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: Soft Computing in Data Science; Third International Azlinah Mohamed,Michael W. Berry,Bee Wah Yap Conference proceedings 2017 Springer Natu

[復(fù)制鏈接]
樓主: ODDS
31#
發(fā)表于 2025-3-27 00:35:16 | 只看該作者
Conference proceedings 2017n topical sections on?deep learning and real-time classification; image feature classification and extraction; classification, clustering, visualization; applications of machine learning; data visualization; fuzzy logic; prediction models and e-learning; text and sentiment analytics..
32#
發(fā)表于 2025-3-27 03:52:20 | 只看該作者
Evaluation of Randomized Variable Translation Wavelet Neural Networksusing benchmark data form UCI machine learning datasets were conducted. The experimental results show that RVT-WNN can work on a broad range of applications from the small size up to the large size with comparable performance to other well-known classifiers.
33#
發(fā)表于 2025-3-27 05:42:01 | 只看該作者
34#
發(fā)表于 2025-3-27 10:57:11 | 只看該作者
Conference proceedings 2017nesia, November 27-28, 2017..The 26 revised full papers presented were carefully reviewed and selected from 68 submissions. The papers are organized in topical sections on?deep learning and real-time classification; image feature classification and extraction; classification, clustering, visualizati
35#
發(fā)表于 2025-3-27 15:41:57 | 只看該作者
36#
發(fā)表于 2025-3-27 18:26:46 | 只看該作者
37#
發(fā)表于 2025-3-28 00:10:51 | 只看該作者
Modeling of the Gaussian-Based Component Analysis on the Kernel Space to Extract Face Imageg sets, 90.83% for three training sets, and 92.38% for four training sets on the YALE database. On the CAI-UTM database, the proposed method could classify correctly by 83.75%, 85.57%, and 87.33% for two, three, and four training sets respectively. The comparison results show that the results of the proposed approach outperformed to other methods.
38#
發(fā)表于 2025-3-28 02:34:14 | 只看該作者
39#
發(fā)表于 2025-3-28 08:28:37 | 只看該作者
Evaluation of Randomized Variable Translation Wavelet Neural Networkst learning algorithms have been proposed such as backpropagation and hybrid wavelet-particle swarm optimization. However, most of them are time costly. This paper proposed a new learning mechanism for VT-WNN using random weights. To validate the performance of randomized VT-WNN, several experiments
40#
發(fā)表于 2025-3-28 13:01:44 | 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, 2025-10-6 16:41
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
滨海县| 无为县| 永仁县| 乐都县| 榆树市| 仁寿县| 江源县| 金华市| 高尔夫| 若羌县| 叙永县| 衢州市| 岗巴县| 闽清县| 庄河市| 汉沽区| 嘉兴市| 福清市| 纳雍县| 合阳县| 勃利县| 驻马店市| 赣州市| 澳门| 井冈山市| 太原市| 巢湖市| 南丰县| 昌黎县| 静乐县| 通化县| 尤溪县| 高唐县| 沙坪坝区| 重庆市| 舞钢市| 日照市| 增城市| 获嘉县| 阜阳市| 阜南县|