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Journal articles on the topic 'Expansion Algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Xue, Xiaomei, Zhengquan Li, Yongqiang Man, et al. "Improved Massive MIMO RZF Precoding Algorithm Based on Truncated Kapteyn Series Expansion." Information 10, no. 4 (2019): 136. http://dx.doi.org/10.3390/info10040136.

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In order to reduce the computational complexity of the inverse matrix in the regularized zero-forcing (RZF) precoding algorithm, this paper expands and approximates the inverse matrix based on the truncated Kapteyn series expansion and the corresponding low-complexity RZF precoding algorithm is obtained. In addition, the expansion coefficients of the truncated Kapteyn series in our proposed algorithm are optimized, leading to further improvement of the convergence speed of the precoding algorithm under the premise of the same computational complexity as the traditional RZF precoding. Moreover,

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2

Ren, Jin, Jingxing Chen, and Liang Feng. "A Novel Positioning Algorithm Based on Self-adaptive Algorithm of RBF Network." Open Electrical & Electronic Engineering Journal 10, no. 1 (2016): 141–48. http://dx.doi.org/10.2174/1874129001610010141.

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Much attention has been paid to Taylor series expansion (TSE) method these years, which has been extensively used for solving nonlinear equations for its good robustness and accuracy of positioning. A Taylor-series expansion location algorithm based on the RBF neural network (RBF-TSE) is proposed before to the performance of TSE highly depends on the initial estimation. In order to have more accurate and lower cost,a new Taylor-series expansion location algorithm based on Self-adaptive RBF neural network (SA-RBF-TSE) is proposed to estimate the initial value. The proposed algorithm is analysed

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Wang, Pengjun, Zhenhai Wang, Rui Xu, Zhidi Jiang, and Disheng Wang. "Conversion algorithm for MPRM expansion." Journal of Semiconductors 35, no. 3 (2014): 035007. http://dx.doi.org/10.1088/1674-4926/35/3/035007.

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Wise, Christi L., and Justin A. Zakis. "Effects of Expansion Algorithms on Speech Reception Thresholds." Journal of the American Academy of Audiology 19, no. 02 (2008): 147–57. http://dx.doi.org/10.3766/jaaa.19.2.5.

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Expansion is commonly used to reduce microphone noise and low-level environmental noises that can be annoying to hearing aid users. It may also improve or reduce the perception of low-level speech. This study assessed the impact of two expansion algorithms, single and multiple channel, on speech reception thresholds (SRT) with 10 hearing impaired listeners wearing hearing aids with ADRO® processing. The single-channel algorithm suppressed sounds below 45 dB A, while the multiple-channel algorithm suppressed sounds below the long-term average spectrum of speech at either 55 or 45 dB SPL. The me

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Zhao, Yuxue, Hongxin Zhang, Yuanzhen Wang, Chenxu Li, Ruilin Xu, and Chen Yang. "An extended binary subband canonical correlation analysis detection algorithm oriented to the radial contraction-expansion motion steady-state visual evoked paradigm." Brain Science Advances 8, no. 1 (2022): 19–37. http://dx.doi.org/10.26599/bsa.2022.9050004.

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The radial contraction-expansion motion paradigm is a novel steady-state visual evoked experimental paradigm, and the electroencephalography (EEG) evoked potential is different from the traditional luminance modulation paradigm. The signal energy is concentrated chiefly in the fundamental frequency, while the higher harmonic power is lower. Therefore, the conventional steady-state visual evoked potential recognition algorithms optimizing multiple harmonic response components, such as the extended canonical correlation analysis (eCCA) and task-related component analysis (TRCA) algorithm, have p

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Arrag, Sliman, Abdellatif Hamdoun, Abderrahim Tragha, and Salah eddine Khamlich. "Replace AES key expansion algorithm by modified genetic algorithm." Applied Mathematical Sciences 7 (2013): 7161–71. http://dx.doi.org/10.12988/ams.2013.38482.

