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A Hybrid Wavelet Fuzzy Neural Network and Switching Particle Swarm Optimization Algorithm for AC Servo System

MATHEMATICAL PROBLEMS IN ENGINEERING 2016年第1期2016卷 1-9页

作者： Hou, Run-min Hou, Yuan-long Wang, Chao Gao, Qiang Sun, Hao Nanjing Univ Sci & Technol Dept Mech Engn Nanjing 210094 Jiangsu Peoples R China

Ahybrid computational intelligent approachwhich combineswavelet fuzzy neural network (WFNN) with switching particle swarm optimization (SPSO) algorithm is proposed to control the nonlinearity, wide variation in loads, time variation, and uncertain disturbance of the high-powerACservo system. TheWFNNmethod integratedwavelet transforms with fuzzy rules and is proposed to achieve precise positioning control of the AC servo system. As the WFNN controller, the back-propagation method is used for the online learning algorithm. Moreover, the SPSO is proposed to adapt the learning rates of theWFNN online, where the velocity updating equation is according to aMarkov chain, whichmakes it easy to jump the local minimum, and acceleration coefficients are dependent on mode switching. Furthermore, the stability of the closed loop system is guaranteed by using the Lyapunov method. The results of the simulation and the prototype test prove that the proposed approach can improve the steady-state performance and possess strong robustness to both parameter perturbation and load disturbance.

关键词： computer algorithms PARTICLE swarm optimization FUZZY neural networks ARTIFICIAL intelligence WAVELET transforms

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High impedance fault detection using combination of multi-layer perceptron neural networks based on multi-resolution morphological gradient features of current waveform

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IET GENERATION TRANSMISSION & DISTRIBUTION 2011年第5期5卷 588-595页

作者： Sarlak, M. Shahrtash, S. M. Iran Univ Sci & Technol Dept Elect Engn Ctr Excellence Power Syst Automat & Operat Tehran Iran

In this study a new pattern recognition-based algorithm is presented for detecting high impedance faults (HIFs) in distribution networks with broken or unbroken conductors and distinguishing them from other similar phenomena such as capacitor bank switching, load switching, no-load transformer switching (through feeder switching), fault on adjacent feeders, insulator leakage current (ILC) and harmonic load. The proposed method has employed multi-resolution morphological gradient (MMG) for extraction of the time-based features from three half cycles of the post-disturbance current waveform. Then, according to these features, three multi-layer perceptron neural networks are trained. Finally, the outputs of these classifiers are combined using the average method. Applying the data for HIF, ILC and harmonic load from field tests and for other similar phenomena from simulations has shown high security and dependability of the proposed method. Also, a comparison between the features from the proposed MMG-based procedure and the features from discrete Fourier transform, discrete S-transform, discrete TT-transform and discrete wavelet transform is made in the feature space.

关键词： ELECTRIC fault location ELECTRIC impedance PERCEPTRONS NEURAL networks (computer science) PATTERN recognition systems computer algorithms ELECTRIC networks ELECTRIC conductors

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Improvements in Genomic Technologies: Application to Crop Genomics

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TRENDS IN BIOTECHNOLOGY 2017年第6期35卷 547-558页

作者： Yuan, Yuxuan Bayer, Philipp E. Batley, Jacqueline Edwards, David Univ Western Australia Sch Plant Biol Perth WA Australia

Second-generation sequencing (SGS) has advanced the study of crop genomes and has provided insights into diversity and evolution. However, repetitive DNA sequences in crops often lead to incomplete or erroneous assemblies because SGS reads are too short to fully resolve these repeats. To overcome some of these challenges, long-read sequencing and optical mapping have been developed to produce high-quality assemblies for complex genomes. Previously, high error rates, low throughput, and high costs have limited the adoption of long-read sequencing and optical mapping. However, with recent improvements and the development of novel algorithms, the application of these technologies is increasing. We review the development of long-read sequencing and optical mapping, and assess their application in crop genomics for breeding improved crops.

关键词： CROP genetics NUCLEOTIDE sequence computer algorithms PLANT breeding COST effectiveness

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A Dynamic Impairment-Aware Networking Solution for Transparent Mesh Optical Networks

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IEEE COMMUNICATIONS MAGAZINE 2009年第5期47卷 38-47页

