Web-based intelligent system for predicting apricot yields using artificial neural networks
Web-based intelligent system for predicting apricot yields using artificial neural networks
复制标题
使用人工神经网络预测杏产量的基于网络的智能系统
DOI：
10.1016/j.scienta.2016.10.032
复制
发表时间：
2016
影响因子：
4.3
通讯作者：
V. Ličina
中科院分区：
文献类型：
--
作者：
M. Blagojevic;Miladin Blagojević;V. Ličina
本文介绍了利用人工神经网络和PDCA （Plan, Do, Check, Act）方法对杏亩产进行预测。本文的目标是确定使用人工神经网络预测杏每公顷产量的可能性，如果使用以下项目作为输入参数：肥料量，芽的长度，芽的厚度，收获的开始和果实质量。该论文的目标还包括创建一个基于web的应用程序，显示通过神经网络获得的最终研究结果。为了保证过程的控制和持续改进，采用了PDCA方法。结果指出了上述方法成功应用的可能性，并突出了其局限性、优点和不足。未来的工作涉及到关联规则挖掘的成功应用，以检测杏产量与其他参数之间的关系。
This paper shows the use of artificial neural networks and the PDCA (Plan, Do, Check, Act) method for predicting the apricot yield per hectare. The goal of the paper is to determine the possibilities for using artificial neural networks to predict the apricot yield per hectare if the following items are used as input parameters: amount of fertilizer, length of shoots, thickness of shoots, beginning of the harvest and fruit mass. The goal of the paper also includes creation of a web-based application that displays final research results, obtained through neural networks. The PDCA method was used in order to ensure the control and continual improvement of the process. The results point to the possibility of successful application of the above mentioned methods, highlighting the limitations, advantages and shortcomings. Future work relates to the successful application of association rule mining in order to detect the relationship between the apricot yield and other parameters.
DOI：
10.7551/mitpress/11457.001.0001
发表时间：
1982-02
期刊：
--
影响因子：
--
作者：
W. Deming
通讯作者：
W. Deming