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Zhang, Zhengwei, Mingjian Zhang, and Liuyang Wang. "Reversible Image Watermarking Algorithm Based on Quadratic Difference Expansion." Mathematical Problems in Engineering 2020 (January 9, 2020): 1–8. http://dx.doi.org/10.1155/2020/1806024.

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To improve the visual quality and embedding rate of existing reversible image watermarking algorithms, a reversible image watermarking algorithm based on quadratic difference expansion is proposed. First, the pixel points with grayscale values 0 and 255 in the original image are removed, and then, the half-scrambled watermark information is embedded into the original image using linear difference expansion. Finally, the remaining half of the watermark information is embedded into the previously generated watermarked image by the quadratic difference expansion, meanwhile the removed pixel point

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Eckerle, Juergen, Jingwei Chen, Nathan Sturtevant, Sandra Zilles, and Robert Holte. "Sufficient Conditions for Node Expansion in Bidirectional Heuristic Search." Proceedings of the International Conference on Automated Planning and Scheduling 27 (June 5, 2017): 79–87. http://dx.doi.org/10.1609/icaps.v27i1.13825.

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In this paper we study bidirectional state space search with consistent heuristics, with a focus on obtaining sufficient conditions for node expansion, that is, conditions characterizing nodes that must be expanded by any admissible bidirectional search algorithm. We provide such conditions for front-to-front and front-to-end bidirectional search. The sufficient conditions are used to prove that the front-to-front bidirectional search algorithm BDS1 is optimally efficient, in terms of node expansion, among a broad class of bidirectional search algorithms, for a specific class of problem instan

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LIM, K. M., E. T. ONG, H. P. LEE, and S. P. LIM. "A FAST BOUNDARY ELEMENT METHOD FOR UNDERWATER ACOUSTICS." Modern Physics Letters B 19, no. 28n29 (2005): 1679–82. http://dx.doi.org/10.1142/s0217984905010207.

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A fast algorithm for the boundary element method is developed to handle problems in underwater acoustics. The algorithm employs the multipole and local expansions to approximate far-field potentials, and exploits the discrete convolution nature of mapping multipole to local expansions to accelerate the potential evaluation process. The speedup in the solution process is achieved by fast Fourier transform on the multipole and local expansion coefficients on a regular grid. The method is demonstrated by a three-dimensional underwater acoustics scattering problem, and it is found to achieve accur

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Dr Bhadresh R. Pandya, Bhumika S. Arora, Dr Vijay Chavda,. "PxEBCA: Proximity Expansion Based Clustering Algorithm." Turkish Journal of Computer and Mathematics Education (TURCOMAT) 12, no. 5 (2021): 852–56. http://dx.doi.org/10.17762/turcomat.v12i5.1494.

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Cluster analysis is one of the main techniques for analysing data. It is a technique for detecting groups of objects which are similar without specifying any criteria for the grouping. The matter of detecting clusters is challenging when the clusters are of varied size, density and shape. DBSCAN can find arbitrary shaped clusters along with outliers but it cannot handle different density. This paper presents a new method for detecting density based clusters which works on datasets having varied density. In this paper we propose PxEBCA that discovers clusters with arbitrary shape and also with

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11

Gen, Mitsuo, and Baoding Lie. "EVOLUTION ALGORITHM FOR OPTIMAL CAPACITY EXPANSION." Journal of the Operations Research Society of Japan 40, no. 1 (1997): 1–9. http://dx.doi.org/10.15807/jorsj.40.1.

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12

Martin, Quentin W. "Hierarchical Algorithm for Water Supply Expansion." Journal of Water Resources Planning and Management 113, no. 5 (1987): 677–95. http://dx.doi.org/10.1061/(asce)0733-9496(1987)113:5(677).

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13

Hosono, Toshio. "Numerical algorithm for Taylor series expansion." Electronics and Communications in Japan (Part I: Communications) 69, no. 6 (1986): 10–18. http://dx.doi.org/10.1002/ecja.4410690602.

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Somchit, Siripat, Sirorat Pattanapairoj, and Rongrit Chatthaworn. "Improved Binary Differential Evolution for Transmission Expansion Planning." E3S Web of Conferences 629 (2025): 06003. https://doi.org/10.1051/e3sconf/202562906003.

