Browsing Engineering, Built Environment and Information Technology by Subject "Machine learning"
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Browsing Engineering, Built Environment and Information Technology by Subject "Machine learning"
Now showing items 1-20 of 42
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(CEUR Workshop Proceedings, 2022)The AAAI 2022 Spring Symposium on Machine Learning and Knowledge Engineering for Hybrid Intelligence (AAAI-MAKE 2022) brought together researchers and practitioners of the two fields to reflect on advances in combining ...
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AI meets CRNs : a prospective review on the application of deep architectures in spectrum management (Institute of Electrical and Electronics Engineers, 2021-08)The spectrum low utilization and high demand conundrum created a bottleneck towards ful lling the requirements of next-generation networks. The cognitive radio (CR) technology was advocated as a de facto technology to ...
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(Taylor and Francis, 2024)Building construction collapse in Nigeria has become a subject of international concern in recent times due to numerous lives and properties being wasted yearly. This study presents a brief statistical report of building ...
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(Springer Open, 2019-04-12)The threat to critical water system infrastructure has increased in recent years as is evident from the increasing number of reported attacks against these systems. Preventative security mechanisms are often not enough ...
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(Institute of Electrical and Electronics Engineers, 2018-05)The three articles in this special section focus on the development of automated design of machine learning and search algorithms. There is a demand, especially from industry and business, to automate the design of machine ...
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(University of Pretoria, 2020-12)Learning rate schedule parameters remain some of the most sensitive hyperparameters in machine learning, as well as being challenging to resolve, in particular when mini-batch subsampling is considered. Mini-batch sub-sampling ...
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(Institute of Electrical and Electronics Engineers, 2020)There has been an increasing number of attacks against critical water system infrastructure in recent years. This is largely due to the fact that these systems are heavily dependent on computer networks meaning that an ...
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(MDPI, 2022-05-31)This article presents a cloud-based method to classify 0-day attacks from a novel dataset called UGRansome1819. The primary objective of the research is to classify potential unknown threats using Machine Learning (ML) ...
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(University of Pretoria, 2018)This thesis compares the profitability of trading rules evolved by a single population genetic program (GP), a co-operative co-evolved GP, and a competitive co-evolved GP. Profitability was determined by trading thirteen ...
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(Easychair, 2023)Automated hate speech detection is important to protecting people’s dignity, online experiences, and physical safety in Society 5.0. Transformers are sophisticated pre-trained language models that can be fine-tuned for ...
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(European Geosciences Union, 2019-12-10)Over the last decade, advanced statistical inference and machine learning have been used to fill the gaps in sparse surface ocean CO2 measurements (Rödenbeck et al., 2015). The estimates from these methods have been ...
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(Computer Society of South Africa, 2006-06)Sampling of large datasets for data mining is important for at least two reasons. The processing of large amounts of data results in increased computational complexity. The cost of this additional complexity may not be ...
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(Elsevier, 2020-02)The selection of an appropriate descriptive system and modeling framework to capture system dynamics and support process control applications is a fundamental problem in the operation of industrial processes. In this study, ...
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(MDPI, 2020-05-27)Data integrity in wireless sensor networks (WSN) is very important because incorrect or missing values could result in the system making suboptimal or catastrophic decisions. Data imputation allows for a system to ...
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(CEUR Workshop Proceedings, 2021)Knowledge and knowledge work are essential for the success of companies nowadays. Decisions are based on knowledge and better knowledge leads to more informed decisions. Therefore, the management of knowledge and support ...
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(Institute of Electrical and Electronics Engineers, 2022-08)In this study, we conducted a bibliometric analysis and comprehensive review of the studies published between the period of 2012 and 2022 on resource management in internet of things (IoT) networks using the Scopus database ...
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Digital forensics supported by machine learning for the detection of online sexual predatory chats (Elsevier, 2021-03)Chat-logs are informative digital footprints available on Social Media Platforms (SMPs). With the rise of cybercrimes targeting children, chat-logs can be used to discover and flag harmful behaviour for the attention of ...
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(University of Pretoria, 2017)The digital in-line holographic configuration is motivated by the goal of developing a portable, cost effective sensor system for pre-screening patient blood samples. The theory of holography is explained from the foundational ...
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(Nature Research, 2024-01)This work examines the application of machine learning (ML) algorithms to evaluate dissolved gas analysis (DGA) data to quickly identify incipient faults in oil-immersed transformers (OITs). Transformers are pivotal equipment ...
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(Public Library of Science, 2022-06-09)One of the most precise methods to detect prostate cancer is by evaluation of a stained biopsy by a pathologist under a microscope. Regions of the tissue are assessed and graded according to the observed histological ...
Now showing items 1-20 of 42