• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

开发农业产消者社区团体平台的框架。

Frameworks for developing an Agro-Prosumer Community Group platform.

作者信息

Jain Pratima, Potdar Vidyasagr

机构信息

School of Information Systems, Curtin University of Technology, Perth, WA, Australia.

School of Management, Curtin University of Technology, Perth, WA, Australia.

出版信息

PeerJ Comput Sci. 2021 Dec 6;7:e765. doi: 10.7717/peerj-cs.765. eCollection 2021.

DOI:10.7717/peerj-cs.765
PMID:34977347
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8670369/
Abstract

BACKGROUND

The involvement of prosumers in the form of agricultural community groups has been acknowledged, and interest in it is increasing due to local food demand and quality of food. How to create a prosumer group? The definition of agro-prosumers and analysis of their behaviour, engaging new members to the existing groups, managing members and their goals are important factors to consider. Hence, to overcome this barrier and to improve the participation of prosumers, in this paper three key frameworks are presented to develop an Agro-Prosumer Community Group (APCGs) platform.

METHODS

A conceptual process that consist of strict multiple stages i.e., requirement analysis, design logic, theoretical fundamentals, implementation of prototype and verification, is used to build the frameworks for APCG. Different methods and approaches are used to design and develop framework's prototype. For instance, clustering algorithms are used to define and group agro-prosumer concept, an approach is developed that evaluates real-time production behaviour of new prosumers while engaging them to APCG. Finally, the goal-ranking techniques i.e., MCGP are used to build a goal management framework that effectively reaches a compromise between diverse goals of APCGs.

RESULTS

Results for each framework is shown while verifying the prototype using prosumers data.

CONCLUSION

An Agro-Prosumer Community Group addresses three key issues relevant to the development of an agro-prosumer community-based approach to manage the prosumers in local food- and carbon-sharing networks. The key contributions are (1) APCG concept, (2) Prosumer engagement framework, and (3) Goal management framework. Thus APCG platform provides a seamless structure for carbon and produce sharing network.

摘要

背景

以农业社区团体形式存在的产消者参与已得到认可,由于当地粮食需求和食品质量,对此的关注度正在上升。如何创建一个产消者团体?农业产消者的定义及其行为分析、吸引新成员加入现有团体、管理成员及其目标是需要考虑的重要因素。因此,为了克服这一障碍并提高产消者的参与度,本文提出了三个关键框架来开发一个农业产消者社区团体(APCGs)平台。

方法

一个由严格的多个阶段组成的概念过程,即需求分析、设计逻辑、理论基础、原型实现和验证,用于构建APCG的框架。使用不同的方法和途径来设计和开发框架的原型。例如,聚类算法用于定义和分组农业产消者概念,开发了一种方法来评估新产消者在加入APCG时的实时生产行为。最后,目标排序技术即MCGP用于构建一个目标管理框架,该框架能在APCG的不同目标之间有效达成妥协。

结果

在使用产消者数据验证原型时展示了每个框架的结果。

结论

一个农业产消者社区团体解决了与基于农业产消者社区的方法相关的三个关键问题,该方法用于管理当地粮食和碳共享网络中的产消者。关键贡献在于(1)APCG概念,(2)产消者参与框架,以及(3)目标管理框架。因此,APCG平台为碳和农产品共享网络提供了一个无缝结构