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Increasing load and penetrating solar PhotoVoltaic (PV) systems tend higher in the future. Transmission Expansion Planning (TEP) is commonly used to solve this issue and is typically formed by using the peak load scenario, which is often assumed to represent the worst-case condition. Metaheuristic algorithms are predominantly used to address the TEP problem, which is frequently characterized by solutions becoming trapped in local optima. To address this challenge, this study proposes a TEP approach, utilizing an improved Binary Differential Evolution (BDE) algorithm in which the mutation facto

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15

Zhang, Xulong, Zihao Cheng, Li Du, and Yuan Du. "Progressive Classifier Mechanism for Bridge Expansion Joint Health Status Monitoring System Based on Acoustic Sensors." Sensors 23, no. 11 (2023): 5090. http://dx.doi.org/10.3390/s23115090.

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The application of IoT (Internet of Things) technology to the health monitoring of expansion joints is of great importance in enhancing the efficiency of bridge expansion joint maintenance. In this study, a low-power, high-efficiency, end-to-cloud coordinated monitoring system analyzes acoustic signals to identify faults in bridge expansion joints. To address the issue of scarce authentic data related to bridge expansion joint failures, an expansion joint damage simulation data collection platform is established for well-annotated datasets. Based on this, a progressive two-level classifier mec

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AMRANI, OFER, AMIR AVERBUCH, TAMIR COHEN, and VALERY A. ZHELUDEV. "SYMMETRIC INTERPOLATORY FRAMELETS AND THEIR ERASURE RECOVERY PROPERTIES." International Journal of Wavelets, Multiresolution and Information Processing 05, no. 04 (2007): 541–66. http://dx.doi.org/10.1142/s0219691307001896.

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A new class of wavelet-type frames in signal space that uses (anti)symmetric waveforms is presented. The construction employs interpolatory filters with rational transfer functions. These filters have linear phase. They are amenable either to fast cascading or parallel recursive implementation. Robust error recovery algorithms are developed by utilizing the redundancy inherent in frame expansions. Experimental results recover images when (as much as) 60% of the expansion coefficients are either lost or corrupted. The proposed approach inflates the size of the image through framelet expansion a

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Juliandri, M. Zarlis, and Z. Situmorang. "The Expansion of Initial Point Algorithm for K-Modes Algorithm." Journal of Physics: Conference Series 930 (December 2017): 012027. http://dx.doi.org/10.1088/1742-6596/930/1/012027.

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18

Ahmadian, Ali, Ali Elkamel, and Abdelkader Mazouz. "An Improved Hybrid Particle Swarm Optimization and Tabu Search Algorithm for Expansion Planning of Large Dimension Electric Distribution Network." Energies 12, no. 16 (2019): 3052. http://dx.doi.org/10.3390/en12163052.

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Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing the total cost of the objective function with technical constraints make it a combinatorial problem which should be solved by powerful optimization algorithms. In this paper, a new improved hybrid Tabu search/particle swarm optimization algorithm is proposed to optimize the electric expansion planning. The proposed method is analyzed both mathematically and experimentally and it is applied to three different electric distribution networks as case studies. Numerical results and c

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19

S., Hakim, and Fouad M. "Improving Data Integrity in Communication Systems by Designing a New Security Hash Algorithm." Journal of Information Sciences and Computing Technologies 6, no. 2 (2017): 638–47. https://doi.org/10.5281/zenodo.3968224.

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The objective of this paper is to design a new secure hash algorithm with final hash code length 512 bits. The proposed hash code algorithm based on the combination of SHA-256 algorithm -with modification in its message expansion- and MD5algorithm based on double-Davis-Mayer scheme to reduce the weakness existing in these functions. In this paper; we modified message expansion for SHA256 in the proposed algorithm .By using MATLAB, The proposed algorithm has been simulated. And hash code for different messages is obtained using MD5, SHA-256, combination of MD5 and SHA-256 with final hash code l

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Patra, Sabyasachi, and Anjali Mohapatra. "Motif discovery in biological network using expansion tree." Journal of Bioinformatics and Computational Biology 16, no. 06 (2018): 1850024. http://dx.doi.org/10.1142/s0219720018500245.

