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Use of neuro fuzzy network with hybrid intelligent optimization techniques for weight determination in parallel Job scheduling
2012
Scientific Research and Essays
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optimization, hybrid particle swarm optimization with the tabu search and the parallel implementation of the hybrid approach of the particle swarm optimization with the tabu search are employed to identify ...
The performance of the neural network in turn depends on the weight determination of its own network and the various optimization techniques like genetic and parallel genetic algorithm, particle swarm ...
algorithm and particle swarm optimization with tabu search (parallel). ...
doi:10.5897/sre11.2148
fatcat:b76strdq65gubn6s5swho3ol6m
Effect of Communication Modes to Swarm Robotic Search
2014
Open Electrical & Electronic Engineering Journal
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Interactions in swarm robotic search are explored for intelligence emergence based on Extended Particle Swarm Optimization (EPSO) model. ...
For this end, the best combination of proper properties in typical versions of PSO is transferred to swarm robotic search. ...
ACKNOWLEDGEMENTS Author thanks for support including the National Natural Science Foundation of China under Grands 61165016, 61472269, and 61403271, as well as Shanxi Natural Science Foundation under Grands ...
doi:10.2174/1874129001408010240
fatcat:wiowg5bzkjhsbo5u2mgiy2ouxq
Parallel Particle Swarm Optimization Algorithm Accelerated by Asynchronous Evaluations
2006
Journal of Aerospace Computing Information and Communication
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A parallel Particle Swarm Optimization (PSO) algorithm is presented. ...
One approach to reduce the elapsed time is to make use of coarse-grained parallelization to evaluate the design points. ...
Parallel Particle Swarm Optimization Algorithm The PSO algorithm is ideally suited for a coarse-grained parallel implimentation on a parallel or distributed computing network. ...
doi:10.2514/1.17873
fatcat:em7xc4tfqbe5tewcxy4uqkmt7i
Estimating output flow depth from Rockfill Porous media
2021
Water Science and Technology : Water Supply
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In the present study, using dimensional analysis and particle swarm optimization (PSO) algorithm and experimental data in different conditions (a total of 178 experimental data for rounded, crashed, Glass ...
To analyze the flow in a rockfill porous media using the Gradually Varied Flows theory (one-dimensional flow analysis) and solving the Parkin equation (two-dimensional flow analysis), calculation of the ...
function in the Particle Swarm Optimization (PSO) algorithm. ...
doi:10.2166/ws.2021.317
fatcat:zhuv4flucnaebfzqerais7mkeu
Parallelizing Comprehensive Learning Particle Swarm Optimization by Open Computing Language on an Integrated Graphical Processing Unit
2020
Complexity
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The deterministic optimization is performed on an ensemble of 62 years' historical inflow records with monthly time steps, is solved by CLPSO, and is parallelized by a coarse-grained multipopulation model ...
Comprehensive learning particle swarm optimization (CLPSO) is a powerful metaheuristic for global optimization. ...
Parallelizing Comprehensive Learning Particle Swarm Optimization
Basic Coarse-Grained All-GPU Model. ...
doi:10.1155/2020/6589658
fatcat:5fcu5utenzgpjiog7oh2ckh7dy
Controlling swarm robots for target search in parallel and asynchronously
2009
International journal of Modeling, identification and control
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To control swarm robots with extended particle swarm optimization approach for target search, target signals should be detected and fused as fitness evaluate due to the inherent parallel processing property ...
Each robot detects signals in a fine-grained parallel way and compares fusion of signals with the best in its character swarm. ...
The authors are currently sponsored by a National Natural Science Foundation (NSFC) of China grant (contract No. 60674104). ...
doi:10.1504/ijmic.2009.030082
fatcat:c57bc3h7kvewlkwjy7o4yqp63y
Synchronous and Asynchronous Communication Modes for Swarm Robotic Search
[chapter]
2011
Mobile Robots - Control Architectures, Bio-Interfacing, Navigation, Multi Robot Motion Planning and Operator Training
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These mentioned algorithms are all attributed to coarse-grained parallelism. ...
Section 2 maps swarm robotic search to the particle swarm optimization algorithm. Then it models the swarm robots with EPSO method and describes the control following swarm intelligence principles. ...
Similar to the coarse-grained parallel particle swarm optimization, we can make robot R i communicate every n iterations to decide the best-found position within robot R i 's TVCS (Huang and Fan, 2006 ...
doi:10.5772/25505
fatcat:4mfy5zcxqfhpdiqynxuk54c2ke
Parallel global optimization with the particle swarm algorithm
2004
International Journal for Numerical Methods in Engineering
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To obtain enhanced computational throughput and global search capability, we detail the coarse-grained parallelization of an increasingly popular global search method, the particle swarm optimization ( ...
When the analytical problems were solved using a fixed number of swarm iterations, a single population of 128 particles produced a better convergence rate than did multiple independent runs performed using ...
