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2nd International Conference on Computer and Automation Engineering (ICCAE)

作者： Xiao, Shunwen Chen, Yajun Luo, Peng CWNU Coll Phys & Elect Informat Nanchong 637002 Sichuan Peoples R China

ISBN: (纸本)9781424455690

When the da (distributed arithmetic) algorithm is directly applied in FPGA (field programmable gate array) to realize FIR (finite impulse response) filter, it is difficult to achieve the best configuration in the coefficient of FIR filter, the storage resource and the computing speed. According to this problem, the paper provides the detailed analysis and discussion in the algorithm, the memory size and the look- up table speed. Also, the corresponding optimization and improvement measures are discussed and the concrete hardware realization of the circuit is presented. The design based on Altera EP2C5T144C8 chips is synthesized under the integrated environment of QUARTUS II 7.1. The results of simulation and test show that this method greatly reduces the FPGA hardware resource and the high speed filtering is achieved. The design has a big breakthrough compared to the traditional FPGA realization.

关键词： FIR filter da algorithm FPGA

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Two novel neural-evolutionary predictive techniques of dragonfly algorithm (da) and biogeography-based optimization (BBO) for landslide susceptibility analysis

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GEOMATICS NATURAL HAZARDS & RISK 2019年第1期10卷 2429-2453页

作者： Moayedi, Hossein Osouli, Abdolreza Dieu Tien Bui Foong, Loke Kok Hoang Nguyen Kalantar, Bahareh Ton Duc Thang Univ Dept Management Sci & Technol Dev Ho Chi Minh City Vietnam Ton Duc Thang Univ Fac Civil Engn Ho Chi Minh City Vietnam Southern Illinois Univ Edwardsville Civil Engn Dept Edwardsville IL USA Duy Tan Univ Inst Res & Dev Da Nang 550000 Vietnam Univ South Eastern Norway Dept Business & IT Geog Informat Syst Grp Bo I Telemark Norway Univ Teknol Malaysia Fac Engn Johor Baharu Johor Malaysia Hanoi Univ Min & Geol Dept Surface Min Hanoi Vietnam Hanoi Univ Min & Geol Ctr Min Electromech Res Hanoi Vietnam RIKEN Ctr Adv Intelligence Project Goal Oriented Technol Res Grp Disaster Resilience Sci Team Tokyo Japan

Due to the wide application of evolutionary science in different engineering problems, the main aim of this paper is to present two novel optimizations of multi-layer perceptron (MLP) neural network, namely dragonfly algorithm (da) and biogeography-based optimization (BBO) for landslide susceptibility assessment at a study area, West of Iran. Utilizing 14 landslide conditioning factors, namely elevation, slope aspect, plan curvature, profile curvature, soil type, lithology, distance to the river, distance to the road, distance to the fault, land cover, slope degree, stream power index (SPI), and topographic wetness index (TWI) and rainfall as the input variables, and 208 historical landslides as target variable, the required spatial database is created. Then, the MLP is synthesized with the mentioned algorithms to develop the proposed da-MLP and BBO-MLP ensembles. Three accuracy criteria of mean square error, mean absolute error, and area under the receiving operating characteristic curve are used to evaluate the performance of the models and also to develop a score-based ranking system. As the first outcome, the application of the da and BBO metaheuristic algorithms enhances the accuracy of the MLP. Moreover, referring to the calculated total ranking scores of 6, 14, and 16, it was revealed that the BBO performs more efficiently than da in optimizing the MLP.

关键词： Landslide susceptibility mapping artificial neural network da algorithm BBO algorithm

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Kinetic parameters estimation via dragonfly algorithm (da) and comparison of cylindrical and spherical reactors performance for CO2 hydrogenation to hydrocarbons

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ENERGY CONVERSION AND MANAGEMENT 2020年 226卷 113550-113550页