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Networks are powerful representation of topological features in biological systems like protein interaction and gene regulation. In order to understand the design principles of such complex networks, the concept of network motifs emerged. Network motifs are recurrent patterns with statistical significance that can be seen as basic building blocks of complex networks. Identification of network motifs leads to many important applications, such as understanding the modularity and the large-scale structure of biological networks, classification of networks into super-families, protein function ann

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21

Zhang, Zhengwei, Lifa Wu, Yunyang Yan, Shaozhang Xiao, and He Sun. "An improved reversible image watermarking algorithm based on difference expansion." International Journal of Distributed Sensor Networks 13, no. 1 (2017): 155014771668657. http://dx.doi.org/10.1177/1550147716686577.

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To improve the visual quality and the embedding rate of the existing reversible image watermarking algorithm, an improved reversible image watermarking algorithm based on difference expansion is proposed. First, the watermark information is divided into groups, and the information value of each group is calculated. The watermark group number and the corresponding carrier image block number are mapped, and the corresponding coefficient position of each corresponding carrier block is identified according to the value of the watermark information in each group. Second, the identified location map

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22

Wang, Huanwei, Shangjie Lou, Jing Jing, Yisen Wang, Wei Liu, and Tieming Liu. "The EBS-A* algorithm: An improved A* algorithm for path planning." PLOS ONE 17, no. 2 (2022): e0263841. http://dx.doi.org/10.1371/journal.pone.0263841.

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Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the traditional A* algorithm has some limitations, such as slow planning speed, close to obstacles. In this paper, we propose an improved A*-based algorithm, called the EBS-A* algorithm, that introduces expansion distance, bidirectional search, and smoothing into path planning. The expansion distance means keeping an extra space from obstacles to improve path reliability by avoiding collisions. Bidirectional search is a strategy searching path from

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23

Wang, Huanwei, Xuyan Qi, Shangjie Lou, Jing Jing, Hongqi He, and Wei Liu. "An Efficient and Robust Improved A* Algorithm for Path Planning." Symmetry 13, no. 11 (2021): 2213. http://dx.doi.org/10.3390/sym13112213.

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Path planning plays an essential role in mobile robot navigation, and the A* algorithm is one of the best-known path planning algorithms. However, the conventional A* algorithm and the subsequent improved algorithms still have some limitations in terms of robustness and efficiency. These limitations include slow algorithm efficiency, weak robustness, and collisions when robots are traversing. In this paper, we propose an improved A*-based algorithm called EBHSA* algorithm. The EBHSA* algorithm introduces the expansion distance, bidirectional search, heuristic function optimization and smoothin

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LIU, ZAIWEN, XIAOYI WANG, and LIFENG CUI. "AN INTELLIGENT SOFT MEASUREMENT METHOD FOR PREDICTING PARAMETERS." International Journal of Information Acquisition 04, no. 01 (2007): 47–56. http://dx.doi.org/10.1142/s0219878907001150.

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An intelligent soft measurement and information processing method for predicting parameters of process control system was proposed. Process neural network (PNN) is a new configuration of artificial neural network put forward in recent years. Some algorithms of PNN were discussed, and these algorithms were based on function orthogonal basis expansion, yet the convergence rate was comparatively low. An improved algorithm for raising training speed based on function orthogonal basis expansion in PNN for soft measurement was researched. After increasing the normalizing rule on the original algorit

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25

Gong, Jian Hong, Bo Li, and Xiao Guang Gao. "A Bidirectional Quintuple Tree Node Expansion Algorithm for UAV Path Planning in Dynamic Environment." Advanced Materials Research 765-767 (September 2013): 413–16. http://dx.doi.org/10.4028/www.scientific.net/amr.765-767.413.

