Data mining Data mining is simply filtering through large amounts of raw data for useful information that gives businesses a competitive edge. This information is made up of meaningful patterns and trends that are already in the data but were previously unseen. The most popular tool used when mining is artificial intelligence (AI). AI technologies try to work the way the human brain works‚ by making intelligent guesses‚ learning by example‚ and using deductive reasoning. Some of the more popular
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SOLUTION MINING A Laboratory Exercise in Extracting Copper from a Synthetic Copper Ore Your Name __Mel Hine______________________ Partner’s Name __Jay Ranson____________________ Date _October 2‚ 2012____________ Introduction This laboratory exercise involves the use of dilute sulfuric acid (H2SO4) to leach copper
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Mining Assignment #4 By Siyuan Wei‚ Yifei Pei‚ Amrita Sur and Clinton Huynh Mineral: Copper Dip: 60 Depth: 650m Location/Terrain: Under River Chosen Mining Method: Sublevel Stoping - Sublevel Stoping is designed for mineral deposits which consists of fairly stable rocks and have a steep dip. - This method is quite commonly used to mine copper at varies sites around Australia. For example‚ Mount Isa‚ Olympic Dam etc… Mining Process - Sublevels are created within the solid
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like some sedimentary material. Also weathering may have contributed to the failing slopes as the orange color appears to be a lighter color orange There was a large volume of loose rock that had been dumped in the upper portion of the slope due to mining making the slope where the slide happened unstable. 1 Vegetation Conditions None Warning Signs of failure prior to event Yes‚ there were warning signs. There were signs of the mine’s wall slipping a millimeter or so each day in February.
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conveyor belt transportation system. Some comments regarding possible ways for detection of mentioned faults are considered. The examples of failures and time related to replacement or repair have been provided. 1. INTRODUCTION Condition monitoring in mining industry is not as well developed as it is in other branches (i.e. power engineering‚ oil industry etc). One of the reasons is that mine is the specific kind of company with harsh environment and dissipation of assets in wide area. There are a lot
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Data Mining Project – Dogs Race Prediction Motivation Gambling is very popular in the Republic of Ireland‚ weather is online or not‚ more people are joining gambling communities formed all over the Island of Ireland. The majority of these communities are involved in horse races related gambling and other sports‚ but there is a significant amount of people dedicated to dogs races. This is a multimillion Euro industry developed on-line and live or face to face. Objective There are many websites
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Engineering Evaluation/Cost Analysis Report Elizabeth Mine South Strafford‚ Vermont Final Report Final Report Prepared for U.S. Army Corps of Engineers New England District Concord‚ Massachusetts 12 March 2002 Arthur D. Little‚ Inc. Acorn Park Cambridge‚ Massachusetts 02140-2390 Contract No. DACW33-00-D-0002 Delivery Order 0002 Arthur D. Little Reference 76071 Table of Contents Page List of Acronyms ............................................................................................
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marking and review‚ and may submit this work to an external plagiarism-detection service who may retain a copy for future plagiarism detection but will not release it or use it for any other purpose. DATE: 06/10/2013 Introduction: In data mining it is said that “success or failure often depends not only on how well you are able to collect data but also on how well you are able to convert them into knowledge that will help you better manage your business (Wilson‚ 2001‚ p. 26).” Tourism and
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1. Sioux Corporation is estimating the following sales for the first four months of next year: Sales are normally collected 60% in the month of sale‚ 35% in the month following the sale‚ and the remaining 5% being uncollectible. Based on this information‚ how much cash should Sioux expect to collect during the month of April? A. $286‚500 B. $320‚000 C. $192‚000 D. $94‚500 Solutions: A 270‚000 * 70% = 162‚000 270‚000 * 35% = 94‚500 320‚000 * 60% = 192‚000 94‚000 + 192‚000 = 286
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fluxicon Process Mining Tutorial Copyright © 2013 Fluxicon fluxicon Goals of this tutorial • Understand phases of process mining analysis • Be able to get started and play around with your own data fluxicon Outline 1. Example Scenario 2. Roadmap 3. Hands-on Session 4. Take-away Points fluxicon Example Scenario Purchasing process ERP Requester Requester Manager Purchasing Agent Supplier Financial Manager fluxicon Problems 1. Inefficient
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