Studies In Supervised Machine Learning for Stock Price Prediction

Researcher: Costa Muthai, University of VendaSupervisor: Dr Martins Aramsowna, University of Venda Internet and Web technologies of today not only enable students to interact more freely with educational resources, friends, and teachers, but they also produce enormous amounts of application data that can be assessed to reveal

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Volatility estimate of Telkom shares under GARCH models

Researcher:  Wandile Nhlapho, University of VendaSupervisor: Dr Jean-Claude Ndogmo, University of Venda The study compares the performance of the ARCH (1) and GARCH (1,1) models in estimating and forecasting the volatility of Telkom share prices.  The Telkom shares are estimated using daily data and the above-mentioned volatility models. We

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Battery as the source of energy

Researcher:  Mbabala Tshimangadzo, University of VendaSupervisors: Dr. N.E Maluta , Prof. R.R Maphanga Mr. R.S Dima, University of Venda There is an increase shortage of energy supply and storage, with the human population and fuel price increasing exponentially this increases the demand of energy supply. Considering battery as the

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Aspects of simulated ant agents for creating an ant-inspired ontology

Researcher:  Shirindi Ntshuxeko, Sol Plaatje UniversitySupervisor: Dr Colin Chibaya, Sol Plaatje University A formal knowledge domain has not been well represented in earlier studies.  There has been a lack of a particular set of procedures required to produce an ant ontology.  To create an ant colony ontology, this work

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From Above the Sky to Below the Earth: Crop type classification using satellite imagery and deep learning

Researcher:  Yusuf Mansoor, University of the Witwatersrand, JohannesburgSupervisor: Prof Adam Elhadi, University of the Witwatersrand, Johannesburg Crop type mapping and classification is necessary for optimal cropland management. Remote sensing with satellite imagery has gained popularity due to the ease of accessibility and availability.  For this study deep learning neural

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Solving electricity crisis in SA

Researcher:  Kgothatso Makubyane, University of LimpopoSupervisor: Dr Caston Sigauke, University of Venda According to Council for Scientific and Industrial Research (CSIR), South Africa is experiencing the worse year of load shedding. However, the is a solution to this obstacle Renewable energy resources (Wind, Sun and Water). The primary subject

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Automatic Karyotyping using Image Semantic Segmentation to Separate Overlapping Chromosomes

Researcher:  Boineelo Sekori, Sol Plaatje UniversitySupervisors:  Dr Albert Whata, Sol Plaatje University This study aims to automate karyotyping to successfully separate the overlapping human chromosomes.  The objectives are as follows:1. Automate semantic segmentation task for separating overlapping chromosomes.2. Perform human karyotype chromosome segmentation using deep learning algorithms.3. Assessing

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