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To deal with the problem of penetration trajectory planning for UAV security issues, an improved bidirectional quintuple tree node expansion algorithm is proposed. Compare to traditional quintuple tree node expansion algorithm, the proposed algorithm could reduce the number of the expanded tree node, and it makes the bidirectional quintuple tree node expansion algorithm more efficient in path planning. By combining the bidirectional quintuple tree node expansion algorithm with multi-step optimization search mechanism, a kind of real-time UAV path planning algorithm is presented.

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Simons, Stuart, and Andrew Tworkowski. "A new algorithm for computing the logarithmic function." Mathematical Gazette 89, no. 515 (2005): 212–21. http://dx.doi.org/10.1017/s0025557200177617.

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The values of many functions, for example sinx or cosx, can be computed efficiently for arbitrary values of x from their known power series expansions. However, for the logarithmic function this is not so straightforward. There does not exist an expansion of ln x as a power series in x, the closest to it mathematically being an infinite power series in of the formwhere (see [1]).

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Zhao, Wei, Ao Tan, and Congcong Ren. "An Innovative Path Planning Algorithm for Complex Obstacle Environments with Adaptive Obstacle Density Adjustment: AODA-PF-RRT*." Electronics 13, no. 20 (2024): 4047. http://dx.doi.org/10.3390/electronics13204047.

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To address the limitations of low node utilization and inadequate adaptability in complex environments encountered by Rapidly-exploring Random Tree (RRT) algorithms during the expansion phase, this study presents an enhanced path planning algorithm—AODA-PF-RRT* (Adaptive Obstacle Density Adjustment-PF-RRT*). The proposed algorithm implements a random extension strategy for nodes that fail collision detection, thereby improving node efficiency. Furthermore, it dynamically partitions the area surrounding sampling points and calculates local obstacle density in real time. By leveraging this densi

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Han, Shao Jin, and Jian Xun Li. "Bayesian Network Structure Learning Based on Probability Density Kernel Estimation." Applied Mechanics and Materials 427-429 (September 2013): 1614–19. http://dx.doi.org/10.4028/www.scientific.net/amm.427-429.1614.

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The traditional structure learning algorithms are mainly faced with a large sample dataset. But the sample dataset practically is small. Based on it, we introduce the Probability Density Kernel Estimation (PDKE), which would achieve the expansion of the original sample sets. Then, the K2 algorithm is used to learn the Bayesian network structure. By optimizing the kernel function and window width, PDKE achieves the effective expansion of the original dataset. After the confirm of variable order based on mutual information, a small sample set of Bayesian structure learning algorithm would be est

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29

Bairagi, Mithun. "A New Algorithm to Determine Adomian Polynomials for Nonlinear Polynomial Functions." Asian Research Journal of Mathematics 19, no. 7 (2023): 1–12. http://dx.doi.org/10.9734/arjom/2023/v19i7670.

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We present a new algorithm by which the Adomian polynomials can be determined for scalar-valued nonlinear polynomial functional in a Hilbert space. This algorithm calculates the Adomian polynomials without the complicated operations such as parametrization, expansion, regrouping, differentiation, etc. The algorithm involves only some matrix operations. Because of the simplicity in the mathematical operations, the new algorithm is faster and more efficient than the other algorithms previously reported in the literature. We also implement the algorithm in the MATHEMATICA code. The computing spee

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TAKAHASHI, AKIHIKO, and MASASHI TODA. "NOTE ON AN EXTENSION OF AN ASYMPTOTIC EXPANSION SCHEME." International Journal of Theoretical and Applied Finance 16, no. 05 (2013): 1350031. http://dx.doi.org/10.1142/s0219024913500313.

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This paper presents an extension of a general computational scheme for asymptotic expansions proposed in earlier works by the authors and coworkers. In the earlier works, a new method was developed for the computation of an arbitrary-order expansion with a normal benchmark distribution in a multidimensional diffusion setting. In particular, a new algorithm was proposed for calculating coefficients in an expansion by solving a system of ordinary differential equations. In the present note, by a change of variable technique, and by various ways of setting the perturbation parameters in the expan

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Escobar Z., Antonio H., Ramón A. Gallego R., and Rubén A. Romero L. "Using traditional heuristic algorithms on an initial genetic algorithm population applied to the transmission expansion planning problem." Ingeniería e Investigación 31, no. 1 (2011): 127–43. http://dx.doi.org/10.15446/ing.investig.v31n1.20534.