ACKNOWLEDGEMENTS The authors gratefully acknowledge funding for this study from NIH National Library of Medicine (R03 LM07332) and Whitaker Foundation grants to B. J. ...
doi:10.1002/nme.1149
pmid:17891226
pmcid:PMC1989676
fatcat:tz6qlmiyizdjvm6mxb5smxi5iu
Mapping loops onto Coarse-Grained Reconfigurable Architectures using Particle Swarm Optimization
2010
2010 International Conference of Soft Computing and Pattern Recognition
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To utilize the abundant parallelism found in CGRAs, we propose a fast and efficient Modulo-Constrained Hybrid Particle Swarm Optimization (MCHPSO) scheduling algorithm to exploit loop level parallelism ...
Coarse-Grained Reconfigurable Architectures (CGRAs) have gained currency in recent years due to their abundant parallelism and flexibility. ...
Particle Swarm Optimization Particle Swarm Optimization (PSO) is an optimization approach that follows an evolutionary metaphor. ...
doi:10.1109/socpar.2010.5685969
dblp:conf/socpar/GnanaolivuNV10
fatcat:kvffgr52zjb47ndx2cvtqzefbq
Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm
2010
International Journal of Computational Intelligence Systems
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We describe the quantum dynamic mechanism and analysis the technology of improving performance, the efficiency of the approach has been illustrated by applying to TSP benchmark instances Chn144. ...
A novel Parallel Ant Colony Optimization Algorithm based on Quantum dynamic mechanism for traveling salesman problem (PQACO) is proposed. ...
Acknowledgements The authors gratefully acknowledge the support of National Natural Science Foundation of Shanghai ...
doi:10.1080/18756891.2010.9727756
fatcat:y6zk7s4o7rfbremxzozk2j33w4
Quantum Dynamic Mechanism-based Parallel Ant Colony Optimization Algorithm
2010
International Journal of Computational Intelligence Systems
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We describe the quantum dynamic mechanism and analysis the technology of improving performance, the efficiency of the approach has been illustrated by applying to TSP benchmark instances Chn144. ...
A novel Parallel Ant Colony Optimization Algorithm based on Quantum dynamic mechanism for traveling salesman problem (PQACO) is proposed. ...
Acknowledgements The authors gratefully acknowledge the support of National Natural Science Foundation of Shanghai ...
doi:10.2991/ijcis.2010.3.s1.8
fatcat:43hx3m4zrfgl3cyupmlsgsj34m
Parallelized Multiple Swarm Artificial Bee Colony Algorithm (MS-ABC) for Global Optimization
2014
Studies in Informatics and Control
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Swarm intelligence metaheuristics have been successfully used for hard optimization problems. ...
Parallelization is usually introduced for performance improvement and better resources utilization. ...
Acknowledgement This research is supported by Ministry of Education and Science of Republic of Serbia, Grant No. III-44006 ...
doi:10.24846/v23i1y201412
fatcat:6bntrc6e35aazamjxcesrs3lry
A Chaotic Parallel Artificial Fish Swarm Algorithm for Water Quality Monitoring Sensor Networks 3D Coverage Optimization
2021
Journal of Sensors
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Ultimately, CPAFSA is compared with genetic algorithm (GA) and particle swarm optimization (PSO). ...
To optimize the 3D coverage of underwater targets, this research proposes a chaotic parallel artificial fish swarm algorithm (CPAFSA). ...
Parallel models include the fine-grained model, masterslave model, and coarse-grained model. The fine-grained model is mainly used in large-scale computer systems. ...
doi:10.1155/2021/5529527
fatcat:mi4lqtuwcrbdhgv6mh4sdim7mm
Clustering Algorithm of Ethnic Cultural Resources based on Spark
2019
International Journal of Performability Engineering
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The particle swarm optimization (PSO) algorithm and global coarse-grained search can quickly determine the k-value of the cluster center, while the retrieval efficiency is low. ...
Finally, the particle swarm optimization algorithm performs initial pre-clustering on the data set, obtains the K-means algorithm cluster center k, and then obtains the final classification result through ...
Particle Swarm Optimization Algorithm The Particle Swarm Optimization (PSO) algorithm is a new type of swarm intelligence evolution algorithm inspired by famous scholars Kennedy and Eberhart in the late ...
doi:10.23940/ijpe.19.03.p4.756762
fatcat:exon4f54bfapzgslsmzsqvkbae
Pipeline 3D Modeling Based on High-Definition Rendering Intelligent Calculation
2022
Mathematical Problems in Engineering
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By analyzing the parallel design schemes of swarm intelligence algorithms under different granularities, this paper proposes a parallel swarm intelligence optimization algorithm design method and then ...
The experimental results verify the excellent performance of the method proposed in this paper. ...
In the artificial fish swarm algorithm, the concept of "field of view" in fish is adopted. e basic idea of particle swarm optimization is to promote the evolution of the group and find the optimal solution ...
doi:10.1155/2022/4580363
fatcat:bsg4jdw6hbbibmn6j5mlz7ypx4
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