找回密碼
 To register

QQ登錄

只需一步,快速開(kāi)始

掃一掃,訪(fǎng)問(wèn)微社區(qū)

打印 上一主題 下一主題

Titlebook: Intelligent and Evolutionary Systems; The 20th Asia Pacifi George Leu,Hemant Kumar Singh,Saber Elsayed Conference proceedings 2017 The Edit

[復(fù)制鏈接]
樓主: 變成小松鼠
31#
發(fā)表于 2025-3-26 22:57:06 | 只看該作者
32#
發(fā)表于 2025-3-27 02:27:17 | 只看該作者
Analysis of Parameter-Less Population Pyramid on the Local Distribution of Inferior Individuals,fect of DII analysis on balance between genetic operators. The performance of P3-DII was confirmed according to the computational experiments which were carried out taking several combinational problems as examples.
33#
發(fā)表于 2025-3-27 08:32:44 | 只看該作者
34#
發(fā)表于 2025-3-27 13:25:57 | 只看該作者
Generating Hub-Spoke Network for Public Transportation: Comparison Between Genetic Algorithm and Cun of the hub node and transportation line network simultaneously. In this framework, this paper reports the comparison result between the genetic algorithm and the cuckoo search algorithm for the hub location problem.
35#
發(fā)表于 2025-3-27 15:15:59 | 只看該作者
36#
發(fā)表于 2025-3-27 20:15:30 | 只看該作者
An Evolutionary Optimization Approach for Path Planning of Arrival Aircraft for Optimal Sequencing,aircraft. The proposed algorithm is compared with the traditional GA. Results indicate that the proposed approach obtains a near optimal solution compared to the traditional GA based algorithm which does not consider TAS constraints.
37#
發(fā)表于 2025-3-27 23:22:59 | 只看該作者
Obstacle Avoidance for Multi-agent Path Planning Based on Vectorized Particle Swarm Optimization,the path planning. In the dynamic environment, the numerical results show that the Simultaneous Replanning Vectorized Particle Swarm Optimization (SRVPSO) algorithm is effective and also efficient for multi-agent systems.
38#
發(fā)表于 2025-3-28 05:51:38 | 只看該作者
Dynamic Job Shop Scheduling Under Uncertainty Using Genetic Programming,onential moving average of the deviations of the processing times in the dispatching rules. We test the performance of the proposed approach under different uncertain scenarios. Our results show that the proposed method performs significantly better for a wide range of uncertain scenarios.
39#
發(fā)表于 2025-3-28 10:16:19 | 只看該作者
Semi-automatic Picture Book Generation Based on Story Model and Agent-Based Simulation,e propose a novel semi-automatic picture book generation method based on story model and agent-based simulation. The computational experiments are carried out to confirm the effectiveness of the proposed method.
40#
發(fā)表于 2025-3-28 13:45:45 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛(ài)論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-25 23:58
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
三亚市| 平武县| 葫芦岛市| 赫章县| 宜君县| 剑河县| 岑巩县| 石棉县| 丹阳市| 鄱阳县| 灵石县| 双牌县| 湾仔区| 蒙阴县| 印江| 孝昌县| 绥德县| 怀宁县| 读书| 三河市| 临沭县| 文登市| 广宗县| 台州市| 定襄县| 广安市| 宝坻区| 长丰县| 山西省| 曲周县| 金寨县| 大悟县| 英山县| 上思县| 肥东县| 中宁县| 滦平县| 鄂托克旗| 游戏| 邮箱| 宽城|