Predictive Model of Rock Fragmentation Using the Neuro-Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) to Estimate Fragmentation Size in Open Pit Mining

Vergara, Betty; Torres, M F Arcocha; Aramburú, Vidal; Raymundo, Carlos

doi:10.1007/978-3-030-80462-6_16

Cited by 4 publications

(1 citation statement)

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“…The article "Predictive Model of Rock Fragmentation Using the Neuro-Fuzzy Inference System (ANFIS) and Particle Swarm Optimization (PSO) to Estimate Fragmentation Size in Open Pit Mining" [7] by Betty Vergara and others describes a predictive model used to estimate rock fragmentation size using the ANFIS in combination with Particle Swarm Optimization (PSO). Utilizing statistical measures such as the correlation coefficient (R2) and mean square error (RMSE), the study determined that the ANFIS-PSO model, with an R2 value of 0.85 and an RMSE value of 0.78, can be considered a dependable and satisfactory model for predicting rock fragmentation in the field.…”

Section: Literature Reviewmentioning

confidence: 99%

Determining the Availability of Continuous Systems in Open Pits Using ANFIS and a Simulation Model

Gomilanovic,

Bugaric,

Bankovic

et al. 2024

Energies

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This paper presents a model for determining the availability of continuous systems at open pits using the neuro-fuzzy system. The concept of availability is divided into partial indicators (synthetic indicators and sub-indicators). The presented model in relation to already existing models for determining availability uses a combination of the advantages of artificial neural networks and fuzzy logic. The case study addressed the I ECC (bucket wheel excavator–conveyors–crushing plant) system of the open pit Drmno, Kostolac. In this paper, in addition to the ANFIS model for determining the availability of continuous systems, a simulation model was developed. The obtained results of the ANFIS model were verified with the help of a simulation model that uses certain assumptions about the distribution of failures. This paper was created as a result of several years of field and theoretical research into the availability of continuous systems in open pits, and completes a cycle that consists of several published articles on the subject of modeling the behavior of these systems in real time using a time picture of the state, expert assessment, simulation and AI models, while respecting the multidisciplinarity of the problem (mining technological, mechanical, and information technological aspects). The developed ANFIS model is a key instrument for improving operational efficiency and resource management in the mining sector. Its ability to accurately predict the availability of the ECC system brings not only operational benefits through reduced downtime and optimized maintenance, but also a potential reduction in overall costs at coal open pits. Such an innovative model marks a significant step forward in the mining industry, especially when it comes to continuous systems in coal open pits.

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Section: Literature Reviewmentioning

confidence: 99%