作者： Najari, Sara Saeidi, Samrand Grof, Gyula Keil, Frerich J. Rodrigues, Alirio E. Budapest Univ Technol & Econ Fac Mech Engn Dept Energy Engn Budapest Hungary Tech Univ Carolo Wilhelmina Braunschweig Inst Energy & Proc Syst Engn Franz Liszt Str 35 D-38106 Braunschweig Germany Hamburg Univ Technol Inst Chem React Engn D-21073 Hamburg Germany Univ Porto Fac Engn Lab Separat & React Engn Lab Catalysis & Mat LSRE LCMAssociate Lab LSRE L Rua Dr Roberto Frias P-4200465 Porto Portugal

Climate change and global warming, as well as growing global demand for hydrocarbons in industrial sectors, make great incentives to investigate the utilization of CO2 for hydrocarbons production. Therefore, finding an indepth understanding of the CO2 hydrogenation reactors along with simulating reactor responses to different operating conditions are of paramount importance. However, the reaction mechanisms for CO2 hydrogenation and their corresponding kinetic parameters have been disputable yet. In this regard, considering the previously proposed Langmuir-Hinshelwood-Hougen-Watson (LHHW) mechanism, which considered CO2 hydrogenation as a combination of reverse water gas shift (RWGS) and Fischer-Tropsch (FT) reactions, and using a onedimensional pseudo-homogeneous non-isothermal model, kinetic parameters of the rate expressions are estimated via fitting experimental and modelling data through a novel swarm intelligence optimization technique called dragonfly algorithm (da). The predicted reactants conversion using da algorithm are closer to the experimental data (with about 4% error) comparing to those obtained by the artificial bee colony (ABC) algorithm, and are in significant agreement with available literature data. The proposed model is used to assess the effect of reactor configuration on the performance and temperature fluctuations. Results show that axial flow spherical reactor (AFSR) and radial flow spherical reactor (RFSR) exhibiting the same surface area with that of the cylindrical reactor (CR), i.e., AFSR-2 and RFSR-2-i are the most efficient exhibiting hydrocarbons selectivity of 40.330% and 40.286% at CO2 conversion of 53.763% and 53.891%. In addition, it is revealed that the location of the jacket has an essential role in controlling the reactor temperature.

关键词： CO2 hydrogenation Optimization da algorithm Cylindrical reactor Axial and radial flow spherical reactor

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A divide and agglomerate algorithm for community detection in social networks

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INFORMATION SCIENCES 2019年 482卷 321-333页

作者： Liu, Zhiyuan Ma, Yinghong Shandong Normal Univ Sch Business Jinan 250014 Shandong Peoples R China

Communities, or clusters, are usually subgraphs of nodes densely interconnected but sparsely linked with others. The nodes with similar properties or behaviors are more likely to be in the same community, and vice versa. However, due to the complexity and diversity of networks, the accurate organization or function of communities in many real networks is often extremely difficult to be recognized. Hence, methods for community detection would have immediate impact on understanding the organizations and functions of networks. Therefore, algorithm design becomes a fundamental problem for many networks. In this paper, the local and global information are applied together to propose a divide and agglomerate (da) algorithm for community detection in social networks. The da algorithm achieves the result with a two-stage strategy: Dividing a network into small groups according to node pairs' similarities, and merging a group with the other who has the biggest attraction for it until the community criterion is steady. The novel similarity, constrained AA index captures the local and global information ensuring the optimal communities detection. The results of experiments show that da algorithm obtains superior community results compared with six other widely used algorithms, which indicate that da algorithm has advantages for community detection. (C) 2019 Elsevier Inc. All rights reserved.

关键词： Community detection da algorithm Constrained AA index Attraction index

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A note on the binomial model with simplex constraints

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COMPUTATIONAL STATISTICS & daTA ANALYSIS 2011年第12期55卷 3381-3385页

作者： Tian, Guo-Liang Ng, Kai Wang Yu, Philip L. H. Univ Hong Kong Dept Stat & Actuarial Sci Hong Kong Hong Kong Peoples R China

Liu (2000) considered maximum likelihood estimation and Bayesian estimation in a binomial model with simplex constraints using the expectation-maximization (EM) and data augmentation (da) algorithms. By introducing latent variables {Z(ij)} and {Y(ij)} (to be defined later), he formulated the constrained parameter problem into a missing data problem. However, the derived da algorithm does not work because he actually assumed that the {Y(ij)} are known. Furthermore, although the final results from the derived EM algorithm are correct, his findings are based on the assumption that the {Y(ij)} are observable. This note provides a correct da algorithm. In addition, we obtained the same E-step and M-step under the assumption that the (Y(ij)) are unobservable. A real example is used for illustration. (C) 2011 Elsevier B.V. All rights reserved.

