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: Business Analytics and Decision Making in Practice; Proceedings of the I Ali Emrouznejad,Panagiotis D. Zervopoulos,John Ric Conference proc

[復制鏈接]
31#
發(fā)表于 2025-3-26 21:15:09 | 只看該作者
,NER-IPL: Indian Legal Prediction Dataset for?Named Entity Recognition,R tasks using language models. All the different experiments with scores, detailed analysis, and the scope of improvements are elaborated in detail. Amongst the experimented baseline models, the InLegalBERT model gives the best F1 score of 0.67 on our dataset.
32#
發(fā)表于 2025-3-27 04:29:03 | 只看該作者
,Benchmarking Machine Learning Algorithms to?Predict Profitability Directional Changes,ls and underlining the necessity of different data sources. Future research could explore machine learning for metrics of profitability in levels and assess the value relevance of raw accounting items. This research aligns with literature while providing fresh insights into predictive modeling in fi
33#
發(fā)表于 2025-3-27 05:33:21 | 只看該作者
34#
發(fā)表于 2025-3-27 12:41:06 | 只看該作者
UAE Stock Markets Prediction: Machine Learning Application,s study determines interesting patterns. When dissecting the stock markets in Dubai and Abu Dhabi separately, the outcomes distinctly indicate a distinct dependence on Qatar, Oman, Bahrain, and Kuwait in both markets. Notably, Dubai exhibits a discernible dependence on the Chinese and Saudi Arabian
35#
發(fā)表于 2025-3-27 16:59:10 | 只看該作者
The Drivers of Port Productivity for Selected Indian Ocean Ports Using the Malmquist Productivity Index. The period of examination is from 2008–2018. The results indicated that over the period of 2008 to 2018 the port of Port Louis achieved an annual average productivity gain of 0.91 whilst the Port of Victoria achieved 0.95. The drivers of productivity being tilted more towards technology change
36#
發(fā)表于 2025-3-27 21:48:14 | 只看該作者
The Technical Efficiency of Farms, Its Decomposition into Input Components, and Their Socioeconomicmanage their resources differently based on their level of knowledge and understanding of resource utilization, according to the input decomposition. The efficient group seemed to be socioeconomically the youngest, most educated, having the largest percentage of family members, having less experienc
37#
發(fā)表于 2025-3-28 01:57:49 | 只看該作者
38#
發(fā)表于 2025-3-28 05:30:41 | 只看該作者
39#
發(fā)表于 2025-3-28 09:31:09 | 只看該作者
Can Machine Learning Enhance the Forecasting of Herding Behavior in International Stock Markets?,tional regression methods in prediction accuracy due to its advanced algorithms and ability to understand complex robust data patterns. Machine learning captures nonlinear relationships, revealing herding behavior causes Our research has two main consequences. It shows that market conditions impact
40#
發(fā)表于 2025-3-28 14:14:34 | 只看該作者
 關于派博傳思  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 論文服務流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學 Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點評 投稿經(jīng)驗總結 SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學 Yale Uni. Stanford Uni.
QQ|Archiver|手機版|小黑屋| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2026-1-17 06:09
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權所有 All rights reserved
快速回復 返回頂部 返回列表
磴口县| 阿拉尔市| 松江区| 饶阳县| 方正县| 岳阳市| 沧源| 张家界市| 明光市| 积石山| 象州县| 泉州市| 兰坪| 凤阳县| 革吉县| 江达县| 邓州市| 绥化市| 铜梁县| 固阳县| 茂名市| 富裕县| 尉氏县| 石河子市| 汕头市| 文化| 沁水县| 山东省| 越西县| 东辽县| 醴陵市| 疏附县| 清河县| 安阳县| 汉寿县| 鲁甸县| 大城县| 高邮市| 孟津县| 黄石市| 清丰县|