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This paper analyses the impact of choosing good initial populations for genetic algorithms regarding convergence speed and final solution quality. Test problems were taken from complex electricity distribution network expansion planning. Constructive heuristic algorithms were used to generate good initial populations, particularly those used in resolving transmission network expansion planning. The results were compared to those found by a genetic algorithm with random initial populations. The results showed that an efficiently generated initial population led to better solutions being found i

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YU, Shengsheng. "Algorithm of capacity expansion on networks optimization." Chinese Science Bulletin 48, no. 10 (2003): 1048. http://dx.doi.org/10.1360/02ww0300.

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McInroy, Justin, and Sergey Shpectorov. "An expansion algorithm for constructing axial algebras." Journal of Algebra 550 (May 2020): 379–409. http://dx.doi.org/10.1016/j.jalgebra.2019.12.018.

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Yu, Shengsheng, Yuhua Liu, Jingzhong Mao, and Kaihua Xu. "Algorithm of capacity expansion on networks optimization." Chinese Science Bulletin 48, no. 10 (2003): 1048–50. http://dx.doi.org/10.1007/bf03184225.

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Kružík, J., D. Horák, M. Čermák, L. Pospíšil, and M. Pecha. "Active set expansion strategies in MPRGP algorithm." Advances in Engineering Software 149 (November 2020): 102895. http://dx.doi.org/10.1016/j.advengsoft.2020.102895.

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Li, Xiangyang, Rong Li, Qiang Huang, and Jiangao Luo. "Minimized-expansion based lossless image authentication algorithm." Journal of Ambient Intelligence and Humanized Computing 6, no. 6 (2015): 845–54. http://dx.doi.org/10.1007/s12652-015-0320-9.

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De Oliveira, E. J., C. A. Moraes, L. W. Oliveira, L. M. Honório, and R. P. B. Poubel. "Efficient hybrid algorithm for transmission expansion planning." Electrical Engineering 100, no. 4 (2018): 2765–77. http://dx.doi.org/10.1007/s00202-018-0744-2.

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Zein, Samih, Benoît Colson, and François Glineur. "An Efficient Sampling Method for Regression-Based Polynomial Chaos Expansion." Communications in Computational Physics 13, no. 4 (2013): 1173–88. http://dx.doi.org/10.4208/cicp.020911.200412a.

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AbstractThe polynomial chaos expansion (PCE) is an efficient numerical method for performing a reliability analysis. It relates the output of a nonlinear system with the uncertainty in its input parameters using a multidimensional polynomial approximation (the so-called PCE). Numerically, such an approximation can be obtained by using a regression method with a suitable design of experiments. The cost of this approximation depends on the size of the design of experiments. If the design of experiments is large and the system is modeled with a computationally expensive FEA (Finite Element Analys

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Abidin, Taufik Fuadi, Amir Mahazir, Muhammad Subianto, Khairul Munadi, and Ridha Ferdhiana. "Recognizing Indonesian Acronym and Expansion Pairs with Supervised Learning and MapReduce." Information 11, no. 4 (2020): 210. http://dx.doi.org/10.3390/info11040210.

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During the previous decades, intelligent identification of acronym and expansion pairs from a large corpus has garnered considerable research attention, particularly in the fields of text mining, entity extraction, and information retrieval. Herein, we present an improved approach to recognize the accurate acronym and expansion pairs from a large Indonesian corpus. Generally, an acronym can be either a combination of uppercase letters or a sequence of speech sounds (syllables). Our proposed approach can be computationally divided into four steps: (1) acronym candidate identification; (2) acron

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Singthongla, Patiwat, and Narakorn Rompurk Kanasri. "SEL Series Expansion and Generalized Model Construction for the Real Number System via Series of Rationals." International Journal of Mathematics and Mathematical Sciences 2014 (2014): 1–8. http://dx.doi.org/10.1155/2014/654319.

