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Examining a modified algorithm of smoothed particle hydrodynamics for a high velocity perforation of an aluminum beam

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MECCANICA 2013年第7期48卷 1623-1636页

作者： Namini, Vahab Haghighat Amanifard, Nima Darvizeh, Aboulfazl Mohamadi, Katayoon Univ Guilan Dept Mech Engn Fac Engn Rasht Iran

The wide spreading of utilizing of smoothed particle hydrodynamics (SPH) for numerical studies of the complex and high rate deformations of continuums, led the current study to gain a more reliable simulation by employing a modified compressible smoothed particle hydrodynamics (MCSPH) algorithm which could be a more accurate and stable technique in high tension regions, in despite of incompressible standard SPH. The main feature of the modified compressible SPH algorithm relies on a three steps solution procedure to calculate the pressure gradient, the deviatoric stress tensor, and the body forces separately. This algorithm is free of any artificial viscosity in its formulations, as well as welcoming to compressible effects which permits the pressure shock waves in high rate plastic deformation. To examine the accuracy of the algorithm, a benchmark problem of colliding rubber cylinders was simulated first and then a high velocity perforation process of an aluminum beam struck by a rigid projectile was simulated in various projectile speeds, and the failure response of the beam in each case was accompanied by crack propagation process. The prominent capability of the utilized MCSPH can be more illustrated when it was used in simulation of thickness crack propagation a tiny crack paths and defragmentation which can be encountered as a not easy numerical case study. The adequate assurance has been more fortified when the results were compared to those reported from a Finite Element method study.

关键词： Smoothed particle hydrodynamics modified algorithm High velocity perforation

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Optimization of the compression ratio of the modified algorithm of decomposition electromyographic signals by a superimposed coding 10

Optimization of the compression ratio of the modified algori...

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International Conference on Signal-Image Technology and Internet-Based Systems SITIS

作者： Oyobe-Okassa, Aime Joseph Ele, Pierre EPM Masuku Franceville Gabon ENSP UYde Yaounde Cameroon ENSP UYde Douala Cameroon IUT UDla Yaounde Cameroon IUT UDla Douala Cameroon

ISBN: (纸本)9781479979783

The purpose of the compression is the minimization of the data storage space, the transmission time or the bandwidth. If the wavelets and specifically wavelets packets bases provide an appropriate framework for the selection of an optimal representation of electromyographic (EMG) signals, the choice of encoding method optimizes the compression ratio without altering the compressed data. In compression, it is usual to fix as goal either a compression ratio to achieve or a minimum acceptable quality of the reconstructed signal. In this work, the novelty is that we have obtained the compression ratio without fixing anything;and the results obtained are better than those given by the modified compression algorithm proposed in [6] as association of coding methods was not used there.

关键词： modified algorithm delta coding multiresolution compression wavelets

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Economical design of H-bridge multilevel inverter drive controlled by modified fast algorithm

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MICROELECTRONICS RELIABILITY 2016年 65卷 89-97页

作者： Mohammed, Jamal Abdul-Kareem Univ Technol Baghdad Dept Electromech Engn Baghdad Iraq

Traditional cascaded multilevel inverter needs n DC voltage sources to give 2n + 1 levels. As number of levels increased, the amount of switching devices, their proper related drive circuits and their controllers and other components are also increased excessively, making the inverter more complex and costly. A simple and low cost single-phase cascade multilevel inverter with no transformers can be implemented using only single-DC source with n-1 DC sources represented by capacitors and with reduced switches. So, current inverter hardware cost can be reduced abruptly as compared with conventional one. When the number of DC sources is increased, inverter output has higher harmonic content characterized by their transcendental equations that become more complicated and required more time to be solved. New technique is exhibited to find the inverter switching angles by executing modified fast recursive algorithm providing an on-line precise solution for the Harmonic Elimination (HE) problem. The suggested optimized algorithm technique have been used to find optimum switching angles necessary to eliminate any number of lowest order harmonics and maintain the desired fundamental voltage for driving an AC motor. Simulation results of cascade 7-level inverter with single-DC source under the optimized HE stepped waveform technique is used to eliminate the 3rd and 5th harmonics. Prototype design for the proposed inverter loaded by single-phase fan motor is built. (C) 2016 Published by Elsevier Ltd.

