Erkan Topal

Professor

Curtin University

Australia

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Professor Erkan Topal is a faculty member at Curtin University in Australia. His research areas include underground mine planning, machine learning applications in mining, and analytical modeling of geological stress orientations. Recent articles highlight his work on predictive models for mining operations, sustainable scheduling methods, and the impact of investor behavior on commodities during global events.

Erkan Topal

Research Interests

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Articles (20)

Interval combination prediction of mine tunnel air volume using improved spiking neural network for error correction

A novel model for sustainable production scheduling of an open-pit mining complex considering waste encapsulation

Concurrent optimisation of open pit ore and waste movement with optimal haul road selection

Mine Closure Surveillance and Feasibility of UAV–AI–MR Technology: A Review Study

The future of underground mine planning in the era of machine learning: Opportunities for engineering robustness and flexibility

Development of Novel Hybrid Intelligent Predictive Models for Dilution Prediction in Underground Sub-level Mining

An analytical modelling of the rotation of in-situ principal stresses orientation in the vicinity of an underground opening

A new layered rock constitutive model incorporating confining pressure and bedding angle weights based on orthogonal matrix analysis

A heuristic method for production scheduling of an open pit mining operation

Investor Behavior in Gold, US Dollars and Cryptocurrency during Global Pandemics

A review of open pit mine and waste dump schedule planning

Reliability and availability artificial intelligence models for predicting blast-induced ground vibration intensity in open-pit mines to ensure the safety of the surroundings

Review of machine learning application in mine blasting

Performance of different models in iron ore price prediction during the time of commodity price spike

Relationship of iron ore price with other major commodity prices

Mineral grade estimation using gradient boosting regression trees

Pattern search method for accelerating Stope boundary optimization problem in underground mining operations

A new ore grade estimation using combine machine learning algorithms

Development of 3D rock fragmentation measurement system using photogrammetry

Transformation of the Australian mining industry and future prospects

Collaborators (3)

Ping Chang

Phillip Stothard

Elham Mardaneh

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