作者： Azodolmolky, Siamak Klonidis, Dimitrios Tomkos, Ioannis Ye, Yabin Saradhi, Chava Vijaya Salvadori, Elio Gunkel, Matthias Manousakis, Kostas Vlachos, Kyriakos Varvarigos, Emmanouel Manos Nejabati, Reza Simeonidou, Dimitra Eiselt, Michael Comellas, Jaume Sole-Pareta, Josep Simonneau, Christian Bayart, Dominique Staessens, Dimitri Colle, Didier Pickavet, Mario Deutsch Telekom Res Ctr Darmstadt Germany Univ Essex High Performance Networked Media Lab Colchester CO4 3SQ Essex England Univ Politecn Cataluna Signal Theory & Communicat Dept E-08028 Barcelona Spain Univ Ghent IBBT INTEC Ghent Belgium

Core networks of the future will have a translucent and eventually transparent optical structure. Ultra-high-speed end-to-end connectivity with high quality of service and high reliability will be realized through the exploitation of optimized protocols and lightpath routing algorithms. These algorithms will complement a flexible control and management plane integrated in the proposed solution. Physical layer impairments and optical performance are monitored and incorporated in impairment-aware lightpath routing algorithms. These algorithms will be integrated into a novel dynamic network planning tool that will consider dynamic traffic characteristics, a reconfigurable optical layer, and varying physical impairment and component characteristics. The network planning tool along with extended control planes will make it possible to realize the vision of optical transparency. This article presents a novel framework that addresses dynamic cross-layer network planning and optimization while considering the development of a future transport network infrastructure.

关键词： computer network architectures NUMERICAL grid generation (Numerical analysis) computer algorithms BANDWIDTHS ROUTING (computer network management) BRILLOUIN scattering ROUTING protocols (computer network protocols) RAMAN effect INTERNETWORKING devices

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DD-SIMCA - A MATLAS GUI tool for data driven SIMCA approach

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CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS 2017年 167卷 23-28页

作者： Zontov, Y. V. Rodionova, O. Ye. Kucheryayskiy, S. V. Pomerantsev, A. L. Natl Res Univ Higher Sch Econ Moscow Russia RAS Semenov Inst Chem Phys Moscow Russia Aalborg Univ Esbjerg Denmark RAS Branch Inst Nat & Tech Syst Soci Russia Fed Inst Ind Property FIPS Moscow Russia

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Performance of gas turbine power plants controlled by the multiagent scheme

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JOURNAL OF ENGINEERING FOR GAS TURBINES AND POWER-TRANSACTIONS OF THE ASME 2007年第3期129卷 738-745页

作者： Dambrosio, Lorenzo Mastrovito, Marco Camporeale, Sergio M. Politecn Bario DIMeG Sez Macchine & Energet I-70125 Bari Italy Polytech Univ DIASS I-74100 Taranto Italy

In recent years the idea of artificial intelligence has been focused around the concept of rational agent. An agent is an (software or hardware) entity that can receive signals from the environment and act upon that environment through output signals, trying to carry out an appropriate task. Seldom agents are considered as stand-alone systems;on the contrary, their main strength can be found in the interaction with other agents, constituting the so-called multiagent system. In the present work, a multiagent system was chosen as a control system of a single-shaft heavy-ditty gas turbine in the multi input multi output mode. The shaft rotational speed (power frequency) and stack temperature (related to the overall gas turbine efficiency) represent the controlled variables;on the other hand, the fuel mass flow (VCE) and the variable inlet guide vanes (VIGV) have been chosen as manipulating variables. The results show that the multiagent approach to the control problem effectively counteracts the load reduction (including the load rejection condition) with limited overshoot in the controlled variables (as other control algorithms do) while showing a good level of adaptivity, readiness, precision, robustness, and stability.

关键词： control systems Environments Standing Orders load rejection Variable computer algorithms Agents turbine efficiency multi-input inlet guide vanes control variable Gas turbine power plants Artificial Intelligence signals heavy duty gas turbine

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Multidimensional Dynamic Programming Algorithm for N-Level Batching with Hierarchical Clustering Structure

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MATHEMATICAL PROBLEMS IN ENGINEERING 2017年第1期2017卷 1-12页

作者： Lim, Seung-Kil Bang, June-Young Kim, Jae-Gon Sungkyul Univ Dept Ind & Management Engn 400-10 Anyang Dong Anyang Si 14097 Gyeonggi Do South Korea Incheon Natl Univ Dept Ind & Management Engn 12-1 Songdo Dong Incheon 22012 South Korea

This study focuses on the N-level batching problem with a hierarchical clustering structure. Clustering is the task of grouping a set of item types in such a way that item types in the same cluster are more similar (in some sense or another) to each other than to those in other clusters. In hierarchical clustering structure, more and more different item types are clustered together as the level of the hierarchy increases. N-level batching is the process by which items with different types are grouped into several batches passed from level 1 to level N sequentially for given hierarchical clustering structure such that batches in each level should satisfy the maximum and minimum batch size requirements of the level. We consider two types of processing costs of the batches: unit processing cost and batch processing cost. We formulate the N-level batching problem with a hierarchical clustering structure as a nonlinear integer programming model with the objective of minimizing the total processing cost. To solve the problem optimally, we propose a multidimensional dynamic programming algorithm with an example.