关键词： DC source Cost Multilevel inverter Harmonics elimination modified algorithm

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Estimation of shale pore-size-distribution from N2 adsorption characteristics employing modified BJH algorithm

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PETROLEUM SCIENCE AND TECHNOLOGY 2021年第19-20期39卷 843-859页

作者： He, Yanqing Chen, Qing Tian, Yuanyuan Yan, Changhui He, Yufeng Li, Kai Chengdu Univ Technol State Key Lab Oil & Gas Reservoir Geol & Exploita Chengdu 610059 Sichuan Peoples R China

Accurate pore-size-distribution (PSD) is the key to comprehending porous media and shale rock characteristics. There are multiple methods for calculating the PSD of porous media. The Barrett-Joyner-Halenda (BJH) method is the most widely used and simplest calculation, and therefore, this study focus on the BJH algorithm to discuss the accurate shale PSD based on N-2 adsorption characteristics. Despite conducting more than a hundred experiments there are certain phenomena for which the calculated pore volume is smaller than the actual pore volume. Therefore, we combined the Brunauer-Emmet-Teller (BET) multilayer adsorption theory and Halsey adsorption equation to analyze the capillary evaporation and desorption demarcation points in the desorption isotherm of each shale sample, and a modified PSD calculation model was established. In addition, we applied the modified BJH algorithm to a homogeneous silicon material with the pore radius known, for calculating the theoretical pore radius and subsequently the pore radii;this allowed determining the correctness of the modified algorithm. The calculation error was approximately 5% that indicated the accuracy of this algorithm. Therefore, this study could provide meaningful insights into the accurate PSD calculation and gas-in-place estimation in shale nanoporous media.

关键词： BJH method modified algorithm N-2 desorption pore size distribution shale nanoporous media

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modified Recommender algorithm based on Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Methodology with Entropy Weighting Method (EWM) 4

Modified Recommender Algorithm based on Technique for Order ...

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4th International Conference of Science and Information Technology in Smart Administration, ICSINTESA 2024

作者： Pacaon, Mark Reden S. Ballera, Melvin A. Technological Institute of the Philippines Graduate Program Manila Philippines Technological Institute of the Philippines Department of Computer Science Manila Philippines

ISBN: (纸本)9798350376111

This research exhibits an algorithm adapted from the Technique for Order of Preference by Ideal Solution (TOPSIS) methodology, integrating the Entropy Weighting Method (EWM) for objective and efficient recommendation processes. Decision-making methodologies have indicated gaps of subjective influence affecting performance values on several implementations with additional limitations on the flexibility of handling complex problems that require multiple factors while maintaining an acceptable running time. The study takes this into account and formulates an adaptable and efficient framework that offers objective and data-driven recommendations for diverse situations. Future endeavors include subjecting the framework to real-life scenarios and testing its effectiveness. © 2024 IEEE.

关键词： decision-making entropy weighting method modified algorithm multicriteria TOPSIS

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modified Bug algorithm with Supervisory Control Using Machine Learning to Reduce Human-Cobot Collisions

Modified Bug Algorithm with Supervisory Control Using Machin...

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作者： Li, Anran Washington State University

学位级别：M.S., Master of Science/Master of Surgery

A collaborative robot, or cobot, is an efficient robot that can work alongside human workers in the same work cell. Cobots are popular in industry because they allow close collaboration between humans and robots. Although a cobot can stop when a collision occurs, it is not safe or pleasant for the human worker to be hit by the cobot multiple times a day. Therefore, it is important to reduce or eliminate collisions between cobots and human workers. This research uses inexpensive proximity sensors on the cobot to detect obstacles and generate motion decisions. First, a modified bug algorithm is utilized to maneuver the cobot to achieve a pick-and-place task. This algorithm applies a wrist yaw angle to move around the human workers and avoid collisions in the same work cell. Second, a long short-term memory (LSTM)-based artificial neural network was trained using a collision-free path dataset. The network model generates corrections when abnormal movements in the modified algorithm are detected due to interference in sensor *** of pick-and-place tasks considered different locations and orientations of human workers, as well as dynamic scenarios. The results show a significant reduction in collisions using the proposed bug algorithm and machine learning supervisory control strategy. The supervisory control method has the ability to find additional solutions to reach the target and reduce the number of steps needed to explore potential collision-free paths.

