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Inter-cell interference coordination in 5G ultra-dense networks
Published 2021“…Conventionally, the formulated optimization is transformed from non-convex to convex problem. …”
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Load balancing using cell range expansion in LTE advanced heterogeneous networks
Published 2016“…A price update mechanism based on a suboptimal solution of a network utility optimization problem is used to adapt the CRE bias. The price is derived from the load status of each pico base station. …”
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A Comparison Between Machine Learning Techniques to Find Leaks in Pipe Networks
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Deep Reinforcement Learning-Based Approaches for the MPPT Control of Standalone Solar PV Systems
Published 2025“…Reinforcement learning (RL) is a model-free optimization approach that can learn solar PV behaviour and store and reuse optimization information for future optimization tasks. …”
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The design of public transit networks with heuristic algorithms : case study Cape Town
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An algorithmic approach to continuous location
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Hierarchical model predictive control of a venlo-type greenhouse
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Fitness Landscape Analysis for the Differential Evolution Algorithm
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Selection Hyper-heuristics for Population-based Meta-heuristics in Continuous Dynamic Environments
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Plastic bags waste management using the knapsack model case study: trashy bags, Accra
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Routing in packet switched computer communication networks
Published 2023“…This thesis concerns the optimization of the routing path in packet-switched computer-communication networks. …”
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Resource allocation mechanism for multiuser multichannel cognitive radio networks
Published 2018“…The advantages of the DPM mechanism in optimizing the performance of CRN is also revealed by the formulation and solution of the optimization problem. …”
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Operational cost and emissions minimisation of a multi-microgrid system through energy management
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Energy-water management and minimal cost solution in residences
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Decision support for the production and distribution of electricity under load shedding
Published 2016“…In this research project we study two optimization problems related to load shedding. The first is how load shedding can be integrated into the unit commitment problem. …”
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Mitigation of control errors in quantum annealing
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Time series forecasting using neural networks without recurrent connections
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