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We present an algorithm for constructing infinite series expansion for real numbers, which yields generalized versions of three famous series expansions, namely, Sylvester series, Engel series, and Lüroth series expansions. Using series of rationals, a generalized model for the real number system is also constructed.

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Geng, Hui. "Modified A* algorithm for path smoothing and obstacle avoidance." Applied and Computational Engineering 33, no. 1 (2024): 167–75. http://dx.doi.org/10.54254/2755-2721/33/20230262.

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With the rapid development of robotics technology, path planning is a crucial aspect of autonomous robot systems. Among them, planning paths involves using the A* algorithm, which is a common method. However, traditional A* algorithm has several limitations in path planning, such as poor real-time performance, large amount of computation per node, long computation time, low algorithmic search efficiency. Based on this, two improved approaches for the A* algorithm are proposed. The first is expanding the obstacles in the map by increasing their expansion radius. The second is the Hybrid A* algo

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Jayasudha, R., S. Subramanian, and L. Sivakumar. "Genetic Algorithm and PSO Based Intelligent Software Reuse." Applied Mechanics and Materials 573 (June 2014): 612–17. http://dx.doi.org/10.4028/www.scientific.net/amm.573.612.

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Software Reuse can improve the development time, cost and quality of Software artifacts. The Storage of artifacts plays an important role of easy retrieval of the needed components according to the requirement. In this paper a great measure has been taken for the retrieval of relevant component from the Ontology based repository. Two famous evolutionary algorithms Genetic Algorithm and Particle Swarm Optimization algorithm were used for extraction of needed component. These two algorithms are separately used for component retrieval. Genetic Algorithm in Component Retrieval is best suited if th

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Aman, Rawat Pradeep Gehlot Vishal Thakuria And Deepak Garg. "A HYBRID GENETIC ALGORITHM FOR THE LONGEST COMMON SUB-SEQUENCE OF MULTIPLE SEQUENCES." INTERNATIONAL JOURNAL OF ENGINEERING SCIENCES & RESEARCH TECHNOLOGY 6, no. 10 (2017): 391–98. https://doi.org/10.5281/zenodo.1012555.

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Finding the longest common subsequence for multiple sequences are knows as k-LCS. For significant number and longer length sequences the k-LCS turns out to be a NP-hard problem. To solve this problem, we have developed a hybrid genetic algorithm that can be used to find an optimal solution in comparatively less time. The results obtained by our solution are comparatively better than that of EA (Expansion-algorithm), BNMAS(Best next maximal available symbol algorithm.), GA(Genetic algorithm) and ACO(Ant colony optimization algorithm). Using Hill Climbing along with Genetic Algorithm proved to b

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GHINCULOV, ADRIAN, and YORK-PENG YAO. "MOMENTUM EXPANSION OF MASSIVE TWO-LOOP FEYNMAN GRAPHS AROUND A FINITE VALUE." Modern Physics Letters A 15, no. 07 (2000): 509–15. http://dx.doi.org/10.1142/s0217732300000499.

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We give an algorithm for obtaining expansions of massive two-loop Feynman graphs in powers of the external momentum around a finite, nonzero value of the momentum. Such momentum derivatives are encountered while evaluating physical radiative corrections, such as in wave function renormalization constants. This is based on our general two-loop formalism to reduce massive two-loop graphs with renormalizable interactions into a standard set of special functions. After the algebraic reduction, the final results are obtained by numerical integration. We apply the expansion algorithm to treat the to

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Messa, Frederico, and André Grahl Pereira. "PEA*+IDA*: An Improved Hybrid Memory-Restricted Algorithm." Proceedings of the AAAI Conference on Artificial Intelligence 36, no. 9 (2022): 10291–98. http://dx.doi.org/10.1609/aaai.v36i9.21270.