关键词： Machine learning Cobots Sensor readings modified algorithm Bug algorithm

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modified artificial bee colony algorithm with differential evolution to enhance precision and convergence performance

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EXPERT SYSTEMS WITH APPLICATIONS 2022年第0期198卷 1页

作者： Ustun, Deniz Toktas, Abdurrahim Erkan, Ugur Akdagli, Ali Engn Fac Dept Comp Engn TR-33400 Tarsus Mersin Turkey Karamanoglu Mehmetbey Univ Engn Fac Dept Elect Elect Engn TR-70200 Karaman Turkey Karamanoglu Mehmetbey Univ Engn Fac Dept Comp Engn TR-70200 Karaman Turkey Mersin Univ Engn Fac Dept Elect Elect Engn TR-33343 Mersin Turkey

Artificial bee colony (ABC) and differential evolution (DE) are the most powerful and operative meta-heuristic algorithms inspired by the nature. Although both algorithms are successful, their successes vary from phase to phase, i.e. while ABC is better in the exploration ability, DE is well in the exploitation capability. Because the diversity of mutation and exponential crossover operators is prominently better than that of onlooker bee;in this study, the exploitation ability of ABC is enhanced by replacing the onlooker bee operator with those of mutation and the crossover phases of DE in order to increase the accuracy and speed up the convergence. We hereby introduce a novel modified algorithm denoted "modified ABC by DE" (mABC). The precision performance of mABC is verified through 20 classical benchmark functions and CEC 2014 test suit by a comprehensive comparison with recent ABC variants and hybrids for 30 and 50 dimensions. The results are interpreted using various statistical evaluations such as Wilcoxon, Friedman, and Nemenyi tests. Moreover, mABC is comparatively examined over convergence plots. In concise, the mean ranks of mABC are 1.4 and 2.3 for classical benchmark functions and CEC 2014, respectively. mABC outperforms the other variants averagely for 14 of 20 classical benchmark functions and 24 of 30 CEC 2014 functions. The results manifest that the proposed mABC is a robust and reliable algorithm as well as better than the existing ABC variants and hybrids with regard to high optimization performance like precision and convergence.

关键词： Artificial bee colony (ABC) Differential evolution (DE) Optimization algorithm modified ABC modified algorithm Hybrid algorithm

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A modified Back Propagation algorithm of Neural Network with Global Optimization

A Modified Back Propagation Algorithm of Neural Network with...

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2014 3rd International Conference on Key Engineering Materials and Computer Science(KEMCS 2014)

作者： Jingjing Li Zhe Cui Chengdu Institute of Computing Technology Chinese Academy of Sciences

The advantages and weakens of traditional BP algorithm is briefly analyzed and an efficient global optimization algorithm is *** basic principle of the algorithm is presented,and a new BP neural network algorithm based on the existing BP algorithm and the new global optimization algorithm is proposed, considering the new global optimization algorithm can solve the problem of local minimum efficiently. To verify the effectiveness of the new BP algorithm,the paper compared the experimental results of various algorithms in solving function fitting problem.