关键词： BATCH processing in electronic data processing DYNAMIC programming computer algorithms CLUSTER analysis (Statistics) DATA analysis

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Ab initio molecular dynamics with discrete variable representation basis sets: Techniques and application to liquid water

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JOURNAL OF PHYSICAL CHEMISTRY A 2006年第16期110卷 5549-5560页

作者： Lee, HS Tuckerman, ME NYU Dept Chem New York NY 10003 USA NYU Courant Inst Math Sci New York NY 10003 USA

Finite temperature ab initio molecular dynamics (AIMD), in which forces are obtained from "on-the-fly" electronic structure calculations, is a widely used technique for studying structural and dynamical properties of chemically active systems. Recently, we introduced an AIMD scheme based on discrete variable representation (DVR) basis sets, which was shown to have improved convergence properties over the conventional plane wave (PW) basis set [Liu,Y.;et al. Ph)u. Rev. B 2003, 68, 125110]. In the present work, the numerical algorithms for the DVR based AIMD scheme (DVR/AIMD) are provided in detail, and the latest developments of the approach are presented. The accuracy and stability of the current implementation of the DVR/AIMD scheme are tested by performing a simulation of liquid water at ambient conditions. The structural information obtained from the present work is in good agreement with the result of recent AIMD simulations with a PW basis set (PW/AIMD). Advantages of using the DVR/AIMD scheme over the PW/AIMD method are discussed. In particular, it is shown that a DVR/AIMD simulation of liquid water in the complete basis set limit is possible with a relatively small number of grid points.

关键词： BASIS sets (Quantum mechanics) MOLECULAR dynamics WATER ELECTRONIC structure SIMULATION methods & models computer algorithms AIMD algorithms

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An Improved Metric Learning Approach for Degraded Face Recognition

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MATHEMATICAL PROBLEMS IN ENGINEERING 2014年第1期2014卷 1-10页

作者： Zou, Guofeng Zhang, Yuanyuan Wang, Kejun Jiang, Shuming Wan, Huisong Fu, Guixia Shandong Acad Sci Informat Res Inst Jinan 250014 Peoples R China Harbin Engn Univ Coll Automat Harbin 150001 Peoples R China

To solve the matching problem of the elements in different data collections, an improved coupled metric learning approach is proposed. First, we improved the supervised locality preserving projection algorithm and added the within-class and between-class information of the improved algorithm to coupled metric learning, so a novel coupled metric learning method is proposed. Furthermore, we extended this algorithm to nonlinear space, and the kernel coupled metric learning method based on supervised locality preserving projection is proposed. In kernel coupled metric learning approach, two elements of different collections are mapped to the unified high dimensional feature space by kernel function, and then generalized metric learning is performed in this space. Experiments based on Yale and CAS-PEAL-R1 face databases demonstrate that the proposed kernel coupled approach performs better in low-resolution and fuzzy face recognition and can reduce the computing time;it is an effective metric method.

关键词： MACHINE learning HUMAN face recognition (computer science) computer algorithms NONLINEAR theories KERNEL (Mathematics) FUZZY logic

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Low-Complexity Compression Algorithm for Hyperspectral Images Based on Distributed Source Coding

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MATHEMATICAL PROBLEMS IN ENGINEERING 2013年第1期2013卷 1-7页

作者： Nian, Yongjian He, Mi Wan, Jianwei Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China Third Mil Med Univ Sch Biomed Engn Chongqing 400038 Peoples R China Chongqing Univ Chongqing 400038 Peoples R China

A low-complexity compression algorithm for hyperspectral images based on distributed source coding (DSC) is proposed in this paper. The proposed distributed compression algorithm can realize both lossless and lossy compression, which is implemented by performing scalar quantization strategy on the original hyperspectral images followed by distributed lossless compression. Multilinear regression model is introduced for distributed lossless compression in order to improve the quality of side information. Optimal quantized step is determined according to the restriction of the correct DSC decoding, which makes the proposed algorithm achieve near lossless compression. Moreover, an effective rate distortion algorithm is introduced for the proposed algorithm to achieve low bit rate. Experimental results show that the compression performance of the proposed algorithm is competitive with that of the state-of-the-art compression algorithms for hyperspectral images.

关键词： COMPUTATIONAL complexity computer algorithms IMAGE compression HYPERSPECTRAL imaging systems IMAGE quality in imaging systems IMAGE analysis

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