities, the future of FPGA technology promises both higher densities and higher speeds for CubeSats on-board computations purposes. The research application shows the advantages of the used Xilinx Virtex-5 LX50 series FPGA approach in the LST-SW implementation with higher sampling rates than what is available from existing digital signal processing (DSP) chips, lower costs than an application specific integrated circuits (ASIC) for moderate volume applications and more flexibility than the alternate approaches. Since many current FPGA architectures are in-system programmable, the configuration of the device may be changed to implement different functionalities if required depending on the LST-SW parameters for each corresponding author. Finally, preliminary results show that the proposed LST-SW Xilinx Virtex-5 LX50 FPGA implementation approach is exceedingly flexible. Moreover, this implementation provides a considerable and promising performance that is suitable for future CubeSats on board LST-SW computations purposes.

关键词： Field programmable gate arrays algorithm structure nano satellites

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Formation of Weighting Coefficients in an Artificial Neural Network Based on the Memristive Effect in Metal-Oxide-Metal Nanostructures

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JOURNAL OF COMMUNICATIONS TECHNOLOGY AND ELECTRONICS 2018年第8期63卷 950-957页

作者： Antonov, I. N. Belov, A. I. Mikhaylov, A. N. Morozov, O. A. Ovchinnikov, P. E. Lobachevsky State Univ Nizhny Novgorod Nizhnii Novgorod 603950 Russia

An approach to formation and training of an artificial neural network (ANN) based on thin-film memristive metal-oxide-metal nanostructures, which exhibit the effect of bipolar resistive switching, has been proposed. An experimental electric circuit of a small-sized ANN (a two-layer perceptron with 32 memristive elements) has been constructed. An algorithm for formation of weighting coefficients (ANN training), which takes into account probable spread of technological parameters of memristive structures has been developed.

关键词： Weighting coefficients formation algorithm structure Nanostructure

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A Study of the Physical structure of algorithms

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IEEE Transactions on Software Engineering 1977年第3期SE-3卷 250-258页

作者： Zweben, Stuart H. Department ofComputer and Information Science Ohio State University Columbus OH 43210 United States

A theory of the structural composition of an alilorithm is presented which allows the frequencies of occurrence of the individual operators and operands to be estimated. It provides justification for some recent hypotheses which suggest certain functional relationships between properties of algorithms. The theory for operands is based in part on models of program construction due to Bayer, while that of operators is based on the workof Zipf and Mandelbrot in natural language. A further relationship be tween the construction of algorithms and natural language text is indicated by demonstrating that thesize of an algoithm as predicted by one of Bayer's programming models and the size of a piece of text as predicted by Zipf's natural language model are identical. The theory is tested experimentally on a variety of algorlthms written in several programming languages with good statistical results. Copyright © 1977 by The Institute, of Electrical and Electronics Engineers, Inc.

关键词： algorithm structure frequency analysis models programming programming study software physics

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A Particle Swarm Optimization(PSO) algorithm Based on Multi-Agent System

A Particle Swarm Optimization(PSO) Algorithm Based on Multi-...

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International Conference on Intelligent Computation Technology and Automation

作者： Sheng Shangxiong Lanzhou Univ Technol Sch Mech & Elect Engn Lanzhou 730050 Gansu Peoples R China

ISBN: (纸本)9780769533575

In this paper, a distributed PSO algorithm in the JADE platform is studied based on traditional PSO. A parallel PSO algorithm structure based on Multi-agent corporative is proposed. The structure is made tip of several compute units. Each unit is a compute agent running basic particles swarm optimization. Simulation results show that the distributed structure can enhance system running efficiency. With the principal and subordinate running mechanism, the communication step is simplified, the running efficiency is optimized and the realization speed is enhanced.

关键词： Multi-agent systems operating efficiency parametric subharmonic oscillator DISTRIBUTED structureS Particle swarm optimization principal running mechanism algorithm structure

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Illegal Network Identification Optimization Based on Convolutional Neural Network

Illegal Network Identification Optimization Based on Convolu...

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2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)

作者： Weibin Chen Jinhua Yang International School Beijing University of Posts and Telecommunications

ISBN: (纸本)9781510871076

Convolutional neural network(CNN) was a widely used algorithm for image classification in the field of computer *** present,in terms of identification of illegal web pages,the main application methods rely on manpower too much,which is a costly and time-consuming *** paper will apply the CNN algorithm to the identification of illegal networks,build a CNN algorithm framework on the server side of browsers and web *** can also use CNN's outstanding performance in image classification to classify images of illegal websites and conducts realtime data on illegal *** paper will introduce the CNN algorithm characteristics from the algorithm structure and function.

关键词： Illegal Website Convolutional Neural Network Image Classification algorithm structure Application Analysis

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Differential Evolution and Meta-Learning for Dynamic Ensemble of Neural Network Classifiers

Differential Evolution and Meta-Learning for Dynamic Ensembl...

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International Joint Conference on Neural Networks

作者： Tiago P. F. Lima Teresa B. Ludermir Universidade Federal de Pernambuco - Centro de Informática

ISBN: (纸本)9781479919611

Diversity is deemed to be a key issue in classifier combination. For this reason, not every classifier is an expert for every query pattern. Thus, many researchers have focused on dynamic ensemble selection. Most works, however, use only one criterion to perform the dynamic selection. Hence, multiple criteria can provide a decision more effective than the one produced by any of the criteria. Another important issue is accuracy of the classifiers, which strongly depends on the adequate choice of its parameters, including, for example, learning algorithm, structure and input feature vector. Therefore, we present a hybrid intelligent system to generate automatically a pool of classifiers, and choose dynamically an ensemble to predict each query pattern. The method evolves simultaneously the classifier parameters and trains, via a learning algorithm, the candidate solutions. Meta-features are extracted and used to build meta-classifiers to predict whether a base classifier is competent enough to classify the query pattern. Experimental results show that the proposed method improves classification accuracy when compared against current state-of-the-art techniques.

关键词： Evolution Meta-Learning Dynamic Classifiers evolution Evolution dynamic algorithm structure hybrid intelligent system evolution evolution Eigenvector OBSERVATIONAL LEARNING

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