关键词： Neural network BP algorithm Global optimization algorithm Global minimum modified algorithm

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Performance enhancement of meta-heuristics through random mutation and simulated annealing-based selection for concurrent topology and sizing optimization of truss structures

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SOFT COMPUTING 2022年第12期26卷 5661-5683页

作者： Kumar, Sumit Tejani, Ghanshyam G. Pholdee, Nantiwat Bureerat, Sujin Univ Tasmania Australian Maritime Coll Coll Sci & Engn Launceston Tas 7248 Australia GSFC Univ Sch Technol Dept Mech Engn Vadodara Gujarat India Khon Kaen Univ Fac Engn Sustainable & Infrastruct Res & Dev Ctr Dept Mech Engn Khon Kaen 40002 Thailand

The present investigation includes the performance enhancement concept of discrete meta-heuristics (MHs) for truss design with concurrent size and topology optimization. The five basic MHs, viz. teaching-learning-based optimization (TLBO), whale optimization algorithm (WOA), dragonfly algorithm (DA), heat transfer search (HTS), and ant lion optimization (ALO) algorithm, are investigated. Often these MHs found incompetent in answering complex problems like concurrent topology and sizing optimization of truss structures due to their poor convergence rate, local optima trap, and higher computation time. Also, the balance between diversification and intensification is very significant for MHs efficiency. A mutation is a strong strategy for balancing the diversification and intensification of MHs and can assist in guiding the population towards the global optimum. Moreover, population diversity can be improved by incorporating the selection of simulated annealing that can reduce the chances of local optima tarp. Therefore, an effective search technique based on a random mutation search along with simulated annealing-based selection is developed. Here, five modified MHs, i.e. the modified DA (MDA), modified ALO (MALO), modified WOA (MWOA), modified HTS (MHTS), and modified TLBO (MTLBO) algorithms, using random mutation search phase and SA-based selection are proposed. The developed techniques are implemented on three standard test problems where dynamic and static constraints and multiple load cases are imposed. The comparative performance of the proposed algorithms and their original algorithms is carried out. An empirical evaluation was done using Friedman rank, and the respective algorithms ranks are assigned. The findings reveal that the new technique results in significant performance enhancement of the various MHs by synchronizing the diversification and intensification of search.

关键词： modified algorithm Meta-heuristic Mutation Structural optimization Discrete section Static and dynamic constraints Simulated annealing

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Multiobjective Design of 2D Hyperchaotic System Using Leader Pareto Grey Wolf Optimizer

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IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS 2024年第9期54卷 5237-5247页

作者： Toktas, Abdurrahim Erkan, Ugur Ustun, Deniz Lai, Qiang Ankara Univ Engn Fac Dept Artificial Intelligence & Data Engn TR-06830 Golbasi Turkiye Karamanoglu Mehmetbey Univ Engn Fac Dept Comp Engn TR-70200 Karaman Turkiye Tarsus Univ Engn Fac Dept Comp Engn TR-33400 Tarsus Turkiye East China Jiaotong Univ Sch Elect & Automat Engn Nanchang 330013 Peoples R China

A chaotic system is a mathematical model exhibiting random and unpredictable behavior. However, existing chaotic systems suffer from suboptimal parameters regarding chaotic indicators. In this study, a novel leader Pareto grey wolf optimizer (LP-GWO) is proposed for multiobjective (MO) design of 2D parametric hyperchaotic system (2D-PHS). The MO capability of LP-GWO is improved by integrating a LP solution within the Pareto optimal set. The effectiveness of LP-GWO is corroborated through a comparison with regular MO versions of grey wolf optimizer (GWO), artificial bee colony, particle swarm optimization, and differential evolution. Additionally, the validation extends to the exploration of LP-GWO's performance across four variants of the 2D-PHS optimized by the compared algorithms. A 2D-PHS model with eight parameters is conceived and then optimized using LP-GWO by ensuring tradeoff between two objectives: Lyapunov exponent (LE) and Kolmogorov entropy (KE). A globally optimal design is chosen for freely improving the two objectives. The chaotic performance of 2D-PHS significantly outperforms existing systems in terms of precise chaos indicators. Therefore, the 2D-PHS has the best ergodicity and erraticity due to optimal parameters provided by LP-GWO.

关键词： Chaos Vectors Chaotic communication Optimization Pareto optimization Heuristic algorithms Linear programming Chaotic system grew wolf optimizer modified algorithm multiobjective (MO) optimization Pareto optimality

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