矿物加工中的人工智能与自然智能

IF 1.3 4区 工程技术 Q4 CHEMISTRY, PHYSICAL
S. G. Ozkan
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引用次数: 0

摘要

本文旨在介绍现代数字世界在采矿和矿物加工中使用的ni -自然智能、ai -人工智能、ml -机器学习、dl -深度学习、es -专家系统等术语,并说明它们之间的主要区别。众所周知,矿产工业的每一个科技步骤都会产生大量的原始数据,对原始数据进行分类是非常必要的。然后,专家们利用专门的仿真软件平台,利用这些参数及其之间的关系,寻找替代方案,以获得最优的结果。这些复杂操作的仿真模型的开发不仅耗时且缺乏实时性,而且需要集成多个软件平台,需要丰富的流程知识和广泛的模型验证。本文还展示了一个示例案例研究,并对结果进行了讨论,涵盖了在浮选相关研究生研究中使用NI的实验参数期间的主要推论、评论和决定,并与可能的AI使用进行了比较。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Artificial intelligence versus natural intelligence in mineral processing
This article aims to introduce the terms NI-Natural Intelligence, AI-Artificial Intelligence, ML-Machine Learning, DL-Deep Learning, ES-Expert Systems and etc. used by modern digital world to mining and mineral processing and to show the main differences between them. As well known, each scientific and technological step in mineral industry creates huge amount of raw data and there is a serious necessity to firstly classify them. Afterwards experts should find alternative solutions in order to get optimal results by using those parameters and relations between them using special simulation software platforms. Development of these simulation models for such complex operations is not only time consuming and lacks real time applicability but also requires integration of multiple software platforms, intensive process knowledge and extensive model validation. An example case study is also demonstrated and the results are discussed within the article covering the main inferences, comments and decision during NI use for the experimental parameters used in a flotation related postgraduate study and compares with possible AI use.
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来源期刊
Physicochemical Problems of Mineral Processing
Physicochemical Problems of Mineral Processing CHEMISTRY, PHYSICAL-MINING & MINERAL PROCESSING
自引率
6.70%
发文量
99
期刊介绍: Physicochemical Problems of Mineral Processing is an international, open access journal which covers theoretical approaches and their practical applications in all aspects of mineral processing and extractive metallurgy. Criteria for publication in the Physicochemical Problems of Mineral Processing journal are novelty, quality and current interest. Manuscripts which only make routine use of minor extensions to well established methodologies are not appropriate for the journal. Topics of interest Analytical techniques and applied mineralogy Computer applications Comminution, classification and sorting Froth flotation Solid-liquid separation Gravity concentration Magnetic and electric separation Hydro and biohydrometallurgy Extractive metallurgy Recycling and mineral wastes Environmental aspects of mineral processing and other mineral processing related subjects.
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