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It is well-known that the search algorithms A* and Iterative Deepening A* (IDA*) can fail to solve state-space tasks optimally due to time and memory limits. The former typically fails in memory-restricted scenarios and the latter in time-restricted scenarios. Therefore, several algorithms were proposed to solve state-space tasks optimally using less memory than A* and less time than IDA*, such as A*+IDA*, a hybrid memory-restricted algorithm that combines A* and IDA*. In this paper, we present a hybrid memory-restricted algorithm that combines Partial Expansion A* (PEA*) and IDA*. This new al

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Li, Xu, and Qiming Sun. "Detect Overlapping Community Based on the Combination of Local Expansion and Label Propagation." Algorithms 14, no. 8 (2021): 237. http://dx.doi.org/10.3390/a14080237.

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It is a common phenomenon in real life that individuals have diverse member relationships in different social clusters, which is called overlap in the science of network. Detecting overlapping components of the community structure in a network has extensive value in real-life applications. The mainstream algorithms for community detection generally focus on optimization of a global or local static metric. These algorithms are often not good when the community characteristics are diverse. In addition, there is a lot of randomness in the process of the algorithm. We proposed a algorithm combinin

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Daumas, Marc, and Claire Finot. "Division of Floating Point Expansions with an Application to the Computation of a Determinant." JUCS - Journal of Universal Computer Science 5, no. (6) (1999): 323–38. https://doi.org/10.3217/jucs-005-06-0323.

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Floating point expansion is a technique for implementing multiple precision using a processor's floating point unit instead of its integer unit. Research on this subject has arised recently from the observation that the floating point unit becomes a more and more efficient part of modern computers. Many simple arithmetic operators and some very useful geometric operators have already been presented on expansions. Yet previous work included only a very simple division algorithm. We present in this work a new algorithm that allows us to extend the set of geometric operators with Bareiss' determi

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Li, Haotian, Haisong Han, and Puyan Huang. "FE-RRT*: Forward Expansion RRT* Enhanced Space Exploitation and Informed Subset Convergence." Electrotehnica, Electronica, Automatica 72, no. 3 (2024): 35–43. http://dx.doi.org/10.46904/eea.23.72.3.1108004.

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Path planning is an important part of decision making, and high-quality planning results will dramatically improve work efficiency. This study delves into the realm of motion planning for intelligent mobile robots. The research addresses the challenges of reverse growth branches and redundant nodes in sampling algorithms, proposing the Forward Expansion RRT* (FE-RRT*) algorithm as a solution. By integrating strategies to enhance space exploitation efficiency and optimize heuristic, the FE-RRT* algorithm outperforms RRT*-Connect and Informed RRT*-Connect. Experimental results show the algorithm

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Abdi, Hamdi, Mansour Moradi, and Sara Lumbreras. "Metaheuristics and Transmission Expansion Planning: A Comparative Case Study." Energies 14, no. 12 (2021): 3618. http://dx.doi.org/10.3390/en14123618.

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Transmission expansion planning (TEP), the determination of new transmission lines to be added to an existing power network, is a key element in power system planning. Using classical optimization to define the most suitable reinforcements is the most desirable alternative. However, the extent of the under-study problems is growing, because of the uncertainties introduced by renewable generation or electric vehicles (EVs) and the larger sizes under consideration given the trends for higher renewable shares and stronger market integration. This means that classical optimization, even using effi

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Pan, Gang, Di Sun, Yarui Chen, and Chuanlei Zhang. "Multiresolution Rotational Symmetry Detection via Radius-Based Frieze-Expansion." Journal of Electrical and Computer Engineering 2016 (2016): 1–8. http://dx.doi.org/10.1155/2016/5683632.

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Rotational symmetry is important for many applications in computer graphics, vision, and image processing. However, it remains difficult to design an effective algorithm for automatic symmetry recognition. In this paper, we present a rotational symmetry detection algorithm, which is easy to use and can determine both the center and the radius of the rotational symmetry supporting region without human interaction. Our algorithm is derived from frieze-expansions approach and improved through a radius-based expansion idea. Multiresolution pyramid is used to accelerate this detection process. We a

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