هل ستصبح شريكنا القادم ؟
Today, a greater generation of information is produced as a consequence of the technological development of society. The Internet has facilitated the access and extraction of this information, thus pursuing the automatic discovery of the knowledge contained within. In this context, data mining aims to discover patterns, profiles and …
Read More
Two various damage types, namely, misalignment and bearing clearance, both on cardan shaft, are investigated in some detail. The experimental results show how vibration analysis together with metadata processing can identify the state of the machine even in harsh operating conditions. Content from this work may be used under the terms …
Read More
Data mining and machine learning have become a vital part of crime detection and prevention. The purpose of this paper is to evaluate data mining methods and their performances that can be used for analyzing the collected data about the past crimes. I identified the most appropriate data mining methods to analyze the collected …
Read More
Design and analysis of a new type of mobile ice cooling equipment for deep mine. Xingdong Zhao, Siyu Zhao & Ang Li. Scientific Reports 13, Article number: 20375 ( …
Read More
Classification algorithms are the most commonly used data mining models that are widely used to extract valuable knowledge from huge amounts of data. The criteria used to evaluate the classifiers are mostly accuracy, computational complexity, robustness, scalability, integration, comprehensibility, stability, and interestingness. This study …
Read More
Popular mobile applications receive millions of user reviews. These reviews contain relevant information for software maintenance, such as bug reports and improvement suggestions. The review's information is a valuable knowledge source for software requirements engineering since the apps review analysis helps make strategic …
Read More
Kumar, U.: Reliability analysis of load-haul-dump machines. Ph.D. thesis, Luleå Tekniska Universitet (1990) Google Scholar Król, R., Zimroz, R., Stolarczyk, Ł.: Failure analysis of hydraulic systems used in mining machines operating in copper ore mine kghm polska miedz sa. Min. Sci. 128, 127 (2009) Google Scholar
Read More
In the realm of data-driven exploration, algorithms seamlessly intertwine with the digital landscape. Our focus converges at the forefront of Intelligent Data Mining, Analysis, and Modeling. This theme delves into the profound integration of machine learning techniques with the domains of data excavation, analysis, and model construction.
Read More
This paper presents the development of an easy-to-deploy and smart monitoring IoT system that utilizes vibration measurement devices to assess real-time condition of bulldozers, power shovels and...
Read More
We investigate the impact of how a cryptocurrency mining system can affect the power consumption of mobile devices. Specifically we look at CoinHive, a cryptocurrency miner and associated mining pool targeting the Monero (XMR) cryptocurrency. CoinHive distributes a JavaScript-based miner to webpages where visitors run the script and …
Read More
1. Large Mining Trucks. To move materials around a mine site, workers need heavy-duty trucks. Also known as off-highway trucks, large mining trucks include both powerful mechanical models and environmentally friendly electric drive models.. Unlike conventional trucks, these mining vehicles have extra-large tires to support the heavy …
Read More
Cloud-based IIoT platforms collect and share data in the mines and concentrators to allow widespread monitoring, analyzation, optimization, and control. This chapter discusses robotics and automation for mining and process control in mineral …
Read More
Text mining is the automation of text analysis using Machine Learning. To achieve this, the algorithms are trained using text as example data. The first step is to assemble data. This data can come from internal sources, such as chat interactions, emails, surveys, or company databases.
Read More
This paper aims to identify the trends in machine learning research using text mining. The researcharticles contain significant knowledge and research results. However, they are long and have many noisy results such that it takes a lot of human efforts to analyze them. Text mining can be used to analyze and extract useful information from a large number of …
Read More
Accelerating Exploration: Real-time data aids in accelerating timelines for multiple mining stages and decision-making intelligence.Remote sensing data is used for rock-face identification and soil classification, while satellite imagery, aerial photography, geophysical maps, and drone-based monitoring are used to predict mineralization, or the locations of …
Read More
An Approach to Realizing Process Control for Underground Mining Operations of Mobile Machines. Zhen Song, 1, * Håkan Schunnesson, 2 Mikael Rinne, 1 and John Sturgul 3 ... There was a process simulation analysis developed for a detailed analysis of the variables that impact the working time of excavation.
Read More
May 2, 2018 11:28 Mathematical Analysis for Machine Learning 9in x 6in b3234-main page 6 6 Mathematical Analysis for Machine Learning and Data Mining ∅ =S for the empty collectionof subsets of S.This is consistent with thefactthat∅⊆C implies C ⊆S. The symmetric differenceofsetsdenotedby ⊕ is definedbyU⊕V = (U−V)∪(V …
Read More
This series began as a journey into the applications of AI and machine learning in mining. As we stand at its conclusion, we see it has transformed into something more – a preview into a future where technology and human ingenuity converge to create a safer, more productive, and more sustainable mining industry.
Read More
Dingo, based in Brisbane, Australia, provides solutions for predictive maintenance in mining. With over 30 years of experience, the company currently manages the operational health of over $13.5 billion of heavy equipment. Its expertise and technical solutions are utilized by companies in mining, rail, oil and gas, and wind power.
Read More
Sentiment analysis of product reviews on e-commerce platforms aids in determining the preferences of customers. Aspect-based sentiment analysis (ABSA) assists in identifying the contributing ...
Read More
PDF | On Jan 1, 2019, A. Michalak and others published Condition Monitoring for LHD Machines Operating in Underground Mine—Analysis of Long-Term Diagnostic Data | Find, read and cite all the ...
Read More
The primary goal of churn analysis is to identify and anticipate churnable consumers as soon as possible. This will help us to rectify the issues of the customer. ... Churn predictions for the telecom industry have been carried out using literature with various methods that includes machine learning algorithms, data mining techniques and ...
Read More
A few of the popular data-mining techniques are clustering, classification, and association. The classification process simplifies the process of identifying and accessing data. ... and Application 4th International Conference on Innovative Data Communication Technology and Application A Comparative Analysis of Machine Learning Algorithms …
Read More
The considered machines for the present analysis are made from M/s The Sandvick Company Limited with 17 tonne bucket capacity and named as LHD1, LHD2, LHD3, LHD4, and LHD5. ... J. Barabady, U. Kumar, Reliability analysis of mining equipment- a case study of a crushing plant at jajarm bauxite mine in Iran. Reliab Eng …
Read More
Data mining (DM) is a process of taking out useful information from a large raw data set which in turn affects the decision-making process [].It is employed for the discovery of new information and patterns hidden inside that large data set by including the use of the intersection of artificial intelligence (AI), ML, and statistical analysis as shown …
Read More
To perform a Market Basket Analysis implementation with the Apriori Algorithm, we will be using the Groceries dataset from Kaggle. The data set was published by Heeral Dedhia on 2020 with a General Public License, version 2. The dataset has 38765 rows of purchase orders from the grocery stores. Photo by Cookie the Pom on Unsplash.
Read More
Alessandro Zanarini c. Add to Mendeley. https://doi/10.1016/j.cor.2020.105036 Get rights and content. Abstract. Manual short …
Read More
This paper reviews the evolution of underground metal mining automation, principally related to the development of tele-operation and automation of mobile mining …
Read More
Text mining—also called text data mining—is an advanced discipline within data science that uses natural language processing (NLP), artificial intelligence (AI) and machine learning models, and data mining techniques to derive pertinent qualitative information from unstructured text data. Text analysis takes it a step farther by focusing …
Read More
This paper investigates the application of process mining methodology on the processes of a mobile asset in mining operations as a means of identifying opportunities to improve the...
Read More