关键词： Constrained binomial model da algorithm EM algorithm Simplex constraints

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Optimized Implementation of Discrete Wavelet Transform with Area Efficiency

Optimized Implementation of Discrete Wavelet Transform with ...

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IEEE International Multi Conference on Automation, Computing, Control, Communication and Compressed Sensing (iMac4s)

作者： John, Sani Jose, Manu Viswajyothi Coll Engn & Technol Vazhakkulam ECE Dept Muvattupuzha Kerala India

ISBN: (纸本)9781467350907;9781467350891

The objective of this paper is to illustrate a comparative study on the performance of DWT with the multiplier reducing algorithms. The optimization techniques were based on the identification of algorithms, which could exploit the FPGA features. Discrete Wavelet Transform (DWT) is one of the most used techniques for image compression and is applied in a large category of applications for multi resolution analysis of signals. DWT can provide significant compression ratios without great loss of visual quality than the previous techniques such as the Discrete Cosine Transform (DCT) and the Discrete Fourier Transform (DFT). This work provides an analysis between the conventional VLSI implementation techniques as against an area efficient realization approach. This is expected to provide a reduction in hardware complexity and also an increase in computational speed. The reduction in the resource utilization improves the system performance by means of reduction in power consumption as well as the reduction in delay.

关键词： da algorithm DWT SA algorithm

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Multi-antenna Compressed Wideband Spectrum Sensing for Cognitive Radio

Multi-antenna Compressed Wideband Spectrum Sensing for Cogni...

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IEEE Wireless Communications and Networking Conference (WCNC)

作者： Yang, Xianjun Cui, Qimei Yang, Rui Tao, Xiaofeng Guo, Xin Beijing Univ Posts & Telecommun Wireless Technol Innovat Inst Key Lab Universal Wireless Commun Minist Educ Beijing 100088 Peoples R China Sony China Res Lab Beijing Peoples R China

ISBN: (纸本)9781612842547

This paper proposes a novel wideband spectrum sensing (WSS) scheme, termed multi-antenna compressed wideband spectrum sensing (MCWSS) scheme, which utilizes compressed sensing (CS) to reduce the extremely high sampling rate of wideband signal. Although there are studies on compressed wideband spectrum sensing, they only focus on single antenna signal. Since multi-antenna technology can enhance the detection performance, this paper investigates the multi-antenna scenario. However, existing CS recovery algorithms are designed only for single antenna signal and are not suitable for recovering multi-antenna signals. Therefore, the paper proposes two novel CS recovery algorithms from different angles, namely CRL2 (combining relevance via L-2 norm) algorithm and CBS (combining before sampling) algorithm. The CRL2 algorithm jointly recovers the multi-antenna signals and performs better than single antenna scenario. Whereas, CBS algorithm can significantly improves the recovery performance with an additional analog combining operation. Since existing WSS algorithms are too complicated, we devise a novel WSS algorithm, i.e. da (divided-averaged) algorithm, which has good performance with low complexity. Simulation results show that the MCWSS scheme performs well at low sampling rate.

关键词： algorithm design and analysis Antennas CBS algorithm CRL2 algorithm CS recovery algorithms da algorithm MCWSS scheme Sensors Signal to noise ratio Simulation Wideband antenna arrays cognitive radio cognitive radio combining before sampling algorithm divided-averaged algorithm multiantenna compressed wideband spectrum sensing single antenna signal

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Optimized Implementation of Discrete Wavelet Transform with Area Efficiency

Optimized Implementation of Discrete Wavelet Transform with ...

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International Multi-Conference on Automation, Computing, Communication, Control and Compressed Sensing

作者： Sani John Manu Jose ECE Department Viswajyothi College of Engineering and Technology Vazhakkulam Muvattupuzha Kerala India

ISBN: (纸本)9781467350891

关键词： da algorithm DWT SA algorithm

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