Combining Indicators: Maximizing Mining Returns In New York Forex Strategies


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Combining Indicators: Maximizing Mining Returns In New York Forex Strategies

Combining Indicators: Maximizing Mining Returns In New York Forex Strategies

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Review of Models and Algorithms for Subsurface Mining Options and Transitional Optimization: Some of the Lessons Learned and the Way Ahead

By Bright Oppong Afum Bright Oppong Afum Scilit Google Scholar and Eugene Ben-Awuah Eugene Ben-Awuah Scilit Google Scholar*

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Received: March 25, 2021 / Revised: April 27, 2021 / Accepted: April 30, 2021 / Published: May 10, 2021

(This article belongs to a recent special issue on Planning, Scheduling and Optimizing Underground Mines: Theory and Applications.)

It is important that strategic mining plans make the most of available resources. and continuously supplying quality minerals to drive sustainable mining and profitability. This requires the development of strategies that are well integrated in mining options for surface and/or underground mining and their interactions. Understanding current tools and methods used in the mining industry for surface and underground mining options. and transition planning It is of particular importance in dealing with deep, complex deposits that are amenable to both open pit and underground mining. in this study A comprehensive literature review and gap analysis matrix were used to identify limitations and opportunities for further research on underground surface mining options and transition optimization for planning. Comprehensive resource development

Combining Indicators: Maximizing Mining Returns In New York Forex Strategies

Surface mining is known to be quite productive, more economical and safer for workers compared to underground mining for optimal deposits. However, recent evolutions in environmental regulations and societal expectations It may result in the development of high-quality small-scale deposits by shallow open pits (OP) or in the establishment of high-quality underground mines (UG) in lieu of extensive OP operations [1]. Both the surface mining method and the UG mining method result in maximum economic decisions by identifying the best mining options for accumulation. in planning resource development Resource utilization optimization is largely dependent on the mining options used to extract data. It is used by researchers and experts to refer to initiatives or alternatives undertaken in the mining industry to expand, change, postpone, abandon or adopt strategies for mining methods and sometimes investment opportunities. depending on changes in economic, technological or market conditions [2, 3, 4, 5, 6, 7, 8, 9, 10]. Such minerals can be used in various forms. of open pit excavation, underground excavation or both

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Some studies have been conducted to address surface-underground mining options and transition optimization (SUMOTO) problems. These studies focus on determining the depth of transition and determining the outcome production for Implementation of OP and UG mining using a simple optimization framework. These models do not broadly address the multi-objective optimization nature of the SUMOTO problem. and does not define the problem with a complete description of the mining environment in practice. especially Existing models do not include necessary development infrastructure such as access to primary and secondary mines. ventilation requirements and geotechnical support and reinforcement in the optimization framework. Results from these models often lead to local optimum solutions or biased solutions that often cannot be applied in the mining environment [2, 3, 11, 12, 13, 14, 15. , 16, 17, 18, 19, 20, 21, 22, 23, 24].

Existing optimization algorithms that are used to try to solve the problem of mining options include the Lerchs-Grossman (LG) algorithm, the Seymour algorithm, the floating cone technique, the flow of networks, dynamic programming, neural networks, graph theory, and mathematical formulas [25]. Some authors have studied underground surface mining options and transitional optimization problems with commercial software packages. Available include Surpac Vision, Datamine’s NPV Scheduler, Whittle Four-X, Geovia MineSched, Datamine’s Integrated 3D CAD System, Vulcan, MineScape, MineSight, Isatis, XPAC, Mining Reserve Optimizer (MRO). , Blasor Hole Optimizer, COMET’s Grading and Timing Optimizer, and Datamine Studio 3 [7, 9, 17, 26, 27]. situation and often leads to local optimization solutions.

Although Bakhtavar, Shahriar and Oraee [3] used behavioral study algorithms to compare calculated economic block values ​​for both open pit mining and underground mining on a depth-flow basis to solve the SUMOTO problem, the results from Heuristic algorithms do not provide a measure of optimal fit. The same is true in the case of mathematical programming optimization. Famous author who used mathematical programming to solve mining transitional problems. limit their model to determining transition depths and block separation sequences for open pit and underground mining [2, 4, 8, 9, 11, 12, 13, 14, 15, 17, 18, 19, 24, 25, 28, 29]. Similarly other authors A random mathematical programming model was developed to solve the underground surface mining choice and transition optimization problems. They focus on determining the depth of change in the 2D environment and excluding other necessary underground mining constraints such as primary and secondary development. Development of ventilation shafts and geotechnical requirements for opening and stopping development in the optimization framework [7, 20, 30, 31]. As underground mining performance improvements are computationally complex [32] and integration This combined with open pit mining makes it more challenging [33].

Positioning the desired crown pillar thickness in the SUMOTO problem is the key to the operation of such mines. Some authors pre-select the depth of the crown post. (Transition depth) before evaluating the section above the crown pillar for open pit excavation. and the part under the crown pillar for underground excavation [4, 18, 25, 27, 28]. This may lead to improper solution. And several pillar positions will need to be assessed in a situational approach. Some authors attempted to include the position of pillars in the optimization process [14, 24, 30, 31, 34, 35]. But there are some limitations such as ventilation requirements. and the strength properties of the stone required for actual use. The transition from OP to UG mining is a complex geomechanical process that is required to consider the rock mass properties [36, 37].

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Bakhtavar [12] has reviewed the combination of open pit and underground mining methods over the past decade. And noticed that the transition problem was applied in both concurrent or non-concurrent mode. He asserts that asynchronous hybrid mining is more acceptable. This is because the method of exploring large underground caves can be used with high productivity and low cost. However, in simultaneous mode, It is more feasible to cut horizontal and vertical slices using underhand and filling with cement backfill with OP Afum, Ben-Awuah and Askari-Nasab [35] excavations. The mathematics that helps an optimization approach decide whether a mineral deposit should be exploited simultaneously, incoherently, sequentially, or in any combination of these.

Most commonly available models do not include the required underground mining infrastructure requirements, such as core access to the underground mine. (Ventilation or reduction or further development) Ventilation development Similarly, operational development (levels, ore and waste drives, cross-sections) and required vertical development (ore passes, raises) are required. These existing models do not incorporate rock strength properties into the SUMOTO problem, although the critical infrastructure and geotechnical characteristics of these rock formations are important for underground mining. But the added complexity makes it difficult to include in the SUMOTO model. According to Bullock [38], mine planning is an iterative process. This involves considering many different options and determining which one will provide the best long-term results. Using such an iterative process can lead to inferior or suboptimal solutions that do not constitute a global optimal solution.

In summary, this paper reviews the relevant literature on algorithms and models for SUMOTO, identifying gaps and opportunities that can be explored for further research and application in the mining industry. and further recommends the importance of using mathematical programs for resource planning that are amenable to both options. Figure 1 is a schematic representation of surface and underground mining operations.

Combining Indicators: Maximizing Mining Returns In New York Forex Strategies

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