Modelling Gold Production Using Sigmoid Models

Researcher: Ignitious Chauke, University of VendaSupervisor: Dr Caston Sigauke, University of Venda This study approximate monthly gold production from Sibanye-Stillwater South Africa (SA) gold operations based on five sigmoid models. The studied models were Gompertz, Gaussian, Probit and the Hill, which were used to forecast the future.

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Electoral Accountability in South Africa

Researcher: Leslie Dwolatzky, University of the Witwatersrand, JohannesburgSupervisor: Prof. Rod Alence, University of the Witwatersrand, Johannesburg This research project investigates the relationship between change in support for the ANC and the change in the provision of public services at the electoral ward level. The project replicates the

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Prediction of Lightning in South Africa using an LSTM Neural Network Model using Historical Lightning Data

Researcher: Yaseen Essa , University of the Witwatersrand, JohannesburgSupervisors: Dr Ritesh Ajoodah and Dr Hugh Hunt , University of the Witwatersrand, Johannesburg We evaluated the prediction ability of the Long-Short Term-Memory-Recurrent Neural Network (LSTM) model to predict short-term lightening flash densities within South Africa using historical lightening

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Rural Governance and Financial Inclusion: Does Rural Governance Matter in the Financial Inclusion in Developing Countries

Researcher: Takunda Pfigu, University of the Witwatersrand, JohannesburgSupervisor: Dr Nyasha Mahonye, University of the Witwatersrand, Johannesburg Financial Inclusion : Process that ensures the access to and usage of basic formal financial services for all. It is crucial for local economic development. Rural people, women and poor people

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Optimisation of hybrid neural network techniques used for stock market predictions

Researcher: Mohammad Rehman, University of the Witwatersrand, JohannesburgSupervisor: Dr Wilbert Chagwiza, University of the Witwatersrand, Johannesburg The combination of traditional technical and fundamental analysis techniques and machine learning techniques has become a common practice for informed stock price prediction. The focus of this research was to stochastically

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The classification and clustering of bank telemarketing data using extreme gradient boost and k-prototype techniques

Researcher: Tselahale Serongwa, University of the Witwatersrand, JohannesburgSupervisor: Dr Wilbert Chagwiza, University of the Witwatersrand, Johannesburg The banking sector needs the ability to categorize the customer data they possess to enable business intelligence analytics and improve their marketing strategies. They require trivial automated models that yield interpretable

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Forecasting Accuracy Comparison of Various Machine Learning and Statistical Models on Stock Market Price Movements

Researcher: Ruan Pretorius, University of the Witwatersrand, JohannesburgSupervisors: Prof. Terence van Zyl, University of Johannesburg and Dr Farai Mlambo, University of the Witwatersrand, Johannesburg Accurate financial time series forecasts can assist investors in gaining a competitive edge over other participants in capital markets No empirical conclusion existed

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Medicare fraud detection using extreme g radient boosted machines (XGBoost)

Researcher: Sheena Phillip, University of the Witwatersrand, JohannesburgSupervisor: Dr Wilbert Chagwiza, University of the Witwatersrand, Johannesburg Fraud detection of health care providers is a growing concern worldwide as billions of dollars is lost each year. Medicare publicly released health provider data in order to encourage the development

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Measuring the South African Financial Cycle using Wavelet Analysis

Researcher: By Kabo Phage, University of the Witwatersrand, JohannesburgSupervisor: Prof. Gregory Farrell, University of the Witwatersrand, Johannesburg Financial cycles capture the evolution of risks to financial stability, and it follows that they are important for macro prudential policymakers.  The robust measurement thereof can aid in formulating and

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