Agape: Parallel genetic algorithm Programming environment developed For APE100/QU adrics

A. Sternieri

首页> 外文期刊>Computers and Artificial Intelligence >Agape: Parallel genetic algorithm Programming environment developed For APE100/QU adrics

【24h】

Agape: Parallel genetic algorithm Programming environment developed For APE100/QU adrics

机译：Agape：针对APE100 / QU adrics开发的并行遗传算法编程环境

获取原文

获取原文并翻译 | 示例

掌桥外文数据库（机构版） >>

开具论文收录证明 >>

页面导航

摘要
著录项
相似文献
相关主题

摘要

AGAPE, an environment for the implementation of parallel evolutionary algorithms on the APE100/Quadrics architecture, is presented. AGAPE is a flexi- ble tool for users to solve numerical optimization problems; in addition researchers can use AGAPE for the study of new genetic operators, selection functions and mi- gration strategies. A version of AGAPE dedicated to the design of neural networks is reported. The simulation results show that the coding scheme adopted by AGAPE leads to the bet learning rate on Rumelhart's problems. The paper also includes two reviews on parallel genetic algorithms and on evolution programs of the optimization of neural networks.

机译：提出了AGAPE，一种在APE100 / Quadrics体系结构上实现并行进化算法的环境。 AGAPE是用户解决数值优化问题的灵活工具。此外，研究人员可以使用AGAPE来研究新的遗传算子，选择功能和迁移策略。报告了专门用于神经网络设计的AGAPE版本。仿真结果表明，AGAPE所采用的编码方案可以提高对Rumelhart问题的下注学习率。本文还包括关于并行遗传算法和神经网络优化的进化程序的两个评论。

著录项

来源
《Computers and Artificial Intelligence》 |1999年第3期|p.217-237|共21页
作者
A. Sternieri;
展开▼
作者单位

展开▼
收录信息
原文格式 PDF
正文语种 eng
中图分类计算技术、计算机技术;
关键词
parallel genetic algorithms; neurla networks design; Ape100/Quadrics architecture;

机译：并行遗传算法;神经网络设计;Ape100 / Quadrics体系结构;

相似文献

外文文献
中文文献
专利

1. Internal combustion engine control for series hybrid electric vehicles by parallel and distributed genetic programming/multiobjective genetic algorithms [J] . D. Gladwin, P. Stewart, J. Stewart International journal of systems science . 2011,第1a3期

机译：基于并行和分布式遗传规划/多目标遗传算法的串联混合动力汽车内燃机控制
2. Implementing genetic algorithms to CUDA environment using data parallelization [J] . Oiso Masashi, Matsumura Yoshiyuki, Yasuda Toshiyuki, Technical Gazette . 2011,第4期

机译：使用数据并行化在CUDA环境中实现遗传算法
3. Implementing genetic algorithms to CUDA environment using data parallelization [J] . Oiso Masashi, Matsumura Yoshiyuki, Yasuda Toshiyuki, Technical Gazette . 2011,第4期

机译：使用数据并行化在CUDA环境中实现遗传算法
4. Genetic Algorithm Based Parallel K-Means Data Clustering Algorithm Using MapReduce Programming Paradigm on Hadoop Environment (GAPKCA) [C] . Sayer Alshammari, Maslina Binti Zolkepli, Rusli Bin Abdullah International Conference on Soft Computing and Data Mining . 2020

机译：基于遗传算法的并行k均值数据聚类算法使用MapReduce编程范例对Hadoop环境（Gapkca）
5. An object-oriented programming environment for parallel genetic algorithms. [D] . Filho, Jose Luiz Ribeiro. 1995

机译：并行遗传算法的面向对象编程环境。
6. Analysis of Parallel Algorithms on SMP Node and Cluster of Workstations Using Parallel Programming Models with New Tile-based Method for Large Biological Datasets [O] . D. D. Shrimankar, S. R. Sathe 2016

机译：大型生物数据集基于新图块的并行编程模型对SMP节点和工作站集群的并行算法进行分析
7. Implementation Method of Genetic Algorithms to the CUDA Environment using Data Parallelization [O] . Masashi OISO, Yoshiyuki MATSUMURA, Toshiyuki YASUDA, 2011

机译：使用数据并行化实现CUDA环境的遗传算法
8. Generalization and Parallelization of Messy Genetic Algorithms and Communicationin Parallel Genetic Algorithms [R] . Merkle, L. D. 1992

机译：并行遗传算法中遗传算法和通信的泛化与并行化

Agape: Parallel genetic algorithm Programming environment developed For APE100/QU adrics

摘要

著录项

相似文献

相关主题

期刊订阅