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Titlebook: Advanced Analytics in Mining Engineering; Leverage Advanced An Ali Soofastaei Book 2022 Springer Nature Switzerland AG 2022 Data Analytics.

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發(fā)表于 2025-3-21 19:53:15 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
期刊全稱Advanced Analytics in Mining Engineering
期刊簡稱Leverage Advanced An
影響因子2023Ali Soofastaei
視頻videohttp://file.papertrans.cn/146/145233/145233.mp4
發(fā)行地址Provides a concise overview of the state of the art for mining executives and managers.Highlights and describes critical opportunity areas for mining optimization.Explains how to implement advanced da
圖書封面Titlebook: Advanced Analytics in Mining Engineering; Leverage Advanced An Ali Soofastaei Book 2022 Springer Nature Switzerland AG 2022 Data Analytics.
影響因子.In this book, Dr. Soofastaei and his colleagues reveal how all mining managers can effectively deploy advanced analytics in their day-to-day operations- one business decision at a time..Most mining companies have a massive amount of data at their disposal. However, they cannot use the stored data in any meaningful way. The powerful new business tool-advanced analytics enables many mining companies to aggressively leverage their data in key business decisions and processes with impressive results..From statistical analysis to machine learning and artificial intelligence, the authors show how many analytical tools can improve decisions about everything in the mine value chain, from exploration to marketing..Combining the science of advanced analytics with the mining industrial business solutions, introduce the “Advanced Analytics in Mining Engineering Book” as a practical road map and tools for unleashing the potential buried in yourcompany’s data..The book is aimed at providing mining executives, managers, and research and development teams with an understanding of the business value and applicability of different analytic approaches and helping data analytics leads by giving them
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沙發(fā)
發(fā)表于 2025-3-21 20:55:28 | 只看該作者
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發(fā)表于 2025-3-22 03:56:45 | 只看該作者
Backwards Compatibility and Extensions,lly employed in solving ultimate pit and production scheduling problems, using rigorous algorithms, heuristics and metaheuristics. This chapter also covers stochastic mine planning and discusses future mine planning.
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發(fā)表于 2025-3-22 05:08:48 | 只看該作者
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發(fā)表于 2025-3-22 10:23:36 | 只看該作者
https://doi.org/10.1007/978-1-4302-0046-8is chapter shows how analytical models can optimize blast patterns according to the real bench geometry and discusses advanced analytical solutions for predicting blast fragmentation and vibration by considering affecting parameters on the blast outcomes. In addition, it presents developed models ba
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發(fā)表于 2025-3-22 15:57:58 | 只看該作者
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發(fā)表于 2025-3-22 19:36:19 | 只看該作者
https://doi.org/10.1007/978-1-4302-0046-8g and blasting operations can be stored in an integrated database, which can be used by other operational data generating processes in mining. The power of advanced analytics can be used to evaluate the data, identify key performance variables, implement management changes, and evaluate the outcome.
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發(fā)表于 2025-3-22 22:33:59 | 只看該作者
https://doi.org/10.1007/978-1-4302-0046-8ntration, medium-heavy separation, froth flotation, magnetic and electrostatic separation, and dewatering. This chapter includes brief details on each of these aforementioned processes, followed by practical instances of advanced intelligence-based data-driven frameworks and technologies being appli
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發(fā)表于 2025-3-23 03:17:31 | 只看該作者
Backwards Compatibility and Extensions,ble. This chapter presents a practical and validated AI approach to optimize three key parameters aimed to minimize haul truck fuel consumption in surface mines. This approach uses an artificial neural network to predict energy consumption and applies a genetic algorithm for optimization. The propos
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發(fā)表于 2025-3-23 05:52:42 | 只看該作者
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