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/97d212c26352/peerj-cs-07-765-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/07a2827c2f59/peerj-cs-07-765-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/77a0137f693f/peerj-cs-07-765-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/b9f385b5d586/peerj-cs-07-765-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/be66d667af5a/peerj-cs-07-765-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/f0f1ea59ab5c/peerj-cs-07-765-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/f62bc0542256/peerj-cs-07-765-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/3072519dcc92/peerj-cs-07-765-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/c60a7a8d704e/peerj-cs-07-765-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/6d327accc3c8/peerj-cs-07-765-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/a88da27c733f/peerj-cs-07-765-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/9af8c5f459bd/peerj-cs-07-765-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/1c214c69d1f2/peerj-cs-07-765-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/113ad18134ba/peerj-cs-07-765-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/389e3a335657/peerj-cs-07-765-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/a6471ea01b76/peerj-cs-07-765-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/4581181a480e/peerj-cs-07-765-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/fc81a3798e31/peerj-cs-07-765-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/ca341581f589/peerj-cs-07-765-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/97d212c26352/peerj-cs-07-765-g019.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/07a2827c2f59/peerj-cs-07-765-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/77a0137f693f/peerj-cs-07-765-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/b9f385b5d586/peerj-cs-07-765-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/be66d667af5a/peerj-cs-07-765-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/f0f1ea59ab5c/peerj-cs-07-765-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/f62bc0542256/peerj-cs-07-765-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/3072519dcc92/peerj-cs-07-765-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/c60a7a8d704e/peerj-cs-07-765-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/6d327accc3c8/peerj-cs-07-765-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/a88da27c733f/peerj-cs-07-765-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/9af8c5f459bd/peerj-cs-07-765-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/1c214c69d1f2/peerj-cs-07-765-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/113ad18134ba/peerj-cs-07-765-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/389e3a335657/peerj-cs-07-765-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/a6471ea01b76/peerj-cs-07-765-g015.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/4581181a480e/peerj-cs-07-765-g016.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/fc81a3798e31/peerj-cs-07-765-g017.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/ca341581f589/peerj-cs-07-765-g018.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9550/8670369/97d212c26352/peerj-cs-07-765-g019.jpg

相似文献

1
Frameworks for developing an Agro-Prosumer Community Group platform.开发农业产消者社区团体平台的框架。
PeerJ Comput Sci. 2021 Dec 6;7:e765. doi: 10.7717/peerj-cs.765. eCollection 2021.
2
A Heuristic to Create Prosumer Community Groups in the Social Internet of Energy.启发式方法在能源社交互联网中创建产消者社区群体。
Sensors (Basel). 2020 Jul 2;20(13):3704. doi: 10.3390/s20133704.
3
The Bioinspired Prosumer-Interactions between Bioinspired Design Methods in the Prosumer Scope.受生物启发的产消者——产消者范围内受生物启发的设计方法之间的相互作用
Biomimetics (Basel). 2024 Sep 6;9(9):539. doi: 10.3390/biomimetics9090539.
4
Rebound and Spillovers: Prosumers in Transition.反弹与溢出效应:转型中的产消者
Front Psychol. 2021 Apr 15;12:636109. doi: 10.3389/fpsyg.2021.636109. eCollection 2021.
5
Cascade computing model to optimize energy exchanges in prosumer communities.用于优化产消者社区能量交换的级联计算模型。
Heliyon. 2022 Feb 8;8(2):e08902. doi: 10.1016/j.heliyon.2022.e08902. eCollection 2022 Feb.
6
A Recommendation System for Prosumers Based on Large Language Models.基于大语言模型的产消者推荐系统
Sensors (Basel). 2024 May 30;24(11):3530. doi: 10.3390/s24113530.
7
Predicting acceptance and adoption of renewable energy community solutions: the prosumer psychology.预测可再生能源社区解决方案的接受度和采用情况:产消者心理。
Open Res Eur. 2022 Sep 29;2:115. doi: 10.12688/openreseurope.14950.1. eCollection 2022.
8
Data Security and Trading Framework for Smart Grids in Neighborhood Area Networks.面向邻里区域网络的智能电网的数据安全与交易框架。
Sensors (Basel). 2020 Feb 29;20(5):1337. doi: 10.3390/s20051337.
9
Blockchain and Demand Response: Zero-Knowledge Proofs for Energy Transactions Privacy.区块链与需求响应:能源交易隐私的零知识证明。
Sensors (Basel). 2020 Oct 5;20(19):5678. doi: 10.3390/s20195678.
10
Dynamic participation in local energy communities with peer-to-peer trading.通过对等交易动态参与地方能源社区。
Open Res Eur. 2024 Oct 18;2:5. doi: 10.12688/openreseurope.14332.1. eCollection 2022.

引用本文的文献

1
Web-based machine learning application for interpretable prediction of prolonged length of stay after lumbar spinal stenosis surgery: a retrospective cohort study with explainable AI.基于网络的机器学习应用程序用于腰椎管狭窄症手术后住院时间延长的可解释预测:一项使用可解释人工智能的回顾性队列研究
Front Physiol. 2025 Feb 19;16:1542240. doi: 10.3389/fphys.2025.1542240. eCollection 2025.