找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Machine Learning and Computational Intelligence Techniques for Data Engineering; Proceedings of the 4 Pradeep Singh,Deepak Singh,Sanjay Mis

[復(fù)制鏈接]
樓主: Motion
11#
發(fā)表于 2025-3-23 11:07:51 | 只看該作者
12#
發(fā)表于 2025-3-23 16:01:00 | 只看該作者
Portfolio Selection Using Golden Eagle Optimizer in Bombay Stock Exchange,ve weed optimization (IWO) on S&P BSE dataset (30 stocks) of Indian stock exchange. Study shows the better performance of the proposed GEO based solution approach among its peer methods on account of execution time, and obtained optimal solutions on efficient frontiers.
13#
發(fā)表于 2025-3-23 22:03:07 | 只看該作者
14#
發(fā)表于 2025-3-23 23:13:20 | 只看該作者
Precise Stratification of Gastritis Associated Risk Factors by Handling Outliers with Feature Selecin the biological data. The dataset contains 21 lifestyle-dietary features that are possible risk factors for pathogen-associated gastritis disease. The Proposed Multilayer Perceptron Model (PMPM) showed highest accuracy of 92% on outliers replaced by median values?+?feature selection.
15#
發(fā)表于 2025-3-24 02:58:47 | 只看該作者
16#
發(fā)表于 2025-3-24 10:29:29 | 只看該作者
Brain Tumor Segmentation Using Deep Neural Networks: A Comparative Study,inally, the study compared the Cascaded and the U-net performance based on F1 score and Dice loss. It was concluded that the U-net architecture performed better than Cascading architecture and delivered a more precise boundary for the target tumor in an MRI scan.
17#
發(fā)表于 2025-3-24 12:32:05 | 只看該作者
18#
發(fā)表于 2025-3-24 18:41:55 | 只看該作者
19#
發(fā)表于 2025-3-24 23:04:34 | 只看該作者
Comparative Study of Loss Functions for Imbalanced Dataset of Online Reviews,al cross-entropy loss function, widely used in the evaluation. The final comparison between the two-loss functions will help determine whether the change of loss function can create how much difference in the model performance.
20#
發(fā)表于 2025-3-25 00:09:55 | 只看該作者
Conference proceedings 2023 book focus on research advancements in machine intelligence, signal processing, and applications. The book covers the real-time challenges involved while processing big data analytics and stream processing with the integration of smart data computing services and interconnectivity. It also includes
 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| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-20 00:56
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
武穴市| 民乐县| 寿光市| 富阳市| 新邵县| 内丘县| 河曲县| 江永县| 五峰| 宁都县| 博乐市| 资源县| 怀安县| 璧山县| 涟水县| 湛江市| 九龙城区| 井冈山市| 水富县| 友谊县| 定陶县| 自治县| 榆中县| 辉南县| 诸暨市| 利津县| 文昌市| 公安县| 古丈县| 曲水县| 皮山县| 保山市| 丽江市| 安阳县| 信阳市| 钟祥市| 福清市| 绥芬河市| 黎川县| 乐安县| 连云港市|