在多哥洛美利用基于梯度 LSTNet 的综合模型进行固体废物预测时使用社会经济、气候和土地利用的土地覆盖模式

IF 2.9 4区计算机科学 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Artificial Intelligence Pub Date : 2024-08-05 DOI:10.1080/08839514.2024.2387504

Kanlanféi Sambiani, Yendoubé Lare, Adamou Zanguina, Satyanarayana Narra

引用次数: 0

摘要

由于传统工具和概率工具效率低下，很少有研究探讨城市固体废物（MSW）产生预测中的递归神经网络模型。本研究旨在 ...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Use of Socio-economic, Climatic, and Land use Land Cover Patterns in Solid Waste Forecasting with Integrated Gradient LSTNet Based Model in Lomé, Togo

Few studies have explored recurrent neural network models in municipal solid waste (MSW) generation forecasting regarding the inefficiency of conventional and probabilistic tools. This study aimed ...

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Applied Artificial Intelligence 工程技术-工程：电子与电气

CiteScore

5.20

自引率

3.60%

发文量

106

审稿时长

6 months

期刊介绍： Applied Artificial Intelligence addresses concerns in applied research and applications of artificial intelligence (AI). The journal also acts as a medium for exchanging ideas and thoughts about impacts of AI research. Articles highlight advances in uses of AI systems for solving tasks in management, industry, engineering, administration, and education; evaluations of existing AI systems and tools, emphasizing comparative studies and user experiences; and the economic, social, and cultural impacts of AI. Papers on key applications, highlighting methods, time schedules, person-months needed, and other